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  • Ways to improve completeness of files for data recovery and scanning?

    - by SteveO
    I am using R-studio for data recovery on one of my ntfs partition. There is a pdf file about 16MB, but the software can only recover 15MB of it. So I am thinking about what ways can be used to improve the quality of scanning and recovery by the software? I am looking around its preferences. I am not quite sure whether there are some adjustable parameters for scanning and recovery which can be fine-tuned to improve the quality? R-studio has a free demo version, for which scanning is free,but recovery isn't. It is downloadable from http://www.data-recovery-software.net/Data_Recovery_Download.shtml Its manual is here http://www.r-tt.com/downloads/Recovery_Manual.pdf. I have tried my best to search for answers in the manual, but failed to find one. Their technical support is not as good as their software, and helpless usually in my opinion. Thanks!

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  • Using Microsoft's Chart Controls In An ASP.NET Application: Serializing Chart Data

    In most usage scenarios, the data displayed in a Microsoft Chart control comes from some dynamic source, such as from a database query. The appearance of the chart can be modified dynamically, as well; past installments in this article series showed how to programmatically customize the axes, labels, and other appearance-related settings. However, it is possible to statically define the chart's data and appearance strictly through the control's declarative markup. One of the demos examined in the Getting Started article rendered a column chart with seven columns whose labels and values were defined statically in the <asp:Series> tag's <Points> collection. Given this functionality, it should come as no surprise that the Microsoft Chart Controls also support serialization. Serialization is the process of persisting the state of a control or an object to some other medium, such as to disk. Deserialization is the inverse process, and involves taking the persisted data and recreating the control or object. With just a few lines of code you can persist the appearance settings, the data, or both to a file on disk or to any stream. Likewise, it takes just a few lines of codes to reconstitute a chart from the persisted information. This article shows how to use the Microsoft Chart Control's serialization functionality by examining a demo application that allows users to create custom charts, specifying the data to plot and some appearance-related settings. The user can then save a "snapshot" of this chart, which persists its appearance and data to a record in a database. From another page, users can view these saved chart snapshots. Read on to learn more! Read More >

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  • Oracle Database Security Protecting the Oracle IRM Schema

    - by Simon Thorpe
    Acquiring the Information Rights Management technology in 2006 was part of Oracle's strategic security vision and IRM compliments nicely the overall Oracle security set of solutions. A year ago I spoke about how Oracle has solutions that can help companies protect information throughout its entire life cycle. With our acquisition of Sun this set of solutions has solidified and has even extended down to the operating system and hardware level. Oracle can now offer customers technology that protects their data from the disk, through the database to documents on the desktop! With the recent release of Oracle IRM 11g I was tasked to configure demonstration and evaluation environments and I thought it would make a nice story to leverage some of the security features in the latest release of the Oracle Database. After building these environments I thought I would put together a simple video demonstrating how both Database Advanced Security and Information Rights Management combined can provide a very secure platform for protecting your information. Have a look at the following which highlights these database security options.Transparent Data Encryption protecting the communication from the Oracle IRM server to the Database server. Encryption techniques provide confidentiality and integrity of the data passing to and from the IRM service on the back end. Transparent Data Encryption protecting the Oracle IRM database schema. Encryption is used to provide confidentiality of the IRM data whilst it resides at rest in the database table space. Database Vault is used to ensure only the Oracle IRM service has access to query and update the information that resides in the database. This is an excellent method of ensuring that database administrators cannot look at or make changes to the Oracle IRM database whilst retaining their ability to administrate the database. The last thing you want after deploying an IRM solution is for a curious or unhappy DBA to run a query that grants them rights to your company financial data or documents pertaining to a merger or acquisition.

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  • Join our webcast: Discover What’s New in Oracle Data Integrator and Oracle GoldenGate

    - by Irem Radzik
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman";} Data integration team has organized a series of webcasts for this summer. We are kicking it off this Thursday June 30th at 10am PT with a product update webcast: Discover What’s New in Oracle Data Integrator and Oracle GoldenGate. In this webcast you will hear from product management about the new patch updates to both GoldenGate 11g R1 and ODI 11gR1. Jeff Pollock, Sr. Director of Product Management for ODI will talk about the new features in Oracle Data Integrator 11.1.1.5, including the data lineage integration with OBI EE, enhanced web services to support flexible architectures as well as capabilities for efficient object execution such as Load Plans. Jeff will discuss support for complex files and performance enhancements. Chris McAllister, Sr. Director of Product Management for Oracle GoldenGate will cover the new features of Oracle GoldenGate 11.1.1.1 such as increased data security by supporting Oracle Database Advanced Security option, deeper integration with Oracle Database, and the expanded list of heterogeneous databases GoldenGate supports . Chris will also talk about the new Oracle GoldenGate 11gR1 release for HP NonStop platform and will provide information on our strategic direction for product development. Join us this Thursday at 10am PT/ 1pm ET to hear directly from Data Integration Product Management . You can register here for the June 30th webcast as well as for the upcoming ones in our summer webcast series.

