30 August 2010

Business Intelligence: Scorecards (Definitions)

"Online, real time reporting to monitor performance against targets." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

"An approach to rating risk used in many areas of risk management. A scorecard is most commonly used for rating customer risk (often individuals) as the probability of default in financial risk management." (Annetta Cortez & Bob Yehling, "The Complete Idiot's Guide To Risk Management", 2010)

"An application that helps organizations measure and align the strategic and tactical aspects of their businesses, comparing organizational and individual performance to goals and targets. (Laura Reeves, A Manager's Guide to Data Warehousing, 2009) 

"A collection of information - organized in a single view - that tracks an organization's progress toward a specific goal." (Ken Withee, "Microsoft® Business Intelligence For Dummies®", 2010)

"Performance management tools that help managers track performance against strategic goals" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"Scorecards are used by enterprises to measure the progress against the enterprise strategy. Scorecards represent performance trends over a period of time such as monthly/quarterly/yearly; whereas dashboards indicate the status of a performance metric at a given point in time. In contrast, dashboards are used to represent actual granular data, they contain data that is more recent than that of scorecards." (Saumya Chaki, "Enterprise Information Management in Practice", 2015)

"A graphical representation of valid values for a source column or output of a rule in profile results. Use scorecards to measure data quality progress." (Informatica)

"A representation of summarized performance measurements representing progress towards the implementation of long-term goals. A scorecard provides static measurements of performance over or at the end of a defined interval." (ISQTB)

"A scorecard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance. Unlike dashboards that display actual values of metrics, scorecards typically display the gap between actual and target values for a smaller number of key performance indicators." (Intrafocus)

17 August 2010

SQL Server: Model Database (Definitions)

"A template for new user databases. The installation process creates model when SQL Server is installed. Each time the create database command is issued, SQL Server makes a copy of model and extends it to the size requested, if necessary." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"An SQL Server–supplied database that provides a template for new user databases. Each time a database is created, SQL Server makes a copy of the model database, sizes it to the requested size, and files the user database with the system tables and objects currently defined in the model database." (Patrick Dalton, "Microsoft SQL Server Black Book", 1997)

"A database installed with SQL Server that provides the template for new user databases. Each time a database is created, SQL Server makes a copy of the model and then extends it to the size requested. A new database cannot be smaller than the model. The model database contains the system tables required for each user database. You can modify the model to add objects that you want in all newly created databases." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A database installed with SQL Server that provides the template for new user databases. SQL Server 2000 creates a new database by copying in the contents of the model database and then expanding it to the size requested." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"The template used when creating new databases. Any new database is created from a copy of the Model database and then modified from there." (Darril Gibson, "MCITP SQL Server 2005 Database Developer All-in-One Exam Guide", 2008)

"A database that is installed with Microsoft SQL Server and that provides the template for new user databases. SQL Server creates a database by copying in the contents of the model database and then expanding the new database to the size requested." (Microsoft, SQL Server 2012 Glossary", 2012)

15 August 2010

Data Security: SQL Injection I - Introduction


  If you are working in IT, most probably you’ve heard already about SQL Injection, if not then might be it’s a good idea to ask your colleagues and eventually your IT manager if your company has any policies related to it. If you are working for a software vendor or a consultancy company then SQL Injection countermeasure techniques might be quite well positioned in the list of best practices in what concerns the development of Web/Desktop Applications, Web Services or database-related logic adopted by your company. If you are working for a company, other than the two mentioned above, and have various software projects on the role or already in house, then most probably you’ll have to ask if the software vendors you are working with have took into consideration the SQL Injection threats and proved their solutions against them. On contrary, if you have nothing to do with IT at all, it might still be a good idea to ask your IT department if they have anything in place related to SQL Injection – Security Policy, security best practices, etc.


