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• difference between project management and process management

  What is the difference between project management and process management? Similar to this question: http://stackoverflow.com/questions/23509/what-is-the-difference-between-project-leader-and-project-manager

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• Big Data Appliance X4-2 Release Announcement

  - by Jean-Pierre Dijcks

  Today we are announcing the release of the 3rd generation Big Data Appliance. Read the Press Release here. Software Focus The focus for this 3rd generation of Big Data Appliance is: Comprehensive and Open - Big Data Appliance now includes all Cloudera Software, including Back-up and Disaster Recovery (BDR), Search, Impala, Navigator as well as the previously included components (like CDH, HBase and Cloudera Manager) and Oracle NoSQL Database (CE or EE). Lower TCO then DIY Hadoop Systems Simplified Operations while providing an open platform for the organization Comprehensive security including the new Audit Vault and Database Firewall software, Apache Sentry and Kerberos configured out-of-the-box Hardware Update A good place to start is to quickly review the hardware differences (no price changes!). On a per node basis the following is a comparison between old and new (X3-2) hardware: Big Data Appliance X3-2 Big Data Appliance X4-2 CPU 2 x 8-Core Intel® Xeon® E5-2660 (2.2 GHz) 2 x 8-Core Intel® Xeon® E5-2650 V2 (2.6 GHz) Memory 64GB 64GB Disk 12 x 3TB High Capacity SAS 12 x 4TB High Capacity SAS InfiniBand 40Gb/sec 40Gb/sec Ethernet 10Gb/sec 10Gb/sec For all the details on the environmentals and other useful information, review the data sheet for Big Data Appliance X4-2. The larger disks give BDA X4-2 33% more capacity over the previous generation while adding faster CPUs. Memory for BDA is expandable to 512 GB per node and can be done on a per-node basis, for example for NameNodes or for HBase region servers, or for NoSQL Database nodes. Software Details More details in terms of software and the current versions (note BDA follows a three monthly update cycle for Cloudera and other software): Big Data Appliance 2.2 Software Stack Big Data Appliance 2.3 Software Stack Linux Oracle Linux 5.8 with UEK 1 Oracle Linux 6.4 with UEK 2 JDK JDK 6 JDK 7 Cloudera CDH CDH 4.3 CDH 4.4 Cloudera Manager CM 4.6 CM 4.7 And like we said at the beginning it is important to understand that all other Cloudera components are now included in the price of Oracle Big Data Appliance. They are fully supported by Oracle and available for all BDA customers. For more information: Big Data Appliance Data Sheet Big Data Connectors Data Sheet Oracle NoSQL Database Data Sheet (CE | EE) Oracle Advanced Analytics Data Sheet

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• Review: Data Modeling 101

  I just recently read “Data Modeling 101”by Scott W. Ambler where he gave an overview of fundamental data modeling skills. I think this article was excellent for anyone who was just starting to learn or refresh their skills in regards to the modeling of data.  Scott defines data modeling as the act of exploring data oriented structures.  He goes on to explain about how data models are actually used by defining three different types of models. Types of Data Models Conceptual Data Model  Logical Data Model (LDMs) Physical Data Model(PDMs) He further expands on modeling by exploring common data modeling notations because there are no industry standards for the practice of data modeling. Scott then defines how to actually model data by expanding on entities, attributes, identities, and relationships which are the basic building blocks of data models. In addition he discusses the value of normalization for redundancy and demoralization for performance. Finally, he discuss ways in which Developers and DBAs can become better data modelers through the use of practice, and seeking guidance from more experienced data modelers.

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• HTML5 data-* (custom data attribute)

  - by Renso

  Goal: Store custom data with the data attribute on any DOM element and retrieve it. Previously under HTML4 we used to use classes to store custom data, something to the affect of <input class="account void limit-5000 over-4999" /> and then have to parse the data out of the class In a book published by Peter-Paul Koch in 2007, ppk on JavaScript, he explains why and how to use custom attributes to make data more accessible to JavaScript, using name-value pairs. Accessing a custom attribute account-limit=5000 is much easier and more intuitive than trying to parse it out of a class, Plus, what if the class name for example "color-5" has a representative class definition in a CSS stylesheet that hides it away or worse some JavaScript plugin that automatically adds 5000 to it, or something crazy like that, just because it is a valid class name. As you can see there are quite a few reasons why using classes is a bad design and why it was important to define custom data attributes in HTML5. Syntax: You define the data attribute by simply prefixing any data item you want to store with any HTML element with "data-". For example to store our customers account data with a hidden input element: <input type="hidden" data-account="void" data-limit=5000 data-over=4999  /> How to access the data: account  -     element.dataset.account limit    -     element.dataset.limit You can also access it by using the more traditional get/setAttribute method or if using jQuery $('#element').attr('data-account','void') Browser support: All except for IE. There is an IE hack around this at http://gist.github.com/362081. Special Note: Be AWARE, do not use upper-case when defining your data elements as it is all converted to lower-case when reading it, so: data-myAccount="A1234" will not be found when you read it with: element.dataset.myAccount Use only lowercase when reading so this will work: element.dataset.myaccount

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• Master Data Management – A Foundation for Big Data Analysis

  - by Manouj Tahiliani

  While Master Data Management has crossed the proverbial chasm and is on its way to becoming mainstream, businesses are being hammered by a new megatrend called Big Data. Big Data is characterized by massive volumes, its high frequency, the variety of less structured data sources such as email, sensors, smart meters, social networks, and Weblogs, and the need to analyze vast amounts of data to determine value to improve upon management decisions. Businesses that have embraced MDM to get a single, enriched and unified view of Master data by resolving semantic discrepancies and augmenting the explicit master data information from within the enterprise with implicit data from outside the enterprise like social profiles will have a leg up in embracing Big Data solutions. This is especially true for large and medium-sized businesses in industries like Retail, Communications, Financial Services, etc that would find it very challenging to get comprehensive analytical coverage and derive long-term success without resolving the limitations of the heterogeneous topology that leads to disparate, fragmented and incomplete master data. For analytical success from Big Data or in other words ROI from Big Data Investments, businesses need to acquire, organize and analyze the deluge of data to make better decisions. There will need to be a coexistence of structured and unstructured data and to maintain a tight link between the two to extract maximum insights. MDM is the catalyst that helps maintain that tight linkage by providing an understanding about the identity, characteristics of Persons, Companies, Products, Suppliers, etc. associated with the Big Data and thereby help accelerate ROI. In my next post I will discuss about patterns for co-existing Big Data Solutions and MDM. Feel free to provide comments and thoughts on above as well as Integration or Architectural patterns.

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• How to Assure an Effective Data Model

  As a general rule in my opinion the effectiveness of a data model can be directly related to the accuracy and complexity of a project’s requirements. For example there is no need to work on very detailed data models when the details surrounding a specific data model have not been defined or even clarified. Developing data models when the clarity of project requirements is limited tends to introduce designed issues because the proper details to create an effective data model are not even known. One way to avoid this issue is to create data models that correspond to the complexity of the existing project requirements so that when requirements are updated then new data models can be created based any new discoveries regarding requirements on a fine grain level.  This allows for data models to be composed of general entities to be created initially when a project’s requirements are very vague and then the entities are refined as new and more substantial requirements are defined or redefined. This promotes communication amongst all stakeholders within a project as they go through the process of defining and finalizing project requirements.In addition, here are some general tips that can be applied to projects in regards to data modeling.Initially model all data generally and slowly reactor the data model as new requirements and business constraints are applied to a project.Ensure that data modelers have the proper tools and training they need to design a data model accurately.Create a common location for all project documents so that everyone will be able to review a project’s data models along with any other project documentation.All data models should follow a clear naming schema that tells readers the intended purpose for the data and how it is going to be applied within a project.

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• Task Management - How important it is for a entry level developer?

  - by Naveen Kumar

  I hold masters in CS & now I'm mobile apps developer (Entry Level) , I always start to plan things when starting or doing any project both at work & projects i do at Home (for passion) - as I can deliver the project on time but sometimes i m running out of time like 10 tasks a day vs my time forecast will take 2 on that day? As I'm beginner level, I want your suggestions on How important is Task Management for a person like me & for achieving my goals? My target for the next 3 year will be a Project Manager or Similiar Role - i belive which these time managing skills will be a needed quality.

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• SQL SERVER – Why Do We Need Data Quality Services – Importance and Significance of Data Quality Services (DQS)

  - by pinaldave

  Databases are awesome.  I’m sure my readers know my opinion about this – I have made SQL Server my life’s work after all!  I love technology and all things computer-related.  Of course, even with my love for technology, I have to admit that it has its limits.  For example, it takes a human brain to notice that data has been input incorrectly.  Computer “brains” might be faster than humans, but human brains are still better at pattern recognition.  For example, a human brain will notice that “300” is a ridiculous age for a human to be, but to a computer it is just a number.  A human will also notice similarities between “P. Dave” and “Pinal Dave,” but this would stump most computers. In a database, these sorts of anomalies are incredibly important.  Databases are often used by multiple people who rely on this data to be true and accurate, so data quality is key.  That is why the improved SQL Server features Master Data Management talks about Data Quality Services.  This service has the ability to recognize and flag anomalies like out of range numbers and similarities between data.  This allows a human brain with its pattern recognition abilities to double-check and ensure that P. Dave is the same as Pinal Dave. A nice feature of Data Quality Services is that once you set the rules for the program to follow, it will not only keep your data organized in the future, but go to the past and “fix up” any data that has already been entered.  It also allows you do combine data from multiple places and it will apply these rules across the board, so that you don’t have any weird issues that crop up when trying to fit a round peg into a square hole. There are two parts of Data Quality Services that help you accomplish all these neat things.  The first part is DQL Server, which you can think of as the hardware component of the system.  It is installed on the side of (it needs to install separately after SQL Server is installed) SQL Server and runs quietly in the background, performing all its cleanup services. DQS Client is the user interface that you can interact with to set the rules and check over your data.  There are three main aspects of Client: knowledge base management, data quality projects and administration.  Knowledge base management is the part of the system that allows you to set the rules, or program the “knowledge base,” so that your database is clean and consistent. Data Quality projects are what run in the background and clean up the data that is already present.  The administration allows you to check out what DQS Client is doing, change rules, and generally oversee the entire process.  The whole process is user-friendly and a pleasure to use.  I highly recommend implementing Data Quality Services in your database. Here are few of my blog posts which are related to Data Quality Services and I encourage you to try this out. SQL SERVER – Installing Data Quality Services (DQS) on SQL Server 2012 SQL SERVER – Step by Step Guide to Beginning Data Quality Services in SQL Server 2012 – Introduction to DQS SQL SERVER – DQS Error – Cannot connect to server – A .NET Framework error occurred during execution of user-defined routine or aggregate “SetDataQualitySessions” – SetDataQualitySessionPhaseTwo SQL SERVER – Configuring Interactive Cleansing Suggestion Min Score for Suggestions in Data Quality Services (DQS) – Sensitivity of Suggestion SQL SERVER – Unable to DELETE Project in Data Quality Projects (DQS) Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Data Quality Services, DQS

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• Welcome Oracle Data Integration 12c: Simplified, Future-Ready Solutions with Extreme Performance

  - by Irem Radzik

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 The big day for the Oracle Data Integration team has finally arrived! It is my honor to introduce you to Oracle Data Integration 12c. Today we announced the general availability of 12c release for Oracle’s key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions Extreme Performance Fast Time-to-Value       There are many new features that support these key differentiators for Oracle Data Integrator 12c and for Oracle GoldenGate 12c. In this first 12c blog post, I will highlight only a few:·Future-Ready Solutions to Support Current and Emerging Initiatives: Oracle Data Integration offer robust and reliable solutions for key technology trends including cloud computing, big data analytics, real-time business intelligence and continuous data availability. Via the tight integration with Oracle’s database, middleware, and application offerings Oracle Data Integration will continue to support the new features and capabilities right away as these products evolve and provide advance features. E    Extreme Performance: Both GoldenGate and Data Integrator are known for their high performance. The new release widens the gap even further against competition. Oracle GoldenGate 12c’s Integrated Delivery feature enables higher throughput via a special application programming interface into Oracle Database. As mentioned in the press release, customers already report up to 5X higher performance compared to earlier versions of GoldenGate. Oracle Data Integrator 12c introduces parallelism that significantly increases its performance as well. Fast Time-to-Value via Higher IT Productivity and Simplified Solutions:  Oracle Data Integrator 12c’s new flow-based declarative UI brings superior developer productivity, ease of use, and ultimately fast time to market for end users.  It also gives the ability to seamlessly reuse mapping logic speeds development.Oracle GoldenGate 12c ‘s Integrated Delivery feature automatically optimally tunes the process, saving time while improving performance. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. On November 12th we will reveal much more about the new release in our video webcast "Introducing 12c for Oracle Data Integration". Our customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Please join us at this free event to learn more from our executives about the 12c release, hear our customers’ perspectives on the new features, and ask your questions to our experts in the live Q&A. Also, please continue to follow our blogs, tweets, and Facebook updates as we unveil more about the new features of the latest release. /* 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-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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• Five Key Trends in Enterprise 2.0 for 2011

  - by kellsey.ruppel(at)oracle.com

  We recently sat down with Andy MacMillan, an industry veteran and vice president of product management for Enterprise 2.0 at Oracle, to get his take on the year ahead in Enterprise 2.0 (E2.0). He offered us his five predictions about the ways he believes E2.0 technologies will transform business in 2011. 1. Forward-thinking organizations will achieve an unprecedented level of organizational awareness. Enterprise 2.0 and Web 2.0 technologies have already transformed the ways customers, employees, partners, and suppliers communicate and stay informed. But this year we are anticipating that organizations will go to the next step and integrate social activities with business applications to deliver rich contextual "activity streams." Activity streams are a new way for enterprise users to get relevant information as quickly as it happens, by navigating to that information in context directly from their portal. We don't mean syndicating social activities limited to a single application. Instead, we believe back-office systems will be combined with social media tools to drive how users make informed business decisions in brand new ways. For example, an account manager might log into the company portal and automatically receive notification that colleagues are closing business around a certain product in his market segment. With a single click, he can reach out instantly to these colleagues via social media and learn from their successes to drive new business opportunities in his own area. 2. Online customer engagement will become a high priority for CMOs. A growing number of chief marketing officers (CMOs) have created a new direct report called "head of online"--a senior marketing executive responsible for all engagements with customers and prospects via the Web, mobile, and social media. This new field has been dubbed "Web experience management" or "online customer engagement" by firms and analyst organizations. It is likely to rapidly increase demand for a host of new business objectives and metrics from Web content management solutions. As companies interface with customers more and more over the Web, Web experience management solutions will help deliver more targeted interactions to ensure increased customer loyalty while meeting sales and business objectives. 3. Real composite applications will be widely adopted. We expect organizations to move from the concept of a single "uber-portal" that encompasses all the necessary features to a more modular, component-based concept for composite applications. This approach is now possible as IT and power users are empowered to assemble new, purpose-built composite applications quickly from existing components. 4. Records management will drive ECM consolidation. We continue to see a significant shift in the approach to records management. Several years ago initiatives were focused on overlaying records management across a set of electronic repositories and physical storage locations. We believe federated records management will continue, but we also expect to see records management driving conversations around single-platform content management consolidation. 5. Organizations will demand ECM at extreme scale. We have already seen a trend within IT organizations to provide a common, highly scalable infrastructure to consolidate and support content and information needs. But as data sizes grow exponentially, ECM at an extreme scale is likely to spread at unprecedented speeds this year. This makes sense as regulations and transparency requirements rise. The model in which ECM and lightweight CMS systems provide basic content services such as check-in, update, delete, and search has converged around a set of industry best practices and has even been coded into new industry standards such as content management interoperability services. As these services converge and the demand for them accelerates, organizations are beginning to rationalize investments into a single, highly scalable infrastructure. Is your organization ready for Enterprise 2.0 in 2011? Learn more.

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• Five Key Strategies in Master Data Management

  - by david.butler(at)oracle.com

  Here is a very interesting Profit Magazine article on MDM: A recent customer survey reveals the deleterious effects of data fragmentation. by Trevor Naidoo, December 2010   Across industries and geographies, IT organizations have grown in complexity, whether due to mergers and acquisitions, or decentralized systems supporting functional or departmental requirements. With systems architected over time to support unique, one-off process needs, they are becoming costly to maintain, and the Internet has only further added to the complexity. Data fragmentation has become a key inhibitor in delivering flexible, user-friendly systems. The Oracle Insight team conducted a survey assessing customers' master data management (MDM) capabilities over the past two years to get a sense of where they are in terms of their capabilities. The responses, by 27 respondents from six different industries, reveal five key areas in which customers need to improve their data management in order to get better financial results. 1. Less than 15 percent of organizations surveyed understand the sources and quality of their master data, and have a roadmap to address missing data domains. Examples of the types of master data domains referred to are customer, supplier, product, financial and site. Many organizations have multiple sources of master data with varying degrees of data quality in each source -- customer data stored in the customer relationship management system is inconsistent with customer data stored in the order management system. Imagine not knowing how many places you stored your customer information, and whether a customer's address was the most up to date in each source. In fact, more than 55 percent of the respondents in the survey manage their data quality on an ad-hoc basis. It is important for organizations to document their inventory of data sources and then profile these data sources to ensure that there is a consistent definition of key data entities throughout the organization. Some questions to ask are: How do we define a customer? What is a product? How do we define a site? The goal is to strive for one common repository for master data that acts as a cross reference for all other sources and ensures consistent, high-quality master data throughout the organization. 2. Only 18 percent of respondents have an enterprise data management strategy to ensure that data is treated as an asset to the organization. Most respondents handle data at the department or functional level and do not have an enterprise view of their master data. The sales department may track all their interactions with customers as they move through the sales cycle, the service department is tracking their interactions with the same customers independently, and the finance department also has a different perspective on the same customer. The salesperson may not be aware that the customer she is trying to sell to is experiencing issues with existing products purchased, or that the customer is behind on previous invoices. The lack of a data strategy makes it difficult for business users to turn data into information via reports. Without the key building blocks in place, it is difficult to create key linkages between customer, product, site, supplier and financial data. These linkages make it possible to understand patterns. A well-defined data management strategy is aligned to the business strategy and helps create the governance needed to ensure that data stewardship is in place and data integrity is intact. 3. Almost 60 percent of respondents have no strategy to integrate data across operational applications. Many respondents have several disparate sources of data with no strategy to keep them in sync with each other. Even though there is no clear strategy to integrate the data (see #2 above), the data needs to be synced and cross-referenced to keep the business processes running. About 55 percent of respondents said they perform this integration on an ad hoc basis, and in many cases, it is done manually with the help of Microsoft Excel spreadsheets. For example, a salesperson needs a report on global sales for a specific product, but the product has different product numbers in different countries. Typically, an analyst will pull all the data into Excel, manually create a cross reference for that product, and then aggregate the sales. The exact same procedure has to be followed if the same report is needed the following month. A well-defined consolidation strategy will ensure that a central cross-reference is maintained with updates in any one application being propagated to all the other systems, so that data is synchronized and up to date. This can be done in real time or in batch mode using integration technology. 4. Approximately 50 percent of respondents spend manual efforts cleansing and normalizing data. Information stored in various systems usually follows different standards and formats, making it difficult to match the data. A customer's address can be stored in different ways using a variety of abbreviations -- for example, "av" or "ave" for avenue. Similarly, a product's attributes can be stored in a number of different ways; for example, a size attribute can be stored in inches and can also be entered as "'' ". These types of variations make it difficult to match up data from different sources. Today, most customers rely on manual, heroic efforts to match, cleanse, and de-duplicate data -- clearly not a scalable, sustainable model. To solve this challenge, organizations need the ability to standardize data for customers, products, sites, suppliers and financial accounts; however, less than 10 percent of respondents have technology in place to automatically resolve duplicates. It is no wonder, therefore, that we get communications about products we don't own, at addresses we don't reside, and using channels (like direct mail) we don't like. An all-too-common example of a potential challenge follows: Customers end up receiving duplicate communications, which not only impacts customer satisfaction, but also incurs additional mailing costs. Cleansing, normalizing, and standardizing data will help address most of these issues. 5. Only 10 percent of respondents have the ability to share data that was mastered in a master data hub. Close to 60 percent of respondents have efforts in place that profile, standardize and cleanse data manually, and the output of these efforts are stored in spreadsheets in various parts of the organization. This valuable information is not easily shared with the rest of the organization and, more importantly, this enriched information cannot be sent back to the source systems so that the data is fixed at the source. A key benefit of a master data management strategy is not only to clean the data, but to also share the data back to the source systems as well as other systems that need the information. Aside from the source systems, another key beneficiary of this data is the business intelligence system. Having clean master data as input to business intelligence systems provides more accurate and enhanced reporting.  Characteristics of Stellar MDM When deciding on the right master data management technology, organizations should look for solutions that have four main characteristics: enterprise-grade MDM performance complete technology that can be rapidly deployed and addresses multiple business issues end-to-end MDM process management with data quality monitoring and assurance pre-built MDM business relevant applications with data stores and workflows These master data management capabilities will aid in moving closer to a best-practice maturity level, delivering tremendous efficiencies and savings as well as revenue growth opportunities as a result of better understanding your customers.  Trevor Naidoo is a senior director in Industry Strategy and Insight at Oracle. 

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• SQL SERVER – Identifying guest User using Policy Based Management

  - by pinaldave

  If you are following my recent blog posts, you may have noticed that I’ve been writing a lot about Guest User in SQL Server. Here are all the blog posts which I have written on this subject: SQL SERVER – Disable Guest Account – Serious Security Issue SQL SERVER – Force Removing User from Database – Fix: Error: Could not drop login ‘test’ as the user is currently logged in SQL SERVER – Detecting guest User Permissions – guest User Access Status SQL SERVER – guest User and MSDB Database – Enable guest User on MSDB Database One of the requests I received was whether we could create a policy that would prevent users unable guest user in user databases. Well, here is a quick tutorial to answer this. Let us see how quickly we can do it. Requirements Check if the guest user is disabled in all the user-created databases. Exclude master, tempdb and msdb database for guest user validation. We will create the following conditions based on the above two requirements: If the name of the user is ‘guest’ If the user has connect (@hasDBAccess) permission in the database Check in All user databases, except: master, tempDB and msdb Once we create two conditions, we will create a policy which will validate the conditions. Condition 1: Is the User Guest? Expand the Database >> Management >> Policy Management >> Conditions Right click on the Conditions, and click on “New Condition…”. First we will create a condition where we will validate if the user name is ‘guest’, and if it’s so, then we will further validate if it has DB access. Check the image for the necessary configuration for condition: Facet: User Expression: @Name = ‘guest’ Condition 2: Does the User have DBAccess? Expand the Database >> Management >> Policy Management >> Conditions Right click on Conditions and click on “New Condition…”. Now we will validate if the user has DB access. Check the image for necessary configuration for condition: Facet: User Expression: @hasDBAccess = False Condition 3: Exclude Databases Expand the Database >> Management >> Policy Management >> Conditions Write click on Conditions and click on “New Condition…” Now we will create condition where we will validate if database name is master, tempdb or msdb and if database name is any of them, we will not validate our first one condition with them. Check the image for necessary configuration for condition: Facet: Database Expression: @Name != ‘msdb’ AND @Name != ‘tempdb’ AND @Name != ‘master’ The next step will be creating a policy which will enforce these conditions. Creating a Policy Right click on Policies and click “New Policy…” Here, we justify what condition we want to validate against what the target is. Condition: Has User DBAccess Target Database: Every Database except (master, tempdb and MSDB) Target User: Every User in Target Database with name ‘guest’ Now we have options for two evaluation modes: 1) On Demand and 2) On Schedule We will select On Demand in this example; however, you can change the mode to On Schedule through the drop down menu, and select the interval of the evaluation of the policy. Evaluate the Policies We have selected OnDemand as our policy evaluation mode. We will now evaluate by means of executing Evaluate policy. Click on Evaluate and it will give the following result: The result demonstrates that one of the databases has a policy violation. Username guest is enabled in AdventureWorks database. You can disable the guest user by running the following code in AdventureWorks database. USE AdventureWorks; REVOKE CONNECT FROM guest; Once you run above query, you can already evaluate the policy again. Notice that the policy violation is fixed now. You can change the method of the evaluation policy to On Schedule and validate policy on interval. You can check the history of the policy and detect the violation. Quiz I have created three conditions to check if the guest user has database access or not. Now I want to ask you: Is it possible to do the same with 2 conditions? If yes, HOW? If no, WHY NOT? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Best Practices, CodeProject, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology Tagged: Policy Management

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• SQL SERVER – Why Do We Need Master Data Management – Importance and Significance of Master Data Management (MDM)

  - by pinaldave

  Let me paint a picture of everyday life for you.  Let’s say you and your wife both have address books for your groups of friends.  There is definitely overlap between them, so that you both have the addresses for your mutual friends, and there are addresses that only you know, and some only she knows.  They also might be organized differently.  You might list your friend under “J” for “Joe” or even under “W” for “Work,” while she might list him under “S” for “Joe Smith” or under your name because he is your friend.  If you happened to trade, neither of you would be able to find anything! This is where data management would be very important.  If you were to consolidate into one address book, you would have to set rules about how to organize the book, and both of you would have to follow them.  You would also make sure that poor Joe doesn’t get entered twice under “J” and under “S.” This might be a familiar situation to you, whether you are thinking about address books, record collections, books, or even shopping lists.  Wherever there is a lot of data to consolidate, you are going to run into problems unless everyone is following the same rules. I’m sure that my readers can figure out where I am going with this.  What is SQL Server but a computerized way to organize data?  And Microsoft is making it easier and easier to get all your “addresses” into one place.  In the  2008 version of SQL they introduced a new tool called Master Data Services (MDS) for Master Data Management, and they have improved it for the new 2012 version. MDM was hailed as a major improvement for business intelligence.  You might not think that an organizational system is terribly exciting, but think about the kind of “address books” a company might have.  Many companies have lots of important information, like addresses, credit card numbers, purchase history, and so much more.  To organize all this efficiently so that customers are well cared for and properly billed (only once, not never or multiple times!) is a major part of business intelligence. MDM comes into play because it will comb through these mountains of data and make sure that all the information is consistent, accurate, and all placed in one database so that employees don’t have to search high and low and waste their time. MDM also has operational MDM functions.  This is not a redundancy.  Operational MDM means that when one employee updates one bit of information in the database, for example – updating a new address for a customer, operational MDM ensures that this address is updated throughout the system so that all departments will have the correct information. Another cool thing about MDM is that it features Master Data Services Configuration Manager, which is exactly what it sounds like.  It has a built-in “helper” that lets you set up your database quickly, easily, and with the correct configurations.  While talking about cool features, I can’t skip over the add-in for Excel.  This allows you to link certain data to Excel files for easier sharing and uploading. In summary, I want to emphasize that the scariest part of the database is slowly disappearing.  Everyone knows that a database – one consolidated area for all your data – is a good idea, but the idea of setting one up is daunting.  But SQL Server is making data management easier and easier with features like Master Data Services (MDS). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Master Data Services, MDM

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• Big Data – Final Wrap and What Next – Day 21 of 21

  - by Pinal Dave

  In yesterday’s blog post we explored various resources related to learning Big Data and in this blog post we will wrap up this 21 day series on Big Data. I have been exploring various terms and technology related to Big Data this entire month. It was indeed fun to write about Big Data in 21 days but the subject of Big Data is much bigger and larger than someone can cover it in 21 days. My first goal was to write about the basics and I think we have got that one covered pretty well. During this 21 days I have received many questions and answers related to Big Data. I have covered a few of the questions in this series and a few more I will be covering in the next coming months. Now after understanding Big Data basics. I am personally going to do a list of the things next. I thought I will share the same with you as this will give you a good idea how to continue the journey of the Big Data. Build a schedule to read various Apache documentations Watch all Pluralsight Courses Explore HortonWorks Sandbox Start building presentation about Big Data – this is a great way to learn something new Present in User Groups Meetings on Big Data Topics Write more blog posts about Big Data I am going to continue learning about Big Data – I want you to continue learning Big Data. Please leave a comment how you are going to continue learning about Big Data. I will publish all the informative comments on this blog with due credit. I want to end this series with the infographic by UMUC. 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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• Partner Webcast - Focus on Oracle Data Profiling and Data Quality 11g

  - by lukasz.romaszewski(at)oracle.com

  Normal 0 false false false EN-US X-NONE X-NONE /* 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:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-ansi-language:RO;} Partner Webcast Focus on Oracle Data Profiling and Data Quality 11g February 24th, 12am  CET   Oracle offers an integrated suite Data Quality software architected to discover and correct today's data quality problems and establish a platform prepared for tomorrow's yet unknown data challenges. Oracle Data Profiling provides data investigation, discovery, and profiling in support of quality, migration, integration, stewardship, and governance initiatives. It includes a broad range of features that expand upon basic profiling, including automated monitoring, business-rule validation, and trend analysis. Oracle Data Quality for Data Integrator provides cleansing, standardization, matching, address validation, location enrichment, and linking functions for global customer data and operational business data. It ensures that data adheres to established standards that are adaptable to fit each organization's specific needs.  Both single - and double - byte data are processed in local languages to provide a unique and centralized view of customers, products and services.   During this in-person briefing, Data Integration Solution Specialists will be providing a technical overview and a walkthrough.   Agenda ·         Oracle Data Integration Strategy overview ·         A focus on Oracle Data Profiling and Oracle Data Quality for Data Integrator: o   Oracle Data Profiling o   Oracle Data Quality for Data Integrator o   Live demoo   Q&A Delivery Format  This FREE online LIVE eSeminar will be delivered over the Web and Conference Call. Registrations   received less than 24hours  prior to start time may not receive confirmation to attend. To register , click here. For any questions please contact [email protected]. 

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• SQL SERVER – Color Coding SQL Server Management Studio Status Bar – SQL in Sixty Seconds #023 – Video

  - by pinaldave

  I often see developers executing the unplanned code on production server when they actually want to execute on the development server. Developers and DBAs get confused because when they use SQL Server Management Studio (SSMS) they forget to pay attention to the server they are connecting. It is very easy to fix this problem. You can select different color for a different server. Once you have different color for different server in the status bar, it will be easier for developer easily notice the server against which they are about to execute the script. Personally when I work on SQL Server development, here is the color code, which I follow. I keep Green for my development server, blue for my staging server and red for my production server. Honestly color coding does not signify much but different color for different server is the key here. More Tips on SSMS in SQL in Sixty Seconds: Generate Script for Schema and Data in SQL Server – SQL in Sixty Seconds #021  Remove Debug Button in SQL Server Management Studio – SQL in Sixty Seconds #020  Three Tricks to Comment T-SQL in SQL Server Management Studio – SQL in Sixty Seconds #019  Importing CSV into SQL Server – SQL in Sixty Seconds #018   Tricks to Replace SELECT * with Column Names – SQL in Sixty Seconds #017 I encourage you to submit your ideas for SQL in Sixty Seconds. We will try to accommodate as many as we can. If we like your idea we promise to share with you educational material. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video

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• Distributed Development Tools -- (Version control and Project Management)

  - by Macy Abbey

  Hello, I've recently become responsible for choosing which source control and project management software to use for a company that employs me. Currently it uses Jira (project management) and Subversion (version control). I know there are many other options out there -- the ones I know about are all in this article http://mashable.com/2010/07/14/distributed-developer-teams/ . I'm leaning towards recommending they just stay with what they have as it seems workable and any change would have to be worth the cost of switching to say github/basecamp or some other solution. Some details on the team: It's a distributed development shop. Meetings of the whole team in one room are rare. It's currently a very small development team (three developers). The project management software is used by developers and a product manager or two. What are you experiences with version control and project management web applications? Are there any you would recommend and you think are worth the switching cost of time to learn new services / implementing the change? Edit: After educating myself further on the options it appears DVCS offer powerful benefits that may be worth investing in now as opposed to later in the company's lifetime when the switching cost is higher: I'm a Subversion geek, why I should consider or not consider Mercurial or Git or any other DVCS?

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• Does a mature agile team requires any management?

  - by ashy_32bit

  After a recent heated debate over Scrum, I realized my problem is that I think of management as a quite unnecessary and redundant activity in a fully agile team. I believe a mature Agile team does not require management or any non-technical decision making process whatsoever. To my (apparently erring) eyes it is more than obvious that the only one suitable and capable of managing a mature development team is their coach (who is the most technically competent colleague with proper communication skills). I can't imagine how a Scrum master can contribute to such a team. I am having great difficulty realizing and understanding the value of such things in Scrum and the manager as someone who is not a veteran developer but is well skilled in planning the production cycles when a coach exists in the team. What does that even mean? How on earth can someone with no edge-skills of development manage a highly technical team? Perhaps management here means something else? I see management as a total waste of time and a by-product of immaturity. In my understanding a mature team is fully self-managing. Apparently I'm mistaken since many great people say the contrary but I can't convince myself.

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• Using Computer Management (MMC) with the Solaris CIFS Service (August 25, 2009)

  - by user12612012

  One of our goals for the Solaris CIFS Service is to provide seamless Windows interoperability: not just to deliver ubiquitous, multi-protocol file sharing, which is obviously a major part of this project, but to support Windows services at a fundamental level.  It's an ongoing mission and our latest update includes support for Windows remote management. Remote management is extremely important to Windows administrators and one of the mainstay tools is Computer Management. Computer Management is a Windows administration application, actually a collection of Microsoft Management Console (MMC) tools, that can be used to configure, monitor and manage local and remote services and resources.  The MMC is an extensible framework of registered components, known as snap-ins, which allows Computer Management to provide comprehensive management features for both the local system and remote systems on the network. Supported Computer Management features include: Share ManagementSupport for share management is relatively complete.  You can create, delete, list and configure shares.  It's not yet possible to change the maximum allowed or number of users properties but other properties, including the Share Permissions, can be managed via the MMC. Users, Groups and ConnectionsYou can view local SMB users and groups, monitor user connections and see the list of open files. If necessary, you can also disconnect users and/or close files. ServicesYou can view the SMF services running on an OpenSolaris system.  This is a read-only view - we don't support service management (the ability to start or stop) SMF services from Computer Management (yet). To ensure that only the appropriate users have access to administrative operations there are some access restrictions on these remote management features. Regular users can: List shares Only members of the Administrators or Power Users groups can: Manage shares List connections Only members of the Administrators group can: List open files and close files Disconnect users View SMF services View the EventLog Here's a screenshot when I was using Computer Management and Server Manager (another Windows remote management application) on Windows XP to view some open files on an OpenSolaris system to prepare a slide presentation on MMC support.

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• Distributed Development Tools -- (Version control and Project Management)

  - by Macy Abbey

  I've recently become responsible for choosing which source control and project management software to use for a company that employs me. Currently it uses Jira (project management) and Subversion (version control). I know there are many other options out there -- the ones I know about are all in this article http://mashable.com/2010/07/14/distributed-developer-teams/ . I'm leaning towards recommending they just stay with what they have as it seems workable and any change would have to be worth the cost of switching to say github/basecamp or some other solution. Some details on the team: It's a distributed development shop. Meetings of the whole team in one room are rare. It's currently a very small development team (three developers). The project management software is used by developers and a product manager or two. What are you experiences with version control and project management web applications? Are there any you would recommend and you think are worth the switching cost of time to learn new services / implementing the change? Edit: After educating myself further on the options it appears DVCS offer powerful benefits that may be worth investing in now as opposed to later in the company's lifetime when the switching cost is higher: I'm a Subversion geek, why I should consider or not consider Mercurial or Git or any other DVCS?

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• Oracle Identity Management 11gR2 Live Event - New York

  - by Tanu Sood

    Are you in New York or the vicinity on September 6? If so, come join Amit Jasuja, Senior Vice President, Security and Identity Management at Oracle as he discusses the evolution of Oracle identity Management solutions and the business drivers (and industry trends) behind those. You have heard about some of the new experiences delivered with the latest release of Oracle Identity Management - simplified user experience, enhanced security and seamless enablement for secure cloud and mobile environments. Now come see it in action and hear what customers, your peers, are saying about their implementations. This forum will also be a great opportunity for you to connect directly with technology experts and network with industry professionals. There is still time left to register so book your space today. Registration details as well as the agenda for the day can be found here. We look forward to hosting you on Thursday, September 6th. Oracle Identity Management 11gR2 Live Event – New York Thursday, September 6, 2012 Oracle NYC Office 101 Park Avenue 4th Floor New York, NY 10178 Register Here Not in NY on Sep 6? Find an event near you in North America.

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• OOW - Oracle Identity Management Demos

  - by B Shashikumar

  If you are in San Francisco or in the vicinity of the city, it must be hard not to feel the OpenWorld vibe in the city. Oracle OpenWorld is now in high gear. If you haven’t already checked out the Identity Management demo grounds in Moscone South, don’t miss it. This year, the Oracle IDM product team has pulled out all stops to bring together one of the most exciting set of demos we have seen. The 9 Identity Management demos are all designed to prove why Oracle Identity Management is the most innovative and integrated solution in the world. Each demo validates several real world use case scenarios that need an end to end solution. And this year, there is an added bonus. If you check out all the 9 IDM demos, you can enter to win an Apple TV.  Just grab an entry form from here or from one of the IDM demo stations. Visit all nine IDM demos and get your form signed by the demo staff. Submit your form to be entered into a drawing for an Apple TV. Here is the complete lineup of all the Identity Management demos. Make sure you check us out.

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• Software Manager who makes developers do Project Management

  - by hdman

  I'm a software developer working in an embedded systems company. We have a Project Manager, who takes care of the overall project schedule (including electrical, quality, software and manufacturing) hence his software schedule is very brief. We also have a Software Manager, who's my boss. He makes me write and maintain the software schedule, design documents (high and low level design), SRS, change management, verification plans and reports, release management, reviews, and ofcourse the software. We only have one Test Engineer for the whole software team (10 members), and at any given time, there are a couple of projects going on. I'm spending 80% of my time making these documents. My boss comes from a Process background, and believes what we need is better documentation to improve software: (1) He considers the design to be paramount, coding is "just writing the design down", it shouldn't take too long, and "all the code should be written before the hardware is ready". (2) Doesn't understand the difference between a Central & Distributed Version control, even after we told him its easier to collaborate with a distributed model. (3) Doesn't understand code, and wants to understand every bug and its proposed solution. (4) Believes verification should be done by developer, and validation by the Tester. Thing is though, our verification only checks if implementation is correct (we don't write unit tests, its never considered in the schedule), and validation is black box testing, so the units tests are missing. I'm really confused. (1) Am I responsible for maintaining all these documents? It makes me feel like I'm doing the Software Project Management, in essence. (2) I don't really like creating documents, I want to solve problems and write code. In my experience, creating design documents only helps to an extent, its never the solution to better or faster code. (3) I feel the boss doesn't really care about making better products, but only about being a good manager in the eyes of the management. What can I do?

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• What is a Relational Database Management System (RDBMS)?

  A Relational Database Management System (RDBMS)  can also be called a traditional database that uses a Structured Query Language (SQL) to provide access to stored data while insuring the integrity of the data. The data is stored in a collection of tables that is defined by relationships between data items. In addition, data permitted to be joined in new relationships. Traditional databases primarily process data through transactions called transaction processing. Transaction processing is the methodology of grouping related business operations based predefined business events. An example of this can be seen when a person attempts to purchase an item from an online e-tailor. The business must execute specific operations for a related  business event. In this case, a business must store the following information: Customer Info, Order Info, Order Item Info, Customer Payment Data, Payment Results, and Current Order Status. Example: Pseudo SQL Operations needed for processing an online e-tailor sale. Insert Customer into Customers Insert New Order into Orders Insert Each New Order Item into OrderItems Insert Customer Payment Info into PaymentInfo Insert Payment Processing Result into PaymentDetails Update Customer for Current Order Status Common Relational Database Management System Microsoft SQL Server Microsoft Access Oracle MySQL DB2 It is important to note that no current RDBMS has fully implemented all of the Relational Principles. Common RDBMS Traits Volatile Data Supports Transaction Processing Optimized for Updates and Simple Queries 

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• Big Data – Buzz Words: What is HDFS – Day 8 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned what is MapReduce. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – HDFS. What is HDFS ? HDFS stands for Hadoop Distributed File System and it is a primary storage system used by Hadoop. It provides high performance access to data across Hadoop clusters. It is usually deployed on low-cost commodity hardware. In commodity hardware deployment server failures are very common. Due to the same reason HDFS is built to have high fault tolerance. The data transfer rate between compute nodes in HDFS is very high, which leads to reduced risk of failure. HDFS creates smaller pieces of the big data and distributes it on different nodes. It also copies each smaller piece to multiple times on different nodes. Hence when any node with the data crashes the system is automatically able to use the data from a different node and continue the process. This is the key feature of the HDFS system. Architecture of HDFS The architecture of the HDFS is master/slave architecture. An HDFS cluster always consists of single NameNode. This single NameNode is a master server and it manages the file system as well regulates access to various files. In additional to NameNode there are multiple DataNodes. There is always one DataNode for each data server. In HDFS a big file is split into one or more blocks and those blocks are stored in a set of DataNodes. The primary task of the NameNode is to open, close or rename files and directory and regulate access to the file system, whereas the primary task of the DataNode is read and write to the file systems. DataNode is also responsible for the creation, deletion or replication of the data based on the instruction from NameNode. In reality, NameNode and DataNode are software designed to run on commodity machine build in Java language. Visual Representation of HDFS Architecture Let us understand how HDFS works with the help of the diagram. Client APP or HDFS Client connects to NameSpace as well as DataNode. Client App access to the DataNode is regulated by NameSpace Node. NameSpace Node allows Client App to connect to the DataNode based by allowing the connection to the DataNode directly. A big data file is divided into multiple data blocks (let us assume that those data chunks are A,B,C and D. Client App will later on write data blocks directly to the DataNode. Client App does not have to directly write to all the node. It just has to write to any one of the node and NameNode will decide on which other DataNode it will have to replicate the data. In our example Client App directly writes to DataNode 1 and detained 3. However, data chunks are automatically replicated to other nodes. All the information like in which DataNode which data block is placed is written back to NameNode. High Availability During Disaster Now as multiple DataNode have same data blocks in the case of any DataNode which faces the disaster, the entire process will continue as other DataNode will assume the role to serve the specific data block which was on the failed node. This system provides very high tolerance to disaster and provides high availability. If you notice there is only single NameNode in our architecture. If that node fails our entire Hadoop Application will stop performing as it is a single node where we store all the metadata. As this node is very critical, it is usually replicated on another clustered as well as on another data rack. Though, that replicated node is not operational in architecture, it has all the necessary data to perform the task of the NameNode in the case of the NameNode fails. The entire Hadoop architecture is built to function smoothly even there are node failures or hardware malfunction. It is built on the simple concept that data is so big it is impossible to have come up with a single piece of the hardware which can manage it properly. We need lots of commodity (cheap) hardware to manage our big data and hardware failure is part of the commodity servers. To reduce the impact of hardware failure Hadoop architecture is built to overcome the limitation of the non-functioning hardware. Tomorrow In tomorrow’s blog post we will discuss the importance of the relational database in Big Data. 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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