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  • SQL SERVER – Concurrency Basics – Guest Post by Vinod Kumar

    - by pinaldave
    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 from 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. Learning is always fun when it comes to SQL Server and learning the basics again can be more fun. I did write about Transaction Logs and recovery over my blogs and the concept of simplifying the basics is a challenge. In the real world we always see checks and queues for a process – say railway reservation, banks, customer supports etc there is a process of line and queue to facilitate everyone. Shorter the queue higher is the efficiency of system (a.k.a higher is the concurrency). Every database does implement this using checks like locking, blocking mechanisms and they implement the standards in a way to facilitate higher concurrency. In this post, let us talk about the topic of Concurrency and what are the various aspects that one needs to know about concurrency inside SQL Server. Let us learn the concepts as one-liners: Concurrency can be defined as the ability of multiple processes to access or change shared data at the same time. The greater the number of concurrent user processes that can be active without interfering with each other, the greater the concurrency of the database system. Concurrency is reduced when a process that is changing data prevents other processes from reading that data or when a process that is reading data prevents other processes from changing that data. Concurrency is also affected when multiple processes are attempting to change the same data simultaneously. Two approaches to managing concurrent data access: Optimistic Concurrency Model Pessimistic Concurrency Model Concurrency Models Pessimistic Concurrency Default behavior: acquire locks to block access to data that another process is using. Assumes that enough data modification operations are in the system that any given read operation is likely affected by a data modification made by another user (assumes conflicts will occur). Avoids conflicts by acquiring a lock on data being read so no other processes can modify that data. Also acquires locks on data being modified so no other processes can access the data for either reading or modifying. Readers block writer, writers block readers and writers. Optimistic Concurrency Assumes that there are sufficiently few conflicting data modification operations in the system that any single transaction is unlikely to modify data that another transaction is modifying. Default behavior of optimistic concurrency is to use row versioning to allow data readers to see the state of the data before the modification occurs. Older versions of the data are saved so a process reading data can see the data as it was when the process started reading and not affected by any changes being made to that data. Processes modifying the data is unaffected by processes reading the data because the reader is accessing a saved version of the data rows. Readers do not block writers and writers do not block readers, but, writers can and will block writers. Transaction Processing A transaction is the basic unit of work in SQL Server. Transaction consists of SQL commands that read and update the database but the update is not considered final until a COMMIT command is issued (at least for an explicit transaction: marked with a BEGIN TRAN and the end is marked by a COMMIT TRAN or ROLLBACK TRAN). Transactions must exhibit all the ACID properties of a transaction. ACID Properties Transaction processing must guarantee the consistency and recoverability of SQL Server databases. Ensures all transactions are performed as a single unit of work regardless of hardware or system failure. A – Atomicity C – Consistency I – Isolation D- Durability Atomicity: Each transaction is treated as all or nothing – it either commits or aborts. Consistency: ensures that a transaction won’t allow the system to arrive at an incorrect logical state – the data must always be logically correct.  Consistency is honored even in the event of a system failure. Isolation: separates concurrent transactions from the updates of other incomplete transactions. SQL Server accomplishes isolation among transactions by locking data or creating row versions. Durability: After a transaction commits, the durability property ensures that the effects of the transaction persist even if a system failure occurs. If a system failure occurs while a transaction is in progress, the transaction is completely undone, leaving no partial effects on data. Transaction Dependencies In addition to supporting all four ACID properties, a transaction might exhibit few other behaviors (known as dependency problems or consistency problems). Lost Updates: Occur when two processes read the same data and both manipulate the data, changing its value and then both try to update the original data to the new value. The second process might overwrite the first update completely. Dirty Reads: Occurs when a process reads uncommitted data. If one process has changed data but not yet committed the change, another process reading the data will read it in an inconsistent state. Non-repeatable Reads: A read is non-repeatable if a process might get different values when reading the same data in two reads within the same transaction. This can happen when another process changes the data in between the reads that the first process is doing. Phantoms: Occurs when membership in a set changes. It occurs if two SELECT operations using the same predicate in the same transaction return a different number of rows. Isolation Levels SQL Server supports 5 isolation levels that control the behavior of read operations. Read Uncommitted All behaviors except for lost updates are possible. Implemented by allowing the read operations to not take any locks, and because of this, it won’t be blocked by conflicting locks acquired by other processes. The process can read data that another process has modified but not yet committed. When using the read uncommitted isolation level and scanning an entire table, SQL Server can decide to do an allocation order scan (in page-number order) instead of a logical order scan (following page pointers). If another process doing concurrent operations changes data and move rows to a new location in the table, the allocation order scan can end up reading the same row twice. Also can happen if you have read a row before it is updated and then an update moves the row to a higher page number than your scan encounters later. Performing an allocation order scan under Read Uncommitted can cause you to miss a row completely – can happen when a row on a high page number that hasn’t been read yet is updated and moved to a lower page number that has already been read. Read Committed Two varieties of read committed isolation: optimistic and pessimistic (default). Ensures that a read never reads data that another application hasn’t committed. If another transaction is updating data and has exclusive locks on data, your transaction will have to wait for the locks to be released. Your transaction must put share locks on data that are visited, which means that data might be unavailable for others to use. A share lock doesn’t prevent others from reading but prevents them from updating. Read committed (snapshot) ensures that an operation never reads uncommitted data, but not by forcing other processes to wait. SQL Server generates a version of the changed row with its previous committed values. Data being changed is still locked but other processes can see the previous versions of the data as it was before the update operation began. Repeatable Read This is a Pessimistic isolation level. Ensures that if a transaction revisits data or a query is reissued the data doesn’t change. That is, issuing the same query twice within a transaction cannot pickup any changes to data values made by another user’s transaction because no changes can be made by other transactions. However, this does allow phantom rows to appear. Preventing non-repeatable read is a desirable safeguard but cost is that all shared locks in a transaction must be held until the completion of the transaction. Snapshot Snapshot Isolation (SI) is an optimistic isolation level. Allows for processes to read older versions of committed data if the current version is locked. Difference between snapshot and read committed has to do with how old the older versions have to be. It’s possible to have two transactions executing simultaneously that give us a result that is not possible in any serial execution. Serializable This is the strongest of the pessimistic isolation level. Adds to repeatable read isolation level by ensuring that if a query is reissued rows were not added in the interim, i.e, phantoms do not appear. Preventing phantoms is another desirable safeguard, but cost of this extra safeguard is similar to that of repeatable read – all shared locks in a transaction must be held until the transaction completes. In addition serializable isolation level requires that you lock data that has been read but also data that doesn’t exist. Ex: if a SELECT returned no rows, you want it to return no. rows when the query is reissued. This is implemented in SQL Server by a special kind of lock called the key-range lock. Key-range locks require that there be an index on the column that defines the range of values. If there is no index on the column, serializable isolation requires a table lock. Gets its name from the fact that running multiple serializable transactions at the same time is equivalent of running them one at a time. Now that we understand the basics of what concurrency is, the subsequent blog posts will try to bring out the basics around locking, blocking, deadlocks because they are the fundamental blocks that make concurrency possible. Now if you are with me – let us continue learning for SQL Server Locking Basics. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Concurrency

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  • Announcing Sesame Data Browser

    - by Fabrice Marguerie
    At the occasion of MIX10, which is currently taking place in Las Vegas, I'd like to announce Sesame Data Browser.Sesame will be a suite of tools for dealing with data, and Sesame Data Browser will be the first tool from that suite.Today, during the second MIX10 keynote, Microsoft demonstrated how they are pushing hard to get OData adopted. If you don't know about OData, you can visit the just revamped dedicated website: http://odata.org. There you'll find about the OData protocol, which allows you to publish and consume data on the web, the OData SDK (with client libraries for .NET, Java, Javascript, PHP, iPhone, and more), a list of OData producers, and a list of OData consumers.This is where Sesame Data Browser comes into play. It's one of the tools you can use today to consume OData.I'll let you have a look, but be aware that this is just a preview and many additional features are coming soon.Sesame Data Browser is part of a bigger picture than just OData that will take shape over the coming months. Sesame is a project I've been working on for many months now, so what you see now is just a start :-)I hope you'll enjoy what you see. Let me know what you think.

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  • Methodology behind fetching large XML data sets in pieces

    - by Jerry Dodge
    I am working on an HTTP Server in Delphi which simply sends back a custom XML dataset. I am not following any type of standard formatting, such as SOAP. I have the system working seamlessly, except one small flaw: When I have a very large dataset to send back to the client, it might take up to 2 minutes for all the data to be transferred. The HTTP Server I'm building is essentially an XML Data based API around a database, implementing the common business rule - therefore, the requests are specific to the data behind the system. When, for example, I fetch a large set of product data, I would like to break this down and send it back piece by piece. However, a single HTTP request calls for a single response. I can't necessarily keep feeding the client with multiple different XML packets unless the client explicitly requests it. I don't have any session management, but rather an API Key. I know if I had sessions, I could keep-alive a dataset temporarily for a client, and they could request bits and pieces of it. However, without session management, I would have to execute the SQL query multiple times (for each chunk of data), and in the mean-time, if that data changes, the "pages" might get messed up, therefore causing items to show on the wrong pages, after navigating to a different page. So how is this commonly handled? What's the methodology behind breaking down a large XML dataset into chunks to save the load?

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  • Using Microsoft's Chart Controls In An ASP.NET Application: Serializing Chart Data

    In most usage scenarios, the data displayed in a Microsoft Chart control comes from some dynamic source, such as from a database query. The appearance of the chart can be modified dynamically, as well; past installments in this article series showed how to programmatically customize the axes, labels, and other appearance-related settings. However, it is possible to statically define the chart's data and appearance strictly through the control's declarative markup. One of the demos examined in the Getting Started article rendered a column chart with seven columns whose labels and values were defined statically in the <asp:Series> tag's <Points> collection. Given this functionality, it should come as no surprise that the Microsoft Chart Controls also support serialization. Serialization is the process of persisting the state of a control or an object to some other medium, such as to disk. Deserialization is the inverse process, and involves taking the persisted data and recreating the control or object. With just a few lines of code you can persist the appearance settings, the data, or both to a file on disk or to any stream. Likewise, it takes just a few lines of codes to reconstitute a chart from the persisted information. This article shows how to use the Microsoft Chart Control's serialization functionality by examining a demo application that allows users to create custom charts, specifying the data to plot and some appearance-related settings. The user can then save a "snapshot" of this chart, which persists its appearance and data to a record in a database. From another page, users can view these saved chart snapshots. Read on to learn more! Read More >

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  • “Big Data” Is A Small Concept Unless You Can Apply It To The Customer Experience

    - by Michael Hylton
    There’s been a lot of recent talk in the industry about “big data”.  Much can be said about the importance of big data and the results from it, but you need to always consider the customer experience when analyzing and applying customer data. Personalization and merchandising drive the user experience.  Big data should enable you to gain valuable insight into each of your customers and apply that insight at the moment they are on your Web site, talking to one of your call center agents, or any other touchpoint.  While past customer experience is important, you need to combine that with what your customer is doing on your Web site now as well what they are doing and saying on social networking sites.  It’s key to have a 360 degree view of your customer across all of your touchpoints in order to provide that relevant and consistent experience that they come to expect when interacting with your brand. Big data can enable you to effectively market, merchandize, and recommend the right products to the right customers and the right time.  By taking customer data and applying it to product recommendations, you have an opportunity to gain a greater share of wallet through the cross-selling and up-selling of additional products and services.  You can also build sustaining loyalty programs to continue to engage with your customers throughout their long-term relationship with your brand.

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  • “Big Data” Is A Small Concept Unless You Can Apply It To The Customer Experience

    - by Michael Hylton
    There’s been a lot of recent talk in the industry about “big data”.  Much can be said about the importance of big data and the results from it, but you need to always consider the customer experience when analyzing and applying customer data. Personalization and merchandising drive the user experience.  Big data should enable you to gain valuable insight into each of your customers and apply that insight at the moment they are on your Web site, talking to one of your call center agents, or any other touchpoint.  While past customer experience is important, you need to combine that with what your customer is doing on your Web site now as well what they are doing and saying on social networking sites.  It’s key to have a 360 degree view of your customer across all of your touchpoints in order to provide that relevant and consistent experience that they come to expect when interacting with your brand. Big data can enable you to effectively market, merchandize, and recommend the right products to the right customers and the right time.  By taking customer data and applying it to product recommendations, you have an opportunity to gain a greater share of wallet through the cross-selling and up-selling of additional products and services.  You can also build sustaining loyalty programs to continue to engage with your customers throughout their long-term relationship with your brand.

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  • Change Data Capture

    - by Ricardo Peres
    There's an hidden gem in SQL Server 2008: Change Data Capture (CDC). Using CDC we get full audit capabilities with absolutely no implementation code: we can see all changes made to a specific table, including the old and new values! You can only use CDC in SQL Server 2008 Standard or Enterprise, Express edition is not supported. Here are the steps you need to take, just remember SQL Agent must be running: use SomeDatabase; -- first create a table CREATE TABLE Author ( ID INT NOT NULL PRIMARY KEY IDENTITY(1, 1), Name NVARCHAR(20) NOT NULL, EMail NVARCHAR(50) NOT NULL, Birthday DATE NOT NULL ) -- enable CDC at the DB level EXEC sys.sp_cdc_enable_db -- check CDC is enabled for the current DB SELECT name, is_cdc_enabled FROM sys.databases WHERE name = 'SomeDatabase' -- enable CDC for table Author, all columns exec sys.sp_cdc_enable_table @source_schema = 'dbo', @source_name = 'Author', @role_name = null -- insert values into table Author insert into Author (Name, EMail, Birthday, Username) values ('Bla', 'bla@bla', 1990-10-10, 'bla') -- check CDC data for table Author -- __$operation: 1 = DELETE, 2 = INSERT, 3 = BEFORE UPDATE 4 = AFTER UPDATE -- __$start_lsn: operation timestamp select * from cdc.dbo_author_CT -- update table Author update Author set EMail = '[email protected]' where Name = 'Bla' -- check CDC data for table Author select * from cdc.dbo_author_CT -- delete from table Author delete from Author -- check CDC data for table Author select * from cdc.dbo_author_CT -- disable CDC for table Author -- this removes all CDC data, so be carefull exec sys.sp_cdc_disable_table @source_schema = 'dbo', @source_name = 'Author', @capture_instance = 'dbo_Author' -- disable CDC for the entire DB -- this removes all CDC data, so be carefull exec sys.sp_cdc_disable_db SyntaxHighlighter.config.clipboardSwf = 'http://alexgorbatchev.com/pub/sh/2.0.320/scripts/clipboard.swf'; SyntaxHighlighter.all();