  Wikipedia defines SQL Injection as “a code injection technique that exploits a security vulnerability occurring in the database layer of an application” [3], the code injection being defined as “the exploitation of a computer bug that is caused by processing invalid data” [4]. For a programmer the definition is acceptable, though for other type of professionals it might not be so clear what’s about, especially when they are not familiar with IT terminology. I find more clear the definition provided by J. Clarke et. al, who in his book SQL Injection Attacks and Defense, defines SQL Injection as the vulnerability that results when you give an attacker the ability to influence the Structured Query Language (SQL) queries that an application passes to a back-end database” [2]. I will slightly modify the last definition and say that the SQL injection is a security vulnerability residing in the possibility to alter the intended behavior of the SQL Queries passed to the database.

Some Background

    At the beginning of our century, with the increase importance of Web Applications whose availability over WAN/Internet (networks) brought new security issues, the SQL Injection became a really hot topic given the damages such techniques could do to an application, with just a few tricks the “hacker” having the possibility to enter in the application and even in the machine hosting the database used, entering thus in the possession of sensitive information, and above all having the possibility of damaging the database. J. Clarke et. al remarks that the first connection between web applications and SQL injection is widely accredited to Rain Forest Puppy, who in an article titled “NT Web Technology Vulnerabilities” (see “ODBC and MS SQL server 6.5” section) written in 1998 for Phrack, an e-zine written by and for hackers [2], was describing the behavior specific to SQL Injection in relation to MS SQL Server 6.5. 
    I remember when my boss break us the news that we have to protect urgently our applications against SQL Injection, having to redesign some of the database objects and components in order to protect our applications against such techniques. I was then in my first or second year of professional experience, so the topic was new and quite intriguing not only for myself but also for my colleagues, some of them having a few more years of professional programming experience that I did and, I hope I’m not mistaking, none (or few) of them actually have heard about it. It was interesting to check how simple techniques could do so much damage. At those times there were few articles on SQL Injection and specific countermeasure techniques, not to mention best practices, so we were kind of groping in the dark in finding a countermeasure to the problem.

State of Art

    Since then, the number of search engines hits on the topic is quite impressive, many professionals approaching the problem in their way, Vendors started to design their solutions and make aware programmers on best practices in order to minimize this type of security threat, books were written on this topic, the awareness increased between developers and other type of IT professionals. Even if considerable effort has been made into this direction, and the topic appears often on the blogs, there are still many web sites not designed to address SQL Injection concerns. In 2007, The WhiteHat Security, placed SQL Injection on 5th position in top of vulnerabilities, estimating that 1 out of 5 web sites is vulnerable to SQL Injection [1]. In 8th Web Security Report based on 2009 data provided by WhiteHat Security[5], and as it seems also in 9th report [6], SQL Injection remains on the same position, what’s interesting to remark is the split per scripting technology provided in [6]: 
SQL Injection - Statistics WhiteHat

   In Web Hacking Incident Database maintained by Web Application Security Consortium, SQL Injection is considered as 17.97 % out of the total 512 reported top attack methods. Even if the number of reported attacks is insignificant in report to the number of sites available on the web, the percentage of cases seems to be in agreement with the number provided in WhiteHat Security reports.


   If the topic made you curious, you could find out more with just a simple search on the Web. There are many professionals who wrote on this topic, however it’s a good idea to start directly with the resources provided by the RDBMS vendors, for example Microsoft through its Security Research & Defense blog, in SQL Injection Attacks post has an interesting list of resources on this topic. A nice document on ‘How to write SQL injection proof PL/SQL’ comes from Oracle, an interesting presentation on ‘SQL Injection Myths and Fallacies’ was made at MySQL Conference & Expo, etc.

[1] WhiteHat Security. [2007]. Website Security Statistics Report. [Online] Available from: http://www.whitehatsec.com/home/assets/WPStatsreport_100107.pdf (Accessed: 15 August 2010)
[2] J.Clarke et. al (2009). SQL Injection Attacks and Defense. Elsevier. ISBN: 978-1-59749-424-3
[3] Wikipedia. (2010). SQL Injection. [Online] Available from: http://en.wikipedia.org/wiki/Sql_injection (Accessed: 15 August 2010)
[4] Wikipedia. (2010). Code Injection. [Online] Available from: http://en.wikipedia.org/wiki/Code_injection (Accessed: 15 August 2010)
[5] WhiteHat Security. [2009]. Website Security Statistic Report, 8th Ed. [Online] Available from: http://www.whitehatsec.com/home/assets/WPstats_fall09_8th.pdf (Accessed: 15 August 2010)
[6] WhiteHat Security. [2010]. Website Security Statistic Report, 9th Ed. [Online] Available from: http://www.slideshare.net/jeremiahgrossman/whitehat-security-9th-website-security-statistics-report-3995771 (Accessed: 15 August 2010)

13 August 2010

SQL Reloaded: Temporary Tables vs. Table Variables and TempDB

    Yesterday I started to read Ken Henderson’s book, SQL Server 2005 Practical Troubleshooting: The Database Engine, diving directly into tempdb topic (Chapter 9, Tempdb issues). He mentions that metadata are created in system tables when a temporary table is created (see p.415). This means that when a temporary table is created, a record must be created in tempdb’s sys.tables and sys.columns system table, the respective records being deleted when the table is dropped. As I never looked at how the metadata of a temporary table look like, I thought is the case to do something in this direction, and here’s the code created for this purpose:

-- creating the temporary tables 
   id int NOT NULL 
, value nvarchar(50) NOT NULL) 

-- retrieving the metadata 
SELECT t.name table_name 
, s.name column_name 
, t.type  
, t.type_desc  
, t.create_date  
FROM tempdb.sys.tables t 
    JOIN tempdb.sys.columns s 
      ON t.object_id = s.object_id 
WHERE t.name LIKE '%temp%' 

-- dropping the temporary table 

temp vs variable tables - temporary example 

    By changing the width of table_name column could be seen that object’s name corresponding to the temporary tables is a combination from table’s name and, according to K. Henderson, the number designating the connection that owns the table.

    If the temporary table is stored in tempdb and metadata are stored about it, what’s happening with a temporary table? Here’s the answer:

-- creating the table variable 
  id int NOT NULL  
, value nvarchar(50) NOT NULL) 

-- retrieving the metadata 
SELECT t.name table_name 
, s.name column_name 
, t.type  
, t.type_desc  
, t.create_date  
FROM tempdb.sys.tables t 
     JOIN tempdb.sys.columns s 
      ON t.object_id = s.object_id 
WHERE t.name LIKE '%#%' 
   AND DateDiff(ss, t.create_date, GetDate()) BETWEEN -2 AND 2

temp vs variable tables - table variable example

    As can be seen I had to put a little more effort in order to see a table variable’s metadata. As there is no name that could be used in order to identify the table, as object’s name is stored as a hex number, I had to restrain the list of tables by using the timestamp. Excepting the name, the metadata stored about the two types of tables are identical for the same table definition. Actually their definition is similar with the one of a “standard” table:

-- creating a "standard" table 
  id int NOT NULL 
, value nvarchar(50) NOT NULL) 

-- retrieving the metadata 
SELECT t.name table_name 
, s.name column_name 
, t.type  
, t.type_desc  
, t.create_date  
FROM sys.tables t 
     JOIN sys.columns s 
      ON t.object_id = s.object_id 
WHERE t.name LIKE '%temp%' 

-- dropping the table 

temp vs variable tables - standard table example

    For exemplification I used a restrained list of attributes, when comparing the various table’s metadata could be used instead a SELECT * statement. The above examples reflect also the differences in declaring the three types of tables.

10 August 2010

SQL Server New Features: Information Schema Views

    In the last post, Database Object Dependencies – An introduction, I was talking about metadata, