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  • Data Quality and Master Data Management Resources

    - by Dejan Sarka
    Many companies or organizations do regular data cleansing. When you cleanse the data, the data quality goes up to some higher level. The data quality level is determined by the amount of work invested in the cleansing. As time passes, the data quality deteriorates, and you need to repeat the cleansing process. If you spend an equal amount of effort as you did with the previous cleansing, you can expect the same level of data quality as you had after the previous cleansing. And then the data quality deteriorates over time again, and the cleansing process starts over and over again. The idea of Data Quality Services is to mitigate the cleansing process. While the amount of time you need to spend on cleansing decreases, you will achieve higher and higher levels of data quality. While cleansing, you learn what types of errors to expect, discover error patterns, find domains of correct values, etc. You don’t throw away this knowledge. You store it and use it to find and correct the same issues automatically during your next cleansing process. The following figure shows this graphically. The idea of master data management, which you can perform with Master Data Services (MDS), is to prevent data quality from deteriorating. Once you reach a particular quality level, the MDS application—together with the defined policies, people, and master data management processes—allow you to maintain this level permanently. This idea is shown in the following picture. OK, now you know what DQS and MDS are about. You can imagine the importance on maintaining the data quality. Here are some resources that help you preparing and executing the data quality (DQ) and master data management (MDM) activities. Books Dejan Sarka and Davide Mauri: Data Quality and Master Data Management with Microsoft SQL Server 2008 R2 – a general introduction to MDM, MDS, and data profiling. Matching explained in depth. Dejan Sarka, Matija Lah and Grega Jerkic: MCTS Self-Paced Training Kit (Exam 70-463): Building Data Warehouses with Microsoft SQL Server 2012 – I wrote quite a few chapters about DQ and MDM, and introduced also SQL Server 2012 DQS. Thomas Redman: Data Quality: The Field Guide – you should start with this book. Thomas Redman is the father of DQ and MDM. Tyler Graham: Microsoft SQL Server 2012 Master Data Services – MDS in depth from a product team mate. Arkady Maydanchik: Data Quality Assessment – data profiling in depth. Tamraparni Dasu, Theodore Johnson: Exploratory Data Mining and Data Cleaning – advanced data profiling with data mining. Forthcoming presentations I am presenting a DQS and MDM seminar at PASS SQL Rally Amsterdam 2013: Wednesday, November 6th, 2013: Enterprise Information Management with SQL Server 2012 – a good kick start to your first DQ and / or MDM project. Courses Data Quality and Master Data Management with SQL Server 2012 – I wrote a 2-day course for SolidQ. If you are interested in this course, which I could also deliver in a shorter seminar way, you can contact your closes SolidQ subsidiary, or, of course, me directly on addresses [email protected] or [email protected]. This course could also complement the existing courseware portfolio of training providers, which are welcome to contact me as well. Start improving the quality of your data now!

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  • How to enable telnet with port 3306 during Master to master replication on MySQL Server

    - by Mainio
    I am trying to do Master to Master Replication in Windows Server 2008. I am successfully able to replicate all the database of Master 1 to Master 2. But I am unable to replicate the changes made on Master 2 to Master 1. Later on I found that, I can telnet to Master 1 from Master 2 with port 3306 but I am not able on telnet from Master 1 to Master 2. When I check netstat on both Master. I found the following result. I couldn't publish my public IP so I put name as Master 1 and Master 2 for their respective IP Master 1 C:\Users\XXXXX>netstat Active Connections Proto Local Address Foreign Address State TCP Master 1:3306 Master 2:61566 ESTABLISHED TCP Master 1:3389 My remote:56053 ESTABLISHED TCP 127.0.0.1:3306 Master 1:60675 ESTABLISHED TCP 127.0.0.1:3306 Master 1:60712 ESTABLISHED TCP 127.0.0.1:60675 Master 1:3306 ESTABLISHED TCP 127.0.0.1:60712 Master 1:3306 ESTABLISHED Master 2 C:\Users\XXXX>netstat Active Connections Proto Local Address Foreign Address State TCP Master 2:3389 My remote:56124 ESTABLISHED TCP Master 2:61566 Master 1:3306 ESTABLISHED TCP Master 2:61574 bil-sc-cm02:http ESTABLISHED TCP 127.0.0.1:3306 Master 2:61562 ESTABLISHED TCP 127.0.0.1:3306 Master 2:61563 ESTABLISHED TCP 127.0.0.1:61562 Master 2:3306 ESTABLISHED TCP 127.0.0.1:61563 Master 2:3306 ESTABLISHED TCP 127.0.0.1:61573 Master 2:3306 TIME_WAIT All shows that In my master 2, port 3306 is not activate. Now I need solution over here. How can I figure it. Your small suggestion would be million for me. Thank you Regards, Udhyan

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  • MySQL Master-Master w/ multiple read slave cost effective setup in AWS

    - by Ross
    I've been evaluating Amazon Web Services RDS for MySQL and costing out potential scenarios involving a simple multi-AZ deployment read/write setup vs. a multi-AZ deployment mysql master (hot-standby) with additional read-only slaves. the issue I'm trying to cost-optimize includes their reserved instance vs on-demand instances. Situation 1: purchase reserved multi-az setup for Extra-large-hi-mem(17GB RAM) instance for $5200/yr and have my application query the master all the time. the problem is, if I don't need all the resources of the (17GB RAM) all the time and therefore, especially not a hot-standby, what alternatives for savings can a better topology create, like potentially situation 2 below: Situation 2: purchase reserved multi-az setup using smaller master instances than above for the master-master hot-standby to receive the writes only. Then create and load balance several read-only slaves off the master and add/remove and/or scale up/down the read slaves based on demand. This might only cost $1000 + the on-demand usage of the read slaves. My thinking is, if I have a variable read-intensive application load, with low write load, the single level topology in situation 1 means I'm paying for a lot of resources at the write level of topology when I don't need them there. My hope is that situation 2 can yield cost savings from smaller reserved instances on the master-master resource level allowing me to scale up and down and/or out on the read-level according to demand as needed. Does anyone see a downside to doing this or know of some reason this isn't possible with RDS? Any other thoughts or advice always welcome of course. Thanks in advance, R

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  • Automatic Storage Management (ASM)

    - by jean-marc.gaudron(at)oracle.com
    Master Note for Automatic Storage Management (ASM) (Doc ID 1187723.1)This Master Note is intended to provide an index and references to the most frequently used My Oracle Support Notes with respect to Oracle Automatic Storage Management (ASM) environments. This Master Note is subdivided into categories to allow for easy access and reference to notes that are applicable to your area of interest. This includes the following categories: Automatic Storage Management (ASM) Concepts and Overview Automatic Storage Management (ASM) Installation Automatic Storage Management (ASM) Configuration Automatic Storage Management (ASM) Administration Automatic Storage Management (ASM) Migration and Upgrade Automatic Storage Management (ASM) Monitoring Automatic Storage Management (ASM) Troubleshooting and Debugging Automatic Storage Management (ASM) Best Practices Automatic Storage Management (ASM) Versions and Patches ASMLIB Database Machine, Exadata Storage Server and RAC Documentation Using My Oracle Support Effectively

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  • Big Data – Learning Basics of Big Data in 21 Days – Bookmark

    - by Pinal Dave
    Earlier this month I had a great time to write Bascis of Big Data series. This series received great response and lots of good comments I have received, I am going to follow up this basics series with further in-depth series in near future. Here is the consolidated blog post where you can find all the 21 days blog posts together. Bookmark this page for future reference. Big Data – Beginning Big Data – Day 1 of 21 Big Data – What is Big Data – 3 Vs of Big Data – Volume, Velocity and Variety – Day 2 of 21 Big Data – Evolution of Big Data – Day 3 of 21 Big Data – Basics of Big Data Architecture – Day 4 of 21 Big Data – Buzz Words: What is NoSQL – Day 5 of 21 Big Data – Buzz Words: What is Hadoop – Day 6 of 21 Big Data – Buzz Words: What is MapReduce – Day 7 of 21 Big Data – Buzz Words: What is HDFS – Day 8 of 21 Big Data – Buzz Words: Importance of Relational Database in Big Data World – Day 9 of 21 Big Data – Buzz Words: What is NewSQL – Day 10 of 21 Big Data – Role of Cloud Computing in Big Data – Day 11 of 21 Big Data – Operational Databases Supporting Big Data – RDBMS and NoSQL – Day 12 of 21 Big Data – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21 Big Data – Operational Databases Supporting Big Data – Columnar, Graph and Spatial Database – Day 14 of 21 Big DataData Mining with Hive – What is Hive? – What is HiveQL (HQL)? – Day 15 of 21 Big Data – Interacting with Hadoop – What is PIG? – What is PIG Latin? – Day 16 of 21 Big Data – Interacting with Hadoop – What is Sqoop? – What is Zookeeper? – Day 17 of 21 Big Data – Basics of Big Data Analytics – Day 18 of 21 Big Data – How to become a Data Scientist and Learn Data Science? – Day 19 of 21 Big Data – Various Learning Resources – How to Start with Big Data? – Day 20 of 21 Big Data – Final Wrap and What Next – Day 21 of 21 Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Get your Master Immersion learning on!