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  • Free NOSQL database for use with C# client [closed]

    - by Mitten
    I've never used NOSQL databases before, but so far it seems like the best data storage solution for my project. I am going to implement a datamining application. The data I would like to mine is thousands of documents which cannot be imported into datamining applications. To make to import easier and faster (than importing thousands of documents) I am planning to import these documents into a NOSQL database first and when import NOSQL database into datamining software. At the very least once I have all the data in NOSQL database I should be able to code simplest datamining logic myself. Am I correct that NOSQL databases allow to creates records of data, but they don't mandate all the records to adhere to the same data schema (same column names/types in a classic table oriended SQL databases)? I think for each document I would create a row/entry/object (not sure what is the correct term is in use in NOSQL world) which would be a string id, few (columns) with unstructured text data, and a dozens of columns mostly of datetime and integer types. From its name NOSQL does not support SQL query syntax, but it support locating the object(row/entry?) by its unique id. Does NOSQL support qyuering objects using property=value syntax? Unfortunately most of free NOSQL db only support Java/C++ clients, which free NOSQL db would you recommend for a C# programmer?

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  • SQL SERVER – Download PSSDIAG Data Collection Utility

    - by pinaldave
    During an early career of mine as a database consultant – when I was dealing with SQL Server 2000, I often needed to collect various data related to SQL Server. My favorite tool to collect the data is PSSDIAG tool. It is a general purpose diagnostic collection utility that Microsoft Product Support Services uses to collect various logs and data files. It collects Performance Monitor logs, SQL Profiler traces, SQL Server blocking script output, Windows Event Logs, and SQLDIAG output. The data collected can be used by SQL Nexus tool which help you troubleshoot SQL Server performance problems. PSSDIAG is a wrapper around other data collection APIs and utilities, the performance impact of running PSSDIAG is generally equal to the impact of the traces that PSSDIAG has been configured to capture. If you are using SQL Server 2000 – you need to seriously consider to upgrading it to SQL Server 2012. Here is a PSSDIAG Data Collection Utility updated in August 2012. My friend and SQL Server Expert Amit Benerjee have written an excellent article on this subject, I encourage all of you to read the same. Note: For SQL Server 2012 there is SQLDiag. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority News, T SQL, Technology

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  • Using XML as data storage

    - by Kian Mayne
    I was thinking about the XML format and the following quote: “XML is not a database. It was never meant to be a database. It is never going to be a database. Relational databases are proven technology with more than 20 years of implementation experience. They are solid, stable, useful products. They are not going away. XML is a very useful technology for moving data between different databases or between databases and other programs. However, it is not itself a database. Don't use it like one.“ -Effective XML: 50 Specific Ways to Improve Your XML by Elliotte Rusty Harold (page 230, Part 4, Item 41, 2nd paragraph) This seems to really stress that XML should not be used for data storage and should only be used for program to program interoperability. Personally, I disagree and .NET's app.config file that's used to store a program's settings is an example of data storage in an XML file. However for databases rather than configurations etc XML should not be used. To develop my point, I will use two examples: A) Data about customers with fields that are all on one level i.e. there are a number of fields all relating to one customer with no children B) Data about configuration of an application where nested fields and properties make a lot of sense So my question is, Is this still a valid statement and is it now acceptable to store data using XML? EDIT: I've sent an email to the author of that quote to ask for his input/extra context.

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  • WolframAlpha Can Now Do In-depth Analysis of Your Facebook Account

    - by Jason Fitzpatrick
    If you’re a big fan of WolframAlpha’s ability to crunch the numbers on just about anything–and we certainly are–you’ll likely be just as delighted as we were to watch it massage the data from your Facebook account. Find out your most liked, discussed, and shared posts, see your Facebook habits, and other neat trends. I unleashed it on my account this morning, not sure what to expect from the results. Within the results tabulation WolframAlpha provided me with all sorts of neat data break downs. I now know exactly how many days it is to my next birthday, the composition of my aggregate posting habits (how many posts are status updates, links, or photos), the time of day when I do the most posting (and what the composition of those posts is), and my average post length. I also know my most liked post and my most commented on post. It will even crunch the numbers on your network of friends (60.6% of my friends are married, for example). By far one of the more interesting data analysis it does on the friendship data, however, is organizing all your friends into relationship clusters so you can see who in your Facebook network is friends with other people in your Facebook network. The service from WolframAlpha is free: simply visit the WolframAlpha search portal and type in “Facebook report” to start the process. You’ll be prompted to create a WolframAlpha account if you don’t have one and to authorize the WolframAlpha Facebook app to access your data. Your Facebook data is cached to your WolframAlpha account for one hour in order to crunch the numbers and display the results. WolframAlpha HTG Explains: How Windows Uses The Task Scheduler for System Tasks HTG Explains: Why Do Hard Drives Show the Wrong Capacity in Windows? Java is Insecure and Awful, It’s Time to Disable It, and Here’s How

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  • How to Implement Complex Form Data?

    - by SoulBeaver
    I'm supposed to implement a relatively complex form that looks like follows, but has at least four more pages requiring the user to fill in all necessary information for the tracks: This data will need to be sent to the server, which is implemented using Dropwizard. I'm looking for best practices on how to upload and send such a complex form with potentially dozens of songs to the server. The simplest available solution I have seen is a simple multipart/form-data request with the following form schema (Source): Client <html> <body> <h1>File Upload with Jersey</h1> <form action="rest/file/upload" method="post" enctype="multipart/form-data"> <p> Select a file : <input type="file" name="file" size="45" /> </p> <input type="submit" value="Upload It" /> </form> </body> </html> Server @POST @Path("/upload") @Consumes(MediaType.MULTIPART_FORM_DATA) public Response uploadTrack(final FormDataMultiPart multiPart) { List<FormDataBodyPart> artists = multiPart.getFields("artist"); StringBuffer output = new StringBuffer(); for (FormDataBodyPart artist : artists) output.append(artist.getValueAs(String.class)); List<FormDataBodyPart> tracks = multiPart.getFields("track"); for (FormDataBodyPart track : tracks) writeToFile(track.getValueAs(InputStream.class), "Foo"); return Response.status(200).entity(output.toString()).build(); } Then I have also read about file uploads via Ajax or Formdata (Mozilla HttpRequest) which allows for Posts in the formats application/x-www-form-urlencoded, multipart/form-data, or text/plain. I don't know which approach, if any, is best. An ideal solution would be to utilize Jackson to convert a json string into my data objects, but I don't get the impression that this is possible with binary data.

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  • Data that has been deleted in P6, how is it updated in Analytics

    - by Jeffrey McDaniel
    In P6 Reporting Database 2.0 the ETL process looked to the refrdel table in the P6 PMDB to determine which projects were deleted. The refrdel table could not be cleared out between ETL runs or those deletes would be lost. After the ETL process is run the refrdel can be cleared out. It is important to keep any purging of the refrdel in a consistent cycle so the ETL process can pick up these deletes and process them accordingly.  In P6 Reporting Database 2.2 and higher the Extended Schema is used as the data source. In the Extended Schema, deleted data is filtered out by the views. The Extended Schema services will handle any interaction with the refrdel table, this concern with timing refrdel cleanup and ETL runs is not applicable as of this release. In the Extended Schema tables (ex. TaskX) there can still be deleted data present. The Extended Schema views join on the primary PMDB tables (ex. Task) and filter out any deleted data.  Any data that was deleted that remains in the Extended Schema tables can be cleaned out at a designated time by running the clean up procedure as documented in the P6 Extended Schema white paper. This can be run occasionally but is not necessary to run often unless large amounts of data has been deleted.

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  • Business Intelligence (BI) Defined

    CIO.com defines Business Intelligence (BI) as a generic reference to a collection of applications that are used to analyze raw organizational data. Typical BI activities include data mining, online analytical processing, querying and reporting. They further explain that the primary reason why a company would utilize BI is to make their more data accessible. The more accessible data is to the users the faster they can identify ways to reduce business cost, discover new business opportunities, and react quickly to adjust prices based on current supply and demand. One area in which a hospital system could use BI derived from a data warehouse can be seen in the Emergency Room (ER) in regards to the number of doctors and nurse they have working during a full moon for each ER location. In order determine this BI needs to determine a trend in the number of patients seen on a full moon, further more they also need to determine the optimal number of staff members working during a full moon be determining the number of employees to patients ration needed to meet standard patient times and also be the most cost effective for the hospital.  This will allow the hospital system to estimate the number of potential patients they will have on the next full moon and adjust their staff schedules accordingly to ensure that patient care is not affected in any way do the influx or lack of influx of patients during this time while also ensuring that they are only working the minimum number of employees to ensure that they still making a profit. Another area where a hospital system could use BI data regards their orders paced to drug and medical supply companies. BI could define trends in prescriptions given to patients, this information could be used for ordering new supplies and forecasting the amount of medicine each hospital needs to keep on site at a given time. For example, a hospital might want to stock up on materials need to set bones in a cast prior to the summer because their BI indicates that a majority of broken bones occur during the summer due to children being out of school and they have more free time.

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  • Globacom and mCentric Deploy BDA and NoSQL Database to analyze network traffic 40x faster

    - by Jean-Pierre Dijcks
    In a fast evolving market, speed is of the essence. mCentric and Globacom leveraged Big Data Appliance, Oracle NoSQL Database to save over 35,000 Call-Processing minutes daily and analyze network traffic 40x faster.  Here are some highlights from the profile: Why Oracle “Oracle Big Data Appliance works well for very large amounts of structured and unstructured data. It is the most agile events-storage system for our collect-it-now and analyze-it-later set of business requirements. Moreover, choosing a prebuilt solution drastically reduced implementation time. We got the big data benefits without needing to assemble and tune a custom-built system, and without the hidden costs required to maintain a large number of servers in our data center. A single support license covers both the hardware and the integrated software, and we have one central point of contact for support,” said Sanjib Roy, CTO, Globacom. Implementation Process It took only five days for Oracle partner mCentric to deploy Oracle Big Data Appliance, perform the software install and configuration, certification, and resiliency testing. The entire process—from site planning to phase-I, go-live—was executed in just over ten weeks, well ahead of the four months allocated to complete the project. Oracle partner mCentric leveraged Oracle Advanced Customer Support Services’ implementation methodology to ensure configurations are tailored for peak performance, all patches are applied, and software and communications are consistently tested using proven methodologies and best practices. Read the entire profile here.

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  • A Web Service to collect data from local servers every hour

    - by anilerduran
    I'm trying to find a way to collect data from different servers around the world. Here are the details: There is only one single PowerShell script on servers that encrypts data (simple csv file) and sends with preferred method (HTTP/HTTPS Post could be) There is no more control on that servers. Can't install any service, process etc. Just I can configure script to execute every hour. This script also will have encrypted username/password/license key for every server. Script will compress data and send to me with these information. So I need a service (I'm not sure if Web Service is the rigth solution) on the cloud that will help me to: Will get data that is sent from servers using a method. Will authenticate request to recognize sender using license key/username/password and most importantly, Will redirect/send this filecab to my SQL Server on the cloud (Azure). Also it should seperate data according to customer information in license key. So every data for every customer will be stored in dedicated DB/Tables on my SQL All the processes above should be completed automatically. No way for manual steps. Question: A Web Service (SOAP or Restful) is the rigth solution for that?

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  • Should I encrypt data in database?

    - by Tio
    I have a client, for which I'm going to do an Web application about patient care, managing patients, consults, history, calendars, everything about that basically. The problem is that this is sensitive data, patient history and such. The client insists on encrypting the data at the database level, but I think this is going to deteriorate the performance of the web app. ( But maybe I shouldn't be worried about this ) I've read the laws about data protection on health issues ( Portugal ), but isn't very specific about this ( I just questioned them about this, I'm waiting for their response ). I've read the following link, but my question is different, should I encrypt the data in the database, or not. One problem that I foresee in encrypting data, is that I'm going to need a key, this could be the user password, but we all know how user passwords are ( 12345 etc etc ), and generating a key I would have to store it somewhere, this means that the programmer, dba, whatever could have access to it, any thoughts on this? Even adding an random salt to the user password isn't going to solve the problem since I can always access it, and therefore decrypt the data.

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  • What is the best way to store a table in C++

    - by Topo
    I'm programming a decision tree in C++ using a slightly modified version of the C4.5 algorithm. Each node represents an attribute or a column of your data set and it has a children per possible value of the attribute. My problem is how to store the training data set having in mind that I have to use a subset for each node so I need a quick way to only select a subset of rows and columns. The main goal is to do it in the most memory and time efficient possible (in that order of priority). The best way I have thought of is to have an array of arrays (or std::vector), or something like that, and for each node have a list (array, vector, etc) or something with the column,line(probably a tuple) pairs that are valid for that node. I now there should be a better way to do this, any suggestions? UPDATE: What I need is something like this: In the beginning I have this data: Paris 4 5.0 True New York 7 1.3 True Tokio 2 9.1 False Paris 9 6.8 True Tokio 0 8.4 False But for the second node I just need this data: Paris 4 5.0 New York 7 1.3 Paris 9 6.8 And for the third node: Tokio 2 9.1 Tokio 0 8.4 But with a table of millions of records with up to hundreds of columns. What I have in mind is keep all the data in a matrix, and then for each node keep the info of the current columns and rows. Something like this: Paris 4 5.0 True New York 7 1.3 True Tokio 2 9.1 False Paris 9 6.8 True Tokio 0 8.4 False Node 2: columns = [0,1,2] rows = [0,1,3] Node 3: columns = [0,1,2] rows = [2,4] This way on the worst case scenario I just have to waste size_of(int) * (number_of_columns + number_of_rows) * node That is a lot less than having an independent data matrix for each node.

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  • MS Access 2003: Can data disappear from records and how do I test for this and prevent it?

    - by user328960
    Problem and about the database: Data from a record in Access 2003 database has disappeared. This database has 1 backend and 3 frontends, multiple users and is hosted on Citrix. Within this database, we have records of all clients served, ranging in the 1000s. Background info: The form for client data entry is set up with various subforms, including both a "programs enrolled" subform and a "services" subform. A client can be enrolled in multiple programs. Once enrolled in a program, services can be entered for that program area using the services subform. There are multiple fields in the services subform, one of which is a drop-down field allowing you to choose from the programs a client has been enrolled in (the list is updated for that client whenever he is enrolled in a new program). The problem details: For one specific record and one specific program area, the program has disappeared from the "programs enrolled" subform and all of the related services have disappeared from the "services" subform for a period of 3 months of data entry. However, other programs and services for this record did not disappear. Questions: Is the disappearance of data a common Access 2003 problem? Are there tests in place that can be run to see if data is disappearing and catch that data? If so, what are they? If there is specific code involved, what is it? What can be done to prevent the disappearing of data (other than using a different database)?

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  • Change Data Capture or Change Tracking - Same as Traditional Audit Trail Table?

    - by HardCode
    Before I delve into the abyss of Microsoft documentation any deeper, I'd like to know if someone experienced with Change Data Capture and Change Tracking know if one or both of these can be used to replace the traditional ... "Audit trail table copy of the 'real table' (all of the fields of the original table, plus date/time, user ID, and DML action field) inserted into by Triggers" ... setup for a database table audit trail, where the trigger populates the audit trail table (which is all manual work). The MSDN overview documentation explains at a high level what Change Data Capture and Change Tracking are, but it isn't clear enough to me, and doesn't state outright, that these tools can be used to replace the traditional audit trail tables we've made so often. Can someone with any experience using Change Data Capture and Change Tracking save me a lot of time, or confirm that I am spending time looking at the right tool? The critical part of our audit trail is capturing all changes to a table's fields (on INSERT, UPDATE, DELETE), when it happened, and who did it. These changes are commonly provided to an end user chronologically via an audit trail report. Which is another question ... Change Data Capture or Change Tracking is the solution, I'd assume that this data can be queried just like data from a normal table? EDIT: I need a permanent audit trail, irregardless of time. I see that Change Data Capture has to do with the transaction logs, so this sounds finite to me.

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  • Interesting Scala typing solution, doesn't work in 2.7.7?

    - by djc
    I'm trying to build some image algebra code that can work with images (basically a linear pixel buffer + dimensions) that have different types for the pixel. To get this to work, I've defined a parametrized Pixel trait with a few methods that should be able to get used with any Pixel subclass. (For now, I'm only interested in operations that work on the same Pixel type.) Here it is: trait Pixel[T <: Pixel[T]] { def mul(v: Double): T def max(v: T): T def div(v: Double): T def div(v: T): T } Now I define a single Pixel type that has storage based on three doubles (basically RGB 0.0-1.0), I've called it TripleDoublePixel: class TripleDoublePixel(v: Array[Double]) extends Pixel[TripleDoublePixel] { var data: Array[Double] = v def this() = this(Array(0.0, 0.0, 0.0)) def toString(): String = { "(" + data(0) + ", " + data(1) + ", " + data(2) + ")" } def increment(v: TripleDoublePixel) { data(0) += v.data(0) data(1) += v.data(1) data(2) += v.data(2) } def mul(v: Double): TripleDoublePixel = { new TripleDoublePixel(data.map(x => x * v)) } def div(v: Double): TripleDoublePixel = { new TripleDoublePixel(data.map(x => x / v)) } def div(v: TripleDoublePixel): TripleDoublePixel = { var tmp = new Array[Double](3) tmp(0) = data(0) / v.data(0) tmp(1) = data(1) / v.data(1) tmp(2) = data(2) / v.data(2) new TripleDoublePixel(tmp) } def max(v: TripleDoublePixel): TripleDoublePixel = { val lv = data(0) * data(0) + data(1) * data(1) + data(2) * data(2) val vv = v.data(0) * v.data(0) + v.data(1) * v.data(1) + v.data(2) * v.data(2) if (lv > vv) (this) else v } } Now I want to write code to use this, that doesn't have to know what type the pixels are. For example: def idiv[T](a: Image[T], b: Image[T]) { for (i <- 0 until a.data.size) { a.data(i) = a.data(i).div(b.data(i)) } } Unfortunately, this doesn't compile: (fragment of lindet-gen.scala):145: error: value div is not a member of T a.data(i) = a.data(i).div(b.data(i)) I was told in #scala that this worked for someone else, but that was on 2.8. I've tried to get 2.8-rc1 going, but it doesn't compile for me. Is there any way to get this to work in 2.7.7?

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