    - by AaronBertrand
    Time is running out to register for the Master Immersion training events being held in Dallas, TX by SQLskills . These particular events will be instructed by Paul Randal ( blog | twitter ), Kimberly Tripp ( blog | twitter ), and Brent Ozar ( blog | twitter ) and reflect the new format for the Microsoft Certified Master (MCM) program. This means training in the low 4 figures instead of close to $20K, and that you can take at your own pace. We at SQL Sentry ( twitter ) are quite proud to be the exclusive...(read more)

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  • Get your Master Immersion learning on!

    - by AaronBertrand
    Time is running out to register for the Master Immersion training events being held in Dallas, TX by SQLskills . These particular events will be instructed by Paul Randal ( blog | twitter ), Kimberly Tripp ( blog | twitter ), and Brent Ozar ( blog | twitter ) and reflect the new format for the Microsoft Certified Master (MCM) program. This means training in the low 4 figures instead of close to $20K, and that you can take at your own pace. We at SQL Sentry ( twitter ) are quite proud to be the exclusive...(read more)

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  • mysql master-master setup as a way to simply master-slave promotion

    - by Chris Go
    I'm trying to see if the following plan is viable. Goal here is to be able to do HA (uptime) and not necessarily for load -- writes are fine on one MySQL 5.5 server (with innodb) but not really possible when the database is down. Currently, I have a master-slave replication setup which works fine except it doesn't have automatic promotion (obviously). what I am planning on doing is setup master-master replication to possibly do this "automatic promotion" using Amazon Route 53 DNS Failover (Health checks). What I am trying to avoid is to NOT have to do the auto-increment trick because the "business folks" got used to the auto-incrementing PK as consecutive numbers (yeah, I know this is bad but data is from 2004). So, setup the master-master replication WITHOUT the auto-increment collision prevention bit. The primary master is db1.domain.com and secondary master is db2.domain.com In Amazon Route 53, setup DNS Failover record for db.domain.com - primary failover is db1.domain.com - with a TCP healthcheck on IP address port 3306 - secondary failover is db2.domain.com - with a TCP healthcheck on IP address port 3306 Most of the time (99%), unless tcp://db1.domain.com:3306 is dead, db1.domain.com will be served up on DNS hits to db.domain.com. In fact, hopefully this is 100%. The possible downsides of this is the loss of a primary key (collision) and I think I am OK with losing one order. We are a low data volume B2B business and can just call our client up if this occurs (like an order disappearing). Does this sound like a good plan? Then I will also run another slave replication on db1.domain.com as "master" to a slave-db1.domain.com -- not sure why, maybe for heavy SELECTs?

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  • Master Data Services Employees Sample Model

    - by Davide Mauri
    I’ve been playing with Master Data Services quite a lot in those last days and I’m also monitoring the web for all available resources on it. Today I’ve found this freshly released sample available on MSDN Code Gallery: SQL Server Master Data Services Employee Sample Model http://code.msdn.microsoft.com/SSMDSEmployeeSample This sample shows how Recursive Hierarchies can be modeled in order to represent a typical organizational chart scenario where a self-relationship exists on the Employee entity. Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Data Quality Through Data Governance

    Data Quality Governance Data quality is very important to every organization, bad data cost an organization time, money, and resources that could be prevented if the proper governance was put in to place.  Data Governance Program Criteria: Support from Executive Management and all Business Units Data Stewardship Program  Cross Functional Team of Data Stewards Data Governance Committee Quality Structured Data It should go without saying but any successful project in today’s business world must get buy in from executive management and all stakeholders involved with the project. If management does not fully support a project because they see it is in there and the company’s best interest then they will remove/eliminate funding, resources and allocated time to work on the project. In essence they can render a project dead until it is official killed by the business. In addition, buy in from stake holders is also very important because they can cause delays increased spending in time, money and resources because they do not support a project. Data Stewardship programs are administered by a data steward manager who primary focus is to support, train and manage a cross functional data stewards team. A cross functional team of data stewards are pulled from various departments act to ensure that all systems work to ensure that an organization’s goals are achieved. Typically, data stewards are subject matter experts that act as mediators between their respective departments and IT. Data Quality Procedures Data Governance Committees are composed of data stewards, Upper management, IT Leadership and various subject matter experts depending on a company. The primary goal of this committee is to define strategic goals, coordinate activities, set data standards and offer data guidelines for the business. Data Quality Policies In 1997, Claudia Imhoff defined a Data Stewardship’s responsibility as to approve business naming standards, develop consistent data definitions, determine data aliases, develop standard calculations and derivations, document the business rules of the corporation, monitor the quality of the data in the data warehouse, define security requirements, and so forth. She further explains data stewards responsible for creating and enforcing polices on the following but not limited to issues. Resolving Data Integration Issues Determining Data Security Documenting Data Definitions, Calculations, Summarizations, etc. Maintaining/Updating Business Rules Analyzing and Improving Data Quality

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  • Failed to connect from slave to master with error "error connecting to master (1045)"

    - by Victor Lin
    I try to setup replication from slave to the master. CHANGE MASTER TO MASTER_HOST = 'master', MASTER_PORT = 3306, MASTER_USER = 'repl', MASTER_PASSWORD = 'xxx'; And I did grant privileges to the user on master. I can connect with mysql command from slave machine to the master mysql -h master -u repl -p mysql> show grants; GRANT RELOAD, SUPER, REPLICATION SLAVE, CREATE USER ON *.* TO 'repl'@'xxx' IDENTIFIED BY PASSWORD 'xxx' mysql> select 1; +---+ | 1 | +---+ | 1 | +---+ 1 row in set (0.04 sec) As you can see, privileges are correct, connection works fine, but however, the connection for replication to master always failed. mysql> show slave status\G *************************** 1. row *************************** Slave_IO_State: Connecting to master Master_Host: master Master_User: repl Master_Port: 3306 Connect_Retry: 60 Master_Log_File: Read_Master_Log_Pos: 4 Relay_Log_File: slave-replay-bin.000002 Relay_Log_Pos: 4 Relay_Master_Log_File: Slave_IO_Running: Connecting Slave_SQL_Running: Yes Replicate_Do_DB: Replicate_Ignore_DB: Replicate_Do_Table: Replicate_Ignore_Table: Replicate_Wild_Do_Table: Replicate_Wild_Ignore_Table: Last_Errno: 0 Last_Error: Skip_Counter: 0 Exec_Master_Log_Pos: 0 Relay_Log_Space: 107 Until_Condition: None Until_Log_File: Until_Log_Pos: 0 Master_SSL_Allowed: No Master_SSL_CA_File: Master_SSL_CA_Path: Master_SSL_Cert: Master_SSL_Cipher: Master_SSL_Key: Seconds_Behind_Master: NULL Master_SSL_Verify_Server_Cert: No Last_IO_Errno: 1045 Last_IO_Error: error connecting to master 'repl@master:3306' - retry-time: 60 retries: 86400 Last_SQL_Errno: 0 Last_SQL_Error: Replicate_Ignore_Server_Ids: Master_Server_Id: 0 1 row in set (0.00 sec) Is this caused by different version of MySQL server? The version of master is 5.0.77, and the slave is 5.5.13. But all articles I could find tell me that it's okay to replicate from a newer slave to old master. How to solve this problem? -- Update -- I even try to upgrade the old MySQL, but still, the problem is not solved. mysql> show slave status\G *************************** 1. row *************************** Slave_IO_State: Connecting to master Master_Host: master Master_User: repl Master_Port: 3306 Connect_Retry: 60 Master_Log_File: master-bin.000007 Read_Master_Log_Pos: 107 Relay_Log_File: slave-replay-bin.000001 Relay_Log_Pos: 4 Relay_Master_Log_File: master-bin.000007 Slave_IO_Running: Connecting Slave_SQL_Running: Yes Replicate_Do_DB: Replicate_Ignore_DB: Replicate_Do_Table: Replicate_Ignore_Table: Replicate_Wild_Do_Table: Replicate_Wild_Ignore_Table: Last_Errno: 0 Last_Error: Skip_Counter: 0 Exec_Master_Log_Pos: 107 Relay_Log_Space: 107 Until_Condition: None Until_Log_File: Until_Log_Pos: 0 Master_SSL_Allowed: No Master_SSL_CA_File: Master_SSL_CA_Path: Master_SSL_Cert: Master_SSL_Cipher: Master_SSL_Key: Seconds_Behind_Master: NULL Master_SSL_Verify_Server_Cert: No Last_IO_Errno: 1045 Last_IO_Error: error connecting to master 'repl@master' - retry-time: 60 retries: 86400 Last_SQL_Errno: 0 Last_SQL_Error: Replicate_Ignore_Server_Ids: Master_Server_Id: 0 1 row in set (0.00 sec)

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  • Failed to connect from slave to master with error "error connecting to master (1045)"

    - by Victor Lin
    I try to setup replication from slave to the master. CHANGE MASTER TO MASTER_HOST = 'master', MASTER_PORT = 3306, MASTER_USER = 'repl', MASTER_PASSWORD = 'xxx'; And I did grant privileges to the user on master. I can connect with mysql command from slave machine to the master mysql -h master -u repl -p mysql> show grants; GRANT RELOAD, SUPER, REPLICATION SLAVE, CREATE USER ON *.* TO 'repl'@'xxx' IDENTIFIED BY PASSWORD 'xxx' mysql> select 1; +---+ | 1 | +---+ | 1 | +---+ 1 row in set (0.04 sec) As you can see, privileges are correct, connection works fine, but however, the connection for replication to master always failed. mysql> show slave status\G *************************** 1. row *************************** Slave_IO_State: Connecting to master Master_Host: master Master_User: repl Master_Port: 3306 Connect_Retry: 60 Master_Log_File: Read_Master_Log_Pos: 4 Relay_Log_File: slave-replay-bin.000002 Relay_Log_Pos: 4 Relay_Master_Log_File: Slave_IO_Running: Connecting Slave_SQL_Running: Yes Replicate_Do_DB: Replicate_Ignore_DB: Replicate_Do_Table: Replicate_Ignore_Table: Replicate_Wild_Do_Table: Replicate_Wild_Ignore_Table: Last_Errno: 0 Last_Error: Skip_Counter: 0 Exec_Master_Log_Pos: 0 Relay_Log_Space: 107 Until_Condition: None Until_Log_File: Until_Log_Pos: 0 Master_SSL_Allowed: No Master_SSL_CA_File: Master_SSL_CA_Path: Master_SSL_Cert: Master_SSL_Cipher: Master_SSL_Key: Seconds_Behind_Master: NULL Master_SSL_Verify_Server_Cert: No Last_IO_Errno: 1045 Last_IO_Error: error connecting to master 'repl@master:3306' - retry-time: 60 retries: 86400 Last_SQL_Errno: 0 Last_SQL_Error: Replicate_Ignore_Server_Ids: Master_Server_Id: 0 1 row in set (0.00 sec) Is this caused by different version of MySQL server? The version of master is 5.0.77, and the slave is 5.5.13. But all articles I could find tell me that it's okay to replicate from a newer slave to old master. How to solve this problem? -- Update -- I even try to upgrade the old MySQL, but still, the problem is not solved. mysql> show slave status\G *************************** 1. row *************************** Slave_IO_State: Connecting to master Master_Host: master Master_User: repl Master_Port: 3306 Connect_Retry: 60 Master_Log_File: master-bin.000007 Read_Master_Log_Pos: 107 Relay_Log_File: slave-replay-bin.000001 Relay_Log_Pos: 4 Relay_Master_Log_File: master-bin.000007 Slave_IO_Running: Connecting Slave_SQL_Running: Yes Replicate_Do_DB: Replicate_Ignore_DB: Replicate_Do_Table: Replicate_Ignore_Table: Replicate_Wild_Do_Table: Replicate_Wild_Ignore_Table: Last_Errno: 0 Last_Error: Skip_Counter: 0 Exec_Master_Log_Pos: 107 Relay_Log_Space: 107 Until_Condition: None Until_Log_File: Until_Log_Pos: 0 Master_SSL_Allowed: No Master_SSL_CA_File: Master_SSL_CA_Path: Master_SSL_Cert: Master_SSL_Cipher: Master_SSL_Key: Seconds_Behind_Master: NULL Master_SSL_Verify_Server_Cert: No Last_IO_Errno: 1045 Last_IO_Error: error connecting to master 'repl@master' - retry-time: 60 retries: 86400 Last_SQL_Errno: 0 Last_SQL_Error: Replicate_Ignore_Server_Ids: Master_Server_Id: 0 1 row in set (0.00 sec)

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  • SQL SERVER – Advanced Data Quality Services with Melissa Data – Azure Data Market

    - by pinaldave
    There has been much fanfare over the new SQL Server 2012, and especially around its new companion product Data Quality Services (DQS). Among the many new features is the addition of this integrated knowledge-driven product that enables data stewards everywhere to profile, match, and cleanse data. In addition to the homegrown rules that data stewards can design and implement, there are also connectors to third party providers that are hosted in the Azure Datamarket marketplace.  In this review, I leverage SQL Server 2012 Data Quality Services, and proceed to subscribe to a third party data cleansing product through the Datamarket to showcase this unique capability. Crucial Questions For the purposes of the review, I used a database I had in an Excel spreadsheet with name and address information. Upon a cursory inspection, there are miscellaneous problems with these records; some addresses are missing ZIP codes, others missing a city, and some records are slightly misspelled or have unparsed suites. With DQS, I can easily add a knowledge base to help standardize my values, such as for state abbreviations. But how do I know that my address is correct? And if my address is not correct, what should it be corrected to? The answer lies in a third party knowledge base by the acknowledged USPS certified address accuracy experts at Melissa Data. Reference Data Services Within DQS there is a handy feature to actually add reference data from many different third-party Reference Data Services (RDS) vendors. DQS simplifies the processes of cleansing, standardizing, and enriching data through custom rules and through service providers from the Azure Datamarket. A quick jump over to the Datamarket site shows me that there are a handful of providers that offer data directly through Data Quality Services. Upon subscribing to these services, one can attach a DQS domain or composite domain (fields in a record) to a reference data service provider, and begin using it to cleanse, standardize, and enrich that data. Besides what I am looking for (address correction and enrichment), it is possible to subscribe to a host of other services including geocoding, IP address reference, phone checking and enrichment, as well as name parsing, standardization, and genderization.  These capabilities extend the data quality that DQS has natively by quite a bit. For my current address correction review, I needed to first sign up to a reference data provider on the Azure Data Market site. For this example, I used Melissa Data’s Address Check Service. They offer free one-month trials, so if you wish to follow along, or need to add address quality to your own data, I encourage you to sign up with them. Once I subscribed to the desired Reference Data Provider, I navigated my browser to the Account Keys within My Account to view the generated account key, which I then inserted into the DQS Client – Configuration under the Administration area. Step by Step to Guide That was all it took to hook in the subscribed provider -Melissa Data- directly to my DQS Client. The next step was for me to attach and map in my Reference Data from the newly acquired reference data provider, to a domain in my knowledge base. On the DQS Client home screen, I selected “New Knowledge Base” under Knowledge Base Management on the left-hand side of the home screen. Under New Knowledge Base, I typed a Name and description of my new knowledge base, then proceeded to the Domain Management screen. Here I established a series of domains (fields) and then linked them all together as a composite domain (record set). Using the Create Domain button, I created the following domains according to the fields in my incoming data: Name Address Suite City State Zip I added a Suite column in my domain because Melissa Data has the ability to return missing Suites based on last name or company. And that’s a great benefit of using these third party providers, as they have data that the data steward would not normally have access to. The bottom line is, with these third party data providers, I can actually improve my data. Next, I created a composite domain (fulladdress) and added the (field) domains into the composite domain. This essentially groups our address fields together in a record to facilitate the full address cleansing they perform. I then selected my newly created composite domain and under the Reference Data tab, added my third party reference data provider –Melissa Data’s Address Check- and mapped in each domain that I had to the provider’s Schema. Now that my composite domain has been married to the Reference Data service, I can take the newly published knowledge base and create a project to cleanse and enrich my data. My next task was to create a new Data Quality project, mapping in my data source and matching it to the appropriate domain column, and then kick off the verification process. It took just a few minutes with some progress indicators indicating that it was working. When the process concluded, there was a helpful set of tabs that place the response records into categories: suggested; new; invalid; corrected (automatically); and correct. Accepting the suggestions provided by  Melissa Data allowed me to clean up all the records and flag the invalid ones. It is very apparent that DQS makes address data quality simplistic for any IT professional. Final Note As I have shown, DQS makes data quality very easy. Within minutes I was able to set up a data cleansing and enrichment routine within my data quality project, and ensure that my address data was clean, verified, and standardized against real reference data. As reviewed here, it’s easy to see how both SQL Server 2012 and DQS work to take what used to require a highly skilled developer, and empower an average business or database person to consume external services and clean data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology Tagged: DQS

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  • ? ORACLE MASTER ????? ????

    - by Urakawa
    ORACLE MASTER 11g?ORACLE MASTER Expert???????????ORACLE MASTER ?????????????????????? ??????????????????????????????1?????????? ????ORACLE MASTER??????11g????????????Expert??????????????????????????????

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  • Oracle Enterprise Manager 11g Application Management Suite for Oracle E-Business Suite Now Available

    - by chung.wu
    Oracle Enterprise Manager 11g Application Management Suite for Oracle E-Business Suite is now available. The management suite combines features that were available in the standalone Application Management Pack for Oracle E-Business Suite and Application Change Management Pack for Oracle E-Business Suite with Oracle's market leading real user monitoring and configuration management capabilities to provide the most complete solution for managing E-Business Suite applications. The features that were available in the standalone management packs are now packaged into Oracle E-Business Suite Plug-in 4.0, which is now fully certified with Oracle Enterprise Manager 11g Grid Control. This latest plug-in extends Grid Control with E-Business Suite specific management capabilities and features enhanced change management support. In addition, this latest release of Application Management Suite for Oracle E-Business Suite also includes numerous real user monitoring improvements. General Enhancements This new release of Application Management Suite for Oracle E-Business Suite offers the following key capabilities: Oracle Enterprise Manager 11g Grid Control Support: All components of the management suite are certified with Oracle Enterprise Manager 11g Grid Control. Built-in Diagnostic Ability: This release has numerous major enhancements that provide the necessary intelligence to determine if the product has been installed and configured correctly. There are diagnostics for Discovery, Cloning, and User Monitoring that will validate if the appropriate patches, privileges, setups, and profile options have been configured. This feature improves the setup and configuration time to be up and operational. Lifecycle Automation Enhancements Application Management Suite for Oracle E-Business Suite provides a centralized view to monitor and orchestrate changes (both functional and technical) across multiple Oracle E-Business Suite systems. In this latest release, it provides even more control and flexibility in managing Oracle E-Business Suite changes.Change Management: Built-in Diagnostic Ability: This latest release has numerous major enhancements that provide the necessary intelligence to determine if the product has been installed and configured correctly. There are diagnostics for Customization Manager, Patch Manager, and Setup Manager that will validate if the appropriate patches, privileges, setups, and profile options have been configured. Enhancing the setup time and configuration time to be up and operational. Customization Manager: Multi-Node Custom Application Registration: This feature automates the process of registering and validating custom products/applications on every node in a multi-node EBS system. Public/Private File Source Mappings and E-Business Suite Mappings: File Source Mappings & E-Business Suite Mappings can be created and marked as public or private. Only the creator/owner can define/edit his/her own mappings. Users can use public mappings, but cannot edit or change settings. Test Checkout Command for Versions: This feature allows you to test/verify checkout commands at the version level within the File Source Mapping page. Prerequisite Patch Validation: You can specify prerequisite patches for Customization packages and for Release 12 Oracle E-Business Suite packages. Destination Path Population: You can now automatically populate the Destination Path for common file types during package construction. OAF File Type Support: Ability to package Oracle Application Framework (OAF) customizations and deploy them across multiple Oracle E-Business Suite instances. Extended PLL Support: Ability to distinguish between different types of PLLs (that is, Report and Forms PLL files). Providing better granularity when managing PLL objects. Enhanced Standard Checker: Provides greater and more comprehensive list of coding standards that are verified during the package build process (for example, File Driver exceptions, Java checks, XML checks, SQL checks, etc.) HTML Package Readme: The package Readme is in HTML format and includes the file listing. Advanced Package Search Capabilities: The ability to utilize more criteria within the advanced search package (that is, Public, Last Updated by, Files Source Mapping, and E-Business Suite Mapping). Enhanced Package Build Notifications: More detailed information on the results of a package build process. Better, more detailed troubleshooting guidance in the event of build failures. Patch Manager:Staged Patches: Ability to run Patch Manager with no external internet access. Customer can download Oracle E-Business Suite patches into a shared location for Patch Manager to access and apply. Supports highly secured production environments that prohibit external internet connections. Support for Superseded Patches: Automatic check for superseded patches. Allows users to easily add superseded patches into the Patch Run. More comprehensive and correct Patch Runs. Removes many manual and laborious tasks, frees up Apps DBAs for higher value-added tasks. Automatic Primary Node Identification: Users can now specify which is the "primary node" (that is, which node hosts the Shared APPL_TOP) during the Patch Run interview process, available for Release 12 only. Setup Manager:Preview Extract Results: Ability to execute an extract in "proof mode", and examine the query results, to determine accuracy. Used in conjunction with the "where" clause in Advanced Filtering. This feature can provide better and more accurate fine tuning of extracts. Use Uploaded Extracts in New Projects: Ability to incorporate uploaded extracts in new projects via new LOV fields in package construction. Leverages the Setup Manager repository to access extracts that have been uploaded. Allows customer to reuse uploaded extracts to provision new instances. Re-use Existing (that is, historical) Extracts in New Projects: Ability to incorporate existing extracts in new projects via new LOV fields in package construction. Leverages the Setup Manager repository to access point-in-time extracts (snapshots) of configuration data. Allows customer to reuse existing extracts to provision new instances. Allows comparative historical reporting of identical APIs, executed at different times. Support for BR100 formats: Setup Manager can now automatically produce reports in the BR100 format. Native support for industry standard formats. Concurrent Manager API Support: General Foundation now provides an API for management of "Concurrent Manager" configuration data. Ability to migrate Concurrent Managers from one instance to another. Complete the setup once and never again; no need to redefine the Concurrent Managers. User Experience Management Enhancements Application Management Suite for Oracle E-Business Suite includes comprehensive capabilities for user experience management, supporting both real user and synthetic transaction based user monitoring techniques. This latest release of the management suite include numerous improvements in real user monitoring support. KPI Reporting: Configurable decimal precision for reporting of KPI and SLA values. By default, this is two decimal places. KPI numerator and denominator information. It is now possible to view KPI numerator and denominator information, and to have it available for export. Content Messages Processing: The application content message facility has been extended to distinguish between notifications and errors. In addition, it is now possible to specify matching rules that can be used to refine a selected content message specification. Note this is only available for XPath-based (not literal) message contents. Data Export: The Enriched data export facility has been significantly enhanced to provide improved performance and accessibility. Data is no longer stored within XML-based files, but is now stored within the Reporter database. However, it is possible to configure an alternative database for its storage. Access to the export data is through SQL. With this enhancement, it is now more easy than ever to use tools such as Oracle Business Intelligence Enterprise Edition to analyze correlated data collected from real user monitoring and business data sources. SNMP Traps for System Events: Previously, the SNMP notification facility was only available for KPI alerting. It has now been extended to support the generation of SNMP traps for system events, to provide external health monitoring of the RUEI system processes. Performance Improvements: Enhanced dashboard performance. The dashboard facility has been enhanced to support the parallel loading of items. In the case of dashboards containing large numbers of items, this can result in a significant performance improvement. Initial period selection within Data Browser and reports. The User Preferences facility has been extended to allow you to specify the initial period selection when first entering the Data Browser or reports facility. The default is the last hour. Performance improvement when querying the all sessions group. Technical Prerequisites, Download and Installation Instructions The Linux version of the plug-in is available for immediate download from Oracle Technology Network or Oracle eDelivery. For specific information regarding technical prerequisites, product download and installation, please refer to My Oracle Support note 1224313.1. The following certifications are in progress: * Oracle Solaris on SPARC (64-bit) (9, 10) * HP-UX Itanium (11.23, 11.31) * HP-UX PA-RISC (64-bit) (11.23, 11.31) * IBM AIX on Power Systems (64-bit) (5.3, 6.1)

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  • Big Data – Is Big Data Relevant to me? – Big Data Questionnaires – Guest Post by Vinod Kumar

    - by Pinal Dave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions of SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. I think the series from Pinal is a good one for anyone planning to start on Big Data journey from the basics. In my daily customer interactions this buzz of “Big Data” always comes up, I react generally saying – “Sir, do you really have a ‘Big Data’ problem or do you have a big Data problem?” Generally, there is a silence in the air when I ask this question. Data is everywhere in organizations – be it big data, small data, all data and for few it is bad data which is same as no data :). Wow, don’t discount me as someone who opposes “Big Data”, I am a big supporter as much as I am a critic of the abuse of this term by the people. In this post, I wanted to let my mind flow so that you can also think in the direction I want you to see these concepts. In any case, this is not an exhaustive dump of what is in my mind – but you will surely get the drift how I am going to question Big Data terms from customers!!! Is Big Data Relevant to me? Many of my customers talk to me like blank whiteboard with no idea – “why Big Data”. They want to jump into the bandwagon of technology and they want to decipher insights from their unexplored data a.k.a. unstructured data with structured data. So what are these industry scenario’s that come to mind? Here are some of them: Financials Fraud detection: Banks and Credit cards are monitoring your spending habits on real-time basis. Customer Segmentation: applies in every industry from Banking to Retail to Aviation to Utility and others where they deal with end customer who consume their products and services. Customer Sentiment Analysis: Responding to negative brand perception on social or amplify the positive perception. Sales and Marketing Campaign: Understand the impact and get closer to customer delight. Call Center Analysis: attempt to take unstructured voice recordings and analyze them for content and sentiment. Medical Reduce Re-admissions: How to build a proactive follow-up engagements with patients. Patient Monitoring: How to track Inpatient, Out-Patient, Emergency Visits, Intensive Care Units etc. Preventive Care: Disease identification and Risk stratification is a very crucial business function for medical. Claims fraud detection: There is no precise dollars that one can put here, but this is a big thing for the medical field. Retail Customer Sentiment Analysis, Customer Care Centers, Campaign Management. Supply Chain Analysis: Every sensors and RFID data can be tracked for warehouse space optimization. Location based marketing: Based on where a check-in happens retail stores can be optimize their marketing. Telecom Price optimization and Plans, Finding Customer churn, Customer loyalty programs Call Detail Record (CDR) Analysis, Network optimizations, User Location analysis Customer Behavior Analysis Insurance Fraud Detection & Analysis, Pricing based on customer Sentiment Analysis, Loyalty Management Agents Analysis, Customer Value Management This list can go on to other areas like Utility, Manufacturing, Travel, ITES etc. So as you can see, there are obviously interesting use cases for each of these industry verticals. These are just representative list. Where to start? A lot of times I try to quiz customers on a number of dimensions before starting a Big Data conversation. Are you getting the data you need the way you want it and in a timely manner? Can you get in and analyze the data you need? How quickly is IT to respond to your BI Requests? How easily can you get at the data that you need to run your business/department/project? How are you currently measuring your business? Can you get the data you need to react WITHIN THE QUARTER to impact behaviors to meet your numbers or is it always “rear-view mirror?” How are you measuring: The Brand Customer Sentiment Your Competition Your Pricing Your performance Supply Chain Efficiencies Predictive product / service positioning What are your key challenges of driving collaboration across your global business?  What the challenges in innovation? What challenges are you facing in getting more information out of your data? Note: Garbage-in is Garbage-out. Hold good for all reporting / analytics requirements Big Data POCs? A number of customers get into the realm of setting a small team to work on Big Data – well it is a great start from an understanding point of view, but I tend to ask a number of other questions to such customers. Some of these common questions are: To what degree is your advanced analytics (natural language processing, sentiment analysis, predictive analytics and classification) paired with your Big Data’s efforts? Do you have dedicated resources exploring the possibilities of advanced analytics in Big Data for your business line? Do you plan to employ machine learning technology while doing Advanced Analytics? How is Social Media being monitored in your organization? What is your ability to scale in terms of storage and processing power? Do you have a system in place to sort incoming data in near real time by potential value, data quality, and use frequency? Do you use event-driven architecture to manage incoming data? Do you have specialized data services that can accommodate different formats, security, and the management requirements of multiple data sources? Is your organization currently using or considering in-memory analytics? To what degree are you able to correlate data from your Big Data infrastructure with that from your enterprise data warehouse? Have you extended the role of Data Stewards to include ownership of big data components? Do you prioritize data quality based on the source system (that is Facebook/Twitter data has lower quality thresholds than radio frequency identification (RFID) for a tracking system)? Do your retention policies consider the different legal responsibilities for storing Big Data for a specific amount of time? Do Data Scientists work in close collaboration with Data Stewards to ensure data quality? How is access to attributes of Big Data being given out in the organization? Are roles related to Big Data (Advanced Analyst, Data Scientist) clearly defined? How involved is risk management in the Big Data governance process? Is there a set of documented policies regarding Big Data governance? Is there an enforcement mechanism or approach to ensure that policies are followed? Who is the key sponsor for your Big Data governance program? (The CIO is best) Do you have defined policies surrounding the use of social media data for potential employees and customers, as well as the use of customer Geo-location data? How accessible are complex analytic routines to your user base? What is the level of involvement with outside vendors and third parties in regard to the planning and execution of Big Data projects? What programming technologies are utilized by your data warehouse/BI staff when working with Big Data? These are some of the important questions I ask each customer who is actively evaluating Big Data trends for their organizations. These questions give you a sense of direction where to start, what to use, how to secure, how to analyze and more. Sign off Any Big data is analysis is incomplete without a compelling story. The best way to understand this is to watch Hans Rosling – Gapminder (2:17 to 6:06) videos about the third world myths. Don’t get overwhelmed with the Big Data buzz word, the destination to what your data speaks is important. In this blog post, we did not particularly look at any Big Data technologies. This is a set of questionnaire one needs to keep in mind as they embark their journey of Big Data. I did write some of the basics in my blog: Big Data – Big Hype yet Big Opportunity. Do let me know if these questions make sense?  Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Big Data – Basics of Big Data Architecture – Day 4 of 21

    - by Pinal Dave
    In yesterday’s blog post we understood how Big Data evolution happened. Today we will understand basics of the Big Data Architecture. Big Data Cycle Just like every other database related applications, bit data project have its development cycle. Though three Vs (link) for sure plays an important role in deciding the architecture of the Big Data projects. Just like every other project Big Data project also goes to similar phases of the data capturing, transforming, integrating, analyzing and building actionable reporting on the top of  the data. While the process looks almost same but due to the nature of the data the architecture is often totally different. Here are few of the question which everyone should ask before going ahead with Big Data architecture. Questions to Ask How big is your total database? What is your requirement of the reporting in terms of time – real time, semi real time or at frequent interval? How important is the data availability and what is the plan for disaster recovery? What are the plans for network and physical security of the data? What platform will be the driving force behind data and what are different service level agreements for the infrastructure? This are just basic questions but based on your application and business need you should come up with the custom list of the question to ask. As I mentioned earlier this question may look quite simple but the answer will not be simple. When we are talking about Big Data implementation there are many other important aspects which we have to consider when we decide to go for the architecture. Building Blocks of Big Data Architecture It is absolutely impossible to discuss and nail down the most optimal architecture for any Big Data Solution in a single blog post, however, we can discuss the basic building blocks of big data architecture. Here is the image which I have built to explain how the building blocks of the Big Data architecture works. Above image gives good overview of how in Big Data Architecture various components are associated with each other. In Big Data various different data sources are part of the architecture hence extract, transform and integration are one of the most essential layers of the architecture. Most of the data is stored in relational as well as non relational data marts and data warehousing solutions. As per the business need various data are processed as well converted to proper reports and visualizations for end users. Just like software the hardware is almost the most important part of the Big Data Architecture. In the big data architecture hardware infrastructure is extremely important and failure over instances as well as redundant physical infrastructure is usually implemented. NoSQL in Data Management NoSQL is a very famous buzz word and it really means Not Relational SQL or Not Only SQL. This is because in Big Data Architecture the data is in any format. It can be unstructured, relational or in any other format or from any other data source. To bring all the data together relational technology is not enough, hence new tools, architecture and other algorithms are invented which takes care of all the kind of data. This is collectively called NoSQL. Tomorrow Next four days we will answer the Buzz Words – Hadoop. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Big Data – Evolution of Big Data – Day 3 of 21

    - by Pinal Dave
    In yesterday’s blog post we answered what is the Big Data. Today we will understand why and how the evolution of Big Data has happened. Though the answer is very simple, I would like to tell it in the form of a history lesson. Data in Flat File In earlier days data was stored in the flat file and there was no structure in the flat file.  If any data has to be retrieved from the flat file it was a project by itself. There was no possibility of retrieving the data efficiently and data integrity has been just a term discussed without any modeling or structure around. Database residing in the flat file had more issues than we would like to discuss in today’s world. It was more like a nightmare when there was any data processing involved in the application. Though, applications developed at that time were also not that advanced the need of the data was always there and there was always need of proper data management. Edgar F Codd and 12 Rules Edgar Frank Codd was a British computer scientist who, while working for IBM, invented the relational model for database management, the theoretical basis for relational databases. He presented 12 rules for the Relational Database and suddenly the chaotic world of the database seems to see discipline in the rules. Relational Database was a promising land for all the unstructured database users. Relational Database brought into the relationship between data as well improved the performance of the data retrieval. Database world had immediately seen a major transformation and every single vendors and database users suddenly started to adopt the relational database models. Relational Database Management Systems Since Edgar F Codd proposed 12 rules for the RBDMS there were many different vendors who started them to build applications and tools to support the relationship between database. This was indeed a learning curve for many of the developer who had never worked before with the modeling of the database. However, as time passed by pretty much everybody accepted the relationship of the database and started to evolve product which performs its best with the boundaries of the RDBMS concepts. This was the best era for the databases and it gave the world extreme experts as well as some of the best products. The Entity Relationship model was also evolved at the same time. In software engineering, an Entity–relationship model (ER model) is a data model for describing a database in an abstract way. Enormous Data Growth Well, everything was going fine with the RDBMS in the database world. As there were no major challenges the adoption of the RDBMS applications and tools was pretty much universal. There was a race at times to make the developer’s life much easier with the RDBMS management tools. Due to the extreme popularity and easy to use system pretty much every data was stored in the RDBMS system. New age applications were built and social media took the world by the storm. Every organizations was feeling pressure to provide the best experience for their users based the data they had with them. While this was all going on at the same time data was growing pretty much every organization and application. Data Warehousing The enormous data growth now presented a big challenge for the organizations who wanted to build intelligent systems based on the data and provide near real time superior user experience to their customers. Various organizations immediately start building data warehousing solutions where the data was stored and processed. The trend of the business intelligence becomes the need of everyday. Data was received from the transaction system and overnight was processed to build intelligent reports from it. Though this is a great solution it has its own set of challenges. The relational database model and data warehousing concepts are all built with keeping traditional relational database modeling in the mind and it still has many challenges when unstructured data was present. Interesting Challenge Every organization had expertise to manage structured data but the world had already changed to unstructured data. There was intelligence in the videos, photos, SMS, text, social media messages and various other data sources. All of these needed to now bring to a single platform and build a uniform system which does what businesses need. The way we do business has also been changed. There was a time when user only got the features what technology supported, however, now users ask for the feature and technology is built to support the same. The need of the real time intelligence from the fast paced data flow is now becoming a necessity. Large amount (Volume) of difference (Variety) of high speed data (Velocity) is the properties of the data. The traditional database system has limits to resolve the challenges this new kind of the data presents. Hence the need of the Big Data Science. We need innovation in how we handle and manage data. We need creative ways to capture data and present to users. Big Data is Reality! Tomorrow In tomorrow’s blog post we will try to answer discuss Basics of Big Data Architecture. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • ModSecurity compile error on nginx

    - by user146481
    I'm trying to install ModSecurity on nginx with the following instructions : wget https://github.com/SpiderLabs/ModSecurity/archive/master.zip unzip master cd ModSecurity-master ./autogen.sh ./configure --enable-standalone-module And i got the following error : Checking plataform... Identified as Linux configure: looking for Apache module support via DSO through APXS configure: error: couldn't find APXS After installing httpd-devel httpd-devel and running ./configure --enable-standalone-module --with-apxs=/usr/sbin/apxs ; make modsecurity compile workes but still have another error of nginx compilation : ./configure --add-module=/usr/local/src/john/ModSecurity-master/nginx/modsecurity and i got this error : gcc -c -pipe -O -W -Wall -Wpointer-arith -Wno-unused-parameter -Werror -g -I src/core -I src/event -I src/event/modules -I src/os/unix -I /usr/include/apache2 -I /usr/include/apr-1.0 -I /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone -I /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2 -I /usr/include/libxml2 -I objs -I src/http -I src/http/modules -I src/mail \ -o objs/addon/modsecurity/ngx_http_modsecurity.o \ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:20:23: error: http_core.h: No such file or directory /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:21:26: error: http_request.h: No such file or directory In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:37, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_logging.h:41:23: error: apr_pools.h: No such file or directory In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:38, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_multipart.h:26:25: error: apr_general.h: No such file or directory /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_multipart.h:27:24: error: apr_tables.h: No such file or directory In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:38, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_multipart.h:44: error: expected specifier-qualifier-list before ‘apr_array_header_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_multipart.h:65: error: expected specifier-qualifier-list before ‘apr_array_header_t’ cc1: warnings being treated as errors /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_multipart.h:135: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_multipart.h:135: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_multipart.h:135: error: expected ‘,’ or ‘;’ before ‘multipart_cleanup’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_multipart.h:137: error: expected declaration specifiers or ‘...’ before ‘apr_table_t’ In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:39, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_pcre.h:41: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_pcre.h:45: error: expected ‘)’ before ‘*’ token In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:40, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:19:27: error: apr_file_info.h: No such file or directory In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:41, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:29, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:40, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/persist_dbm.h:21: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/persist_dbm.h:21: error: type defaults to ‘int’ in declaration of ‘apr_table_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/persist_dbm.h:21: error: expected ‘,’ or ‘;’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/persist_dbm.h:24: error: expected declaration specifiers or ‘...’ before ‘apr_table_t’ In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:42, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:29, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:40, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:20:19: error: httpd.h: No such file or directory /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:21:24: error: ap_release.h: No such file or directory /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:24:26: error: apr_optional.h: No such file or directory In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:42, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:29, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:40, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:30: error: expected declaration specifiers or ‘...’ before ‘modsec_register_tfn’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:30: error: expected declaration specifiers or ‘...’ before ‘(’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:30: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:30: error: type defaults to ‘int’ in declaration of ‘APR_DECLARE_OPTIONAL_FN’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:31: error: expected declaration specifiers or ‘...’ before ‘modsec_register_operator’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:31: error: expected declaration specifiers or ‘...’ before ‘(’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:31: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:31: error: type defaults to ‘int’ in declaration of ‘APR_DECLARE_OPTIONAL_FN’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:32: error: expected declaration specifiers or ‘...’ before ‘modsec_register_variable’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:33: error: expected declaration specifiers or ‘...’ before ‘(’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:32: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:36: error: type defaults to ‘int’ in declaration of ‘APR_DECLARE_OPTIONAL_FN’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:37: error: expected declaration specifiers or ‘...’ before ‘modsec_register_reqbody_processor’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:37: error: expected declaration specifiers or ‘...’ before ‘(’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:37: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:37: error: type defaults to ‘int’ in declaration of ‘APR_DECLARE_OPTIONAL_FN’ In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:42, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:29, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:40, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:56: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:58: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:65: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:65: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:65: error: expected ‘,’ or ‘;’ before ‘input_filter’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:68: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:68: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:68: error: expected ‘,’ or ‘;’ before ‘output_filter’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:70: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:70: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:70: error: expected ‘,’ or ‘;’ before ‘read_request_body’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:77: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:77: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:77: error: expected ‘,’ or ‘;’ before ‘send_error_bucket’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:83: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:85: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:93: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/apache2.h:95: error: expected ‘)’ before ‘*’ token In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:29, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:40, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:43:25: error: http_config.h: No such file or directory In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:29, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:40, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:59: error: expected declaration specifiers or ‘...’ before ‘apr_array_header_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:61: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:61: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:61: error: expected ‘,’ or ‘;’ before ‘collection_original_setvar’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:63: error: expected declaration specifiers or ‘...’ before ‘apr_pool_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:67: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:70: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:75: error: expected declaration specifiers or ‘...’ before ‘apr_array_header_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:76: error: expected declaration specifiers or ‘...’ before ‘apr_pool_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:86: error: expected specifier-qualifier-list before ‘apr_pool_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:94: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:101: error: expected specifier-qualifier-list before ‘apr_pool_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:111: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:111: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:111: error: expected ‘,’ or ‘;’ before ‘msre_ruleset_process_phase’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:113: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:113: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:113: error: expected ‘,’ or ‘;’ before ‘msre_ruleset_process_phase_internal’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:115: error: expected declaration specifiers or ‘...’ before ‘apr_pool_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:143: error: expected specifier-qualifier-list before ‘apr_ipsubnet_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:149: error: expected specifier-qualifier-list before ‘apr_array_header_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:189: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:219: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:235: error: expected specifier-qualifier-list before ‘fn_tfn_execute_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:239: error: expected declaration specifiers or ‘...’ before ‘fn_tfn_execute_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:258: error: expected declaration specifiers or ‘...’ before ‘apr_table_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:258: error: expected declaration specifiers or ‘...’ before ‘apr_pool_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:285: error: expected specifier-qualifier-list before ‘apr_table_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:341: error: expected declaration specifiers or ‘...’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:341: error: type defaults to ‘int’ in declaration of ‘apr_status_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:341: error: ‘apr_status_t’ declared as function returning a function /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:341: error: ‘apr_status_t’ redeclared as different kind of symbol /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:113: note: previous declaration of ‘apr_status_t’ was here /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:342: error: expected declaration specifiers or ‘...’ before ‘apr_pool_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:342: error: ‘fn_action_execute_t’ declared as function returning a function /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:369: error: expected specifier-qualifier-list before ‘fn_action_init_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:399: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:403: error: expected declaration specifiers or ‘...’ before ‘apr_array_header_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:403: error: ‘msre_parse_vars’ declared as function returning a function /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/re.h:415: error: expected specifier-qualifier-list before ‘apr_size_t’ In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:40, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:54: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:62: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:66: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:68: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:70: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:74: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:76: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:82: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:88: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:90: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:92: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:100: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:102: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:104: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:106: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:108: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:110: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:112: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:114: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:128: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:132: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:136: error: expected ‘)’ before ‘*’ token /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:140: error: data definition has no type or storage class /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:140: error: type defaults to ‘int’ in declaration of ‘apr_fileperms_t’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:140: error: expected ‘,’ or ‘;’ before ‘mode2fileperms’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_util.h:144: error: expected declaration specifiers or ‘...’ before ‘apr_pool_t’ In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:41, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_xml.h:43: error: ‘xml_cleanup’ declared as function returning a function In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:42, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_geo.h:38:25: error: apr_file_io.h: No such file or directory In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:42, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_geo.h:58: error: expected specifier-qualifier-list before ‘apr_file_t’ In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:43, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_gsb.h:22:22: error: apr_hash.h: No such file or directory In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:43, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_gsb.h:25: error: expected specifier-qualifier-list before ‘apr_file_t’ In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:44, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_unicode.h:25: error: expected specifier-qualifier-list before ‘apr_file_t’ In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:46, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/msc_crypt.h:34: error: expected ‘)’ before ‘*’ token In file included from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../standalone/api.h:23, from /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:28: /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:48:23: error: ap_config.h: No such file or directory /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:49:21: error: apr_md5.h: No such file or directory /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:50:25: error: apr_strings.h: No such file or directory /usr/local/src/john/ModSecurity-master/nginx/modsecurity/../../apache2/modsecurity.h:54:22: error: http_log.h: No such file or directory /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:938: error: ‘ngx_http_modsecurity_ctx_t’ has no member named ‘req’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:938: error: too many arguments to function ‘ConvertNgxStringToUTF8’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:942: error: ‘ngx_http_modsecurity_ctx_t’ has no member named ‘req’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:944: error: ‘ngx_http_modsecurity_ctx_t’ has no member named ‘req’ /usr/local/src/john/ModSecurity-master/nginx/modsecurity/ngx_http_modsecurity.c:952: error: ‘modsecurity_read_body_cb’ undeclared (first use in this function) make[1]: *** [objs/addon/modsecurity/ngx_http_modsecurity.o] Error 1 make[1]: Leaving directory `/usr/local/src/john/nginx-1.2.5' make: *** [build] Error 2 Note : I'm using nginx as the only webserver and i do not have apache installed. OS : Centos 6 64bit How can i solve this problem And do you have another easy way to install modsecurity with nginx ?

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  • Working with Temporal Data in SQL Server

    - by Dejan Sarka
    My third Pluralsight course, Working with Temporal Data in SQL Server, is published. I am really proud on the second part of the course, where I discuss optimization of temporal queries. This was a nearly impossible task for decades. First solutions appeared only lately. I present all together six solutions (and one more that is not a solution), and I invented four of them. http://pluralsight.com/training/Courses/TableOfContents/working-with-temporal-data-sql-server

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  • New Communications Industry Data Model with "Factory Installed" Predictive Analytics using Oracle Da

    - by charlie.berger
    Oracle Introduces Oracle Communications Data Model to Provide Actionable Insight for Communications Service Providers   We've integrated pre-installed analytical methodologies with the new Oracle Communications Data Model to deliver automated, simple, yet powerful predictive analytics solutions for customers.  Churn, sentiment analysis, identifying customer segments - all things that can be anticipated and hence, preconcieved and implemented inside an applications.  Read on for more information! TM Forum Management World, Nice, France - 18 May 2010 News Facts To help communications service providers (CSPs) manage and analyze rapidly growing data volumes cost effectively, Oracle today introduced the Oracle Communications Data Model. With the Oracle Communications Data Model, CSPs can achieve rapid time to value by quickly implementing a standards-based enterprise data warehouse that features communications industry-specific reporting, analytics and data mining. The combination of the Oracle Communications Data Model, Oracle Exadata and the Oracle Business Intelligence (BI) Foundation represents the most comprehensive data warehouse and BI solution for the communications industry. Also announced today, Hong Kong Broadband Network enhanced their data warehouse system, going live on Oracle Communications Data Model in three months. The leading provider increased its subscriber base by 37 percent in six months and reduced customer churn to less than one percent. Product Details Oracle Communications Data Model provides industry-specific schema and embedded analytics that address key areas such as customer management, marketing segmentation, product development and network health. CSPs can efficiently capture and monitor critical data and transform it into actionable information to support development and delivery of next-generation services using: More than 1,300 industry-specific measurements and key performance indicators (KPIs) such as network reliability statistics, provisioning metrics and customer churn propensity. Embedded OLAP cubes for extremely fast dimensional analysis of business information. Embedded data mining models for sophisticated trending and predictive analysis. Support for multiple lines of business, such as cable, mobile, wireline and Internet, which can be easily extended to support future requirements. With Oracle Communications Data Model, CSPs can jump start the implementation of a communications data warehouse in line with communications-industry standards including the TM Forum Information Framework (SID), formerly known as the Shared Information Model. Oracle Communications Data Model is optimized for any Oracle Database 11g platform, including Oracle Exadata, which can improve call data record query performance by 10x or more. Supporting Quotes "Oracle Communications Data Model covers a wide range of business areas that are relevant to modern communications service providers and is a comprehensive solution - with its data model and pre-packaged templates including BI dashboards, KPIs, OLAP cubes and mining models. It helps us save a great deal of time in building and implementing a customized data warehouse and enables us to leverage the advanced analytics quickly and more effectively," said Yasuki Hayashi, executive manager, NTT Comware Corporation. "Data volumes will only continue to grow as communications service providers expand next-generation networks, deploy new services and adopt new business models. They will increasingly need efficient, reliable data warehouses to capture key insights on data such as customer value, network value and churn probability. With the Oracle Communications Data Model, Oracle has demonstrated its commitment to meeting these needs by delivering data warehouse tools designed to fill communications industry-specific needs," said Elisabeth Rainge, program director, Network Software, IDC. "The TM Forum Conformance Mark provides reassurance to customers seeking standards-based, and therefore, cost-effective and flexible solutions. TM Forum is extremely pleased to work with Oracle to certify its Oracle Communications Data Model solution. Upon successful completion, this certification will represent the broadest and most complete implementation of the TM Forum Information Framework to date, with more than 130 aggregate business entities," said Keith Willetts, chairman and chief executive officer, TM Forum. Supporting Resources Oracle Communications Oracle Communications Data Model Data Sheet Oracle Communications Data Model Podcast Oracle Data Warehousing Oracle Communications on YouTube Oracle Communications on Delicious Oracle Communications on Facebook Oracle Communications on Twitter Oracle Communications on LinkedIn Oracle Database on Twitter The Data Warehouse Insider Blog

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  • Master Note for Generic Data Warehousing

    - by lajos.varady(at)oracle.com
    ++++++++++++++++++++++++++++++++++++++++++++++++++++ The complete and the most recent version of this article can be viewed from My Oracle Support Knowledge Section. Master Note for Generic Data Warehousing [ID 1269175.1] ++++++++++++++++++++++++++++++++++++++++++++++++++++In this Document   Purpose   Master Note for Generic Data Warehousing      Components covered      Oracle Database Data Warehousing specific documents for recent versions      Technology Network Product Homes      Master Notes available in My Oracle Support      White Papers      Technical Presentations Platforms: 1-914CU; This document is being delivered to you via Oracle Support's Rapid Visibility (RaV) process and therefore has not been subject to an independent technical review. Applies to: Oracle Server - Enterprise Edition - Version: 9.2.0.1 to 11.2.0.2 - Release: 9.2 to 11.2Information in this document applies to any platform. Purpose Provide navigation path Master Note for Generic Data Warehousing Components covered Read Only Materialized ViewsQuery RewriteDatabase Object PartitioningParallel Execution and Parallel QueryDatabase CompressionTransportable TablespacesOracle Online Analytical Processing (OLAP)Oracle Data MiningOracle Database Data Warehousing specific documents for recent versions 11g Release 2 (11.2)11g Release 1 (11.1)10g Release 2 (10.2)10g Release 1 (10.1)9i Release 2 (9.2)9i Release 1 (9.0)Technology Network Product HomesOracle Partitioning Advanced CompressionOracle Data MiningOracle OLAPMaster Notes available in My Oracle SupportThese technical articles have been written by Oracle Support Engineers to provide proactive and top level information and knowledge about the components of thedatabase we handle under the "Database Datawarehousing".Note 1166564.1 Master Note: Transportable Tablespaces (TTS) -- Common Questions and IssuesNote 1087507.1 Master Note for MVIEW 'ORA-' error diagnosis. For Materialized View CREATE or REFRESHNote 1102801.1 Master Note: How to Get a 10046 trace for a Parallel QueryNote 1097154.1 Master Note Parallel Execution Wait Events Note 1107593.1 Master Note for the Oracle OLAP OptionNote 1087643.1 Master Note for Oracle Data MiningNote 1215173.1 Master Note for Query RewriteNote 1223705.1 Master Note for OLTP Compression Note 1269175.1 Master Note for Generic Data WarehousingWhite Papers Transportable Tablespaces white papers Database Upgrade Using Transportable Tablespaces:Oracle Database 11g Release 1 (February 2009) Platform Migration Using Transportable Database Oracle Database 11g and 10g Release 2 (August 2008) Database Upgrade using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007) Platform Migration using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007)Parallel Execution and Parallel Query white papers Best Practices for Workload Management of a Data Warehouse on the Sun Oracle Database Machine (June 2010) Effective resource utilization by In-Memory Parallel Execution in Oracle Real Application Clusters 11g Release 2 (Feb 2010) Parallel Execution Fundamentals in Oracle Database 11g Release 2 (November 2009) Parallel Execution with Oracle Database 10g Release 2 (June 2005)Oracle Data Mining white paper Oracle Data Mining 11g Release 2 (March 2010)Partitioning white papers Partitioning with Oracle Database 11g Release 2 (September 2009) Partitioning in Oracle Database 11g (June 2007)Materialized Views and Query Rewrite white papers Oracle Materialized Views  and Query Rewrite (May 2005) Improving Performance using Query Rewrite in Oracle Database 10g (December 2003)Database Compression white papers Advanced Compression with Oracle Database 11g Release 2 (September 2009) Table Compression in Oracle Database 10g Release 2 (May 2005)Oracle OLAP white papers On-line Analytic Processing with Oracle Database 11g Release 2 (September 2009) Using Oracle Business Intelligence Enterprise Edition with the OLAP Option to Oracle Database 11g (July 2008)Generic white papers Enabling Pervasive BI through a Practical Data Warehouse Reference Architecture (February 2010) Optimizing and Protecting Storage with Oracle Database 11g Release 2 (November 2009) Oracle Database 11g for Data Warehousing and Business Intelligence (August 2009) Best practices for a Data Warehouse on Oracle Database 11g (September 2008)Technical PresentationsA selection of ObE - Oracle by Examples documents: Generic Using Basic Database Functionality for Data Warehousing (10g) Partitioning Manipulating Partitions in Oracle Database (11g Release 1) Using High-Speed Data Loading and Rolling Window Operations with Partitioning (11g Release 1) Using Partitioned Outer Join to Fill Gaps in Sparse Data (10g) Materialized View and Query Rewrite Using Materialized Views and Query Rewrite Capabilities (10g) Using the SQLAccess Advisor to Recommend Materialized Views and Indexes (10g) Oracle OLAP Using Microsoft Excel With Oracle 11g Cubes (how to analyze data in Oracle OLAP Cubes using Excel's native capabilities) Using Oracle OLAP 11g With Oracle BI Enterprise Edition (Creating OBIEE Metadata for OLAP 11g Cubes and querying those in BI Answers) Building OLAP 11g Cubes Querying OLAP 11g Cubes Creating Interactive APEX Reports Over OLAP 11g CubesSelection of presentations from the BIWA website:Extreme Data Warehousing With Exadata  by Hermann Baer (July 2010) (slides 2.5MB, recording 54MB)Data Mining Made Easy! Introducing Oracle Data Miner 11g Release 2 New "Work flow" GUI   by Charlie Berger (May 2010) (slides 4.8MB, recording 85MB )Best Practices for Deploying a Data Warehouse on Oracle Database 11g  by Maria Colgan (December 2009)  (slides 3MB, recording 18MB, white paper 3MB )

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  • Big Data – How to become a Data Scientist and Learn Data Science? – Day 19 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the analytics in Big Data Story. In this article we will understand how to become a Data Scientist for Big Data Story. Data Scientist is a new buzz word, everyone seems to be wanting to become Data Scientist. Let us go over a few key topics related to Data Scientist in this blog post. First of all we will understand what is a Data Scientist. In the new world of Big Data, I see pretty much everyone wants to become Data Scientist and there are lots of people I have already met who claims that they are Data Scientist. When I ask what is their role, I have got a wide variety of answers. What is Data Scientist? Data scientists are the experts who understand various aspects of the business and know how to strategies data to achieve the business goals. They should have a solid foundation of various data algorithms, modeling and statistics methodology. What do Data Scientists do? Data scientists understand the data very well. They just go beyond the regular data algorithms and builds interesting trends from available data. They innovate and resurrect the entire new meaning from the existing data. They are artists in disguise of computer analyst. They look at the data traditionally as well as explore various new ways to look at the data. Data Scientists do not wait to build their solutions from existing data. They think creatively, they think before the data has entered into the system. Data Scientists are visionary experts who understands the business needs and plan ahead of the time, this tremendously help to build solutions at rapid speed. Besides being data expert, the major quality of Data Scientists is “curiosity”. They always wonder about what more they can get from their existing data and how to get maximum out of future incoming data. Data Scientists do wonders with the data, which goes beyond the job descriptions of Data Analysist or Business Analysist. Skills Required for Data Scientists Here are few of the skills a Data Scientist must have. Expert level skills with statistical tools like SAS, Excel, R etc. Understanding Mathematical Models Hands-on with Visualization Tools like Tableau, PowerPivots, D3. j’s etc. Analytical skills to understand business needs Communication skills On the technology front any Data Scientists should know underlying technologies like (Hadoop, Cloudera) as well as their entire ecosystem (programming language, analysis and visualization tools etc.) . Remember that for becoming a successful Data Scientist one require have par excellent skills, just having a degree in a relevant education field will not suffice. Final Note Data Scientists is indeed very exciting job profile. As per research there are not enough Data Scientists in the world to handle the current data explosion. In near future Data is going to expand exponentially, and the need of the Data Scientists will increase along with it. It is indeed the job one should focus if you like data and science of statistics. Courtesy: emc Tomorrow In tomorrow’s blog post we will discuss about various Big Data Learning resources. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Unstructured Data - The future of Data Administration

    Some have claimed that there is a problem with the way data is currently managed using the relational paradigm do to the rise of unstructured data in modern business. PCMag.com defines unstructured data as data that does not reside in a fixed location. They further explain that unstructured data refers to data in a free text form that is not bound to any specific structure. With the rise of unstructured data in the form of emails, spread sheets, images and documents the critics have a right to argue that the relational paradigm is not as effective as the object oriented data paradigm in managing this type of data. The relational paradigm relies heavily on structure and relationships in and between items of data. This type of paradigm works best in a relation database management system like Microsoft SQL, MySQL, and Oracle because data is forced to conform to a structure in the form of tables and relations can be derived from the existence of one or more tables. These critics also claim that database administrators have not kept up with reality because their primary focus in regards to data administration deals with structured data and the relational paradigm. The relational paradigm was developed in the 1970’s as a way to improve data management when compared to standard flat files. Little has changed since then, and modern database administrators need to know more than just how to handle structured data. That is why critics claim that today’s data professionals do not have the proper skills in order to store and maintain data for modern systems when compared to the skills of system designers, programmers , software engineers, and data designers  due to the industry trend of object oriented design and development. I think that they are wrong. I do not disagree that the industry is moving toward an object oriented approach to development with the potential to use more of an object oriented approach to data.   However, I think that it is business itself that is limiting database administrators from changing how data is stored because of the potential costs, and impact that might occur by altering any part of stored data. Furthermore, database administrators like all technology workers constantly are trying to improve their technical skills in order to excel in their job, so I think that accusing data professional is not just when the root cause of the lack of innovation is controlled by business, and it is business that will suffer for their inability to keep up with technology. One way for database professionals to better prepare for the future of database management is start working with data in the form of objects and so that they can extract data from the objects so that the stored information within objects can be used in relation to the data stored in a using the relational paradigm. Furthermore, I think the use of pattern matching will increase with the increased use of unstructured data because object can be selected, filtered and altered based on the existence of a pattern found within an object.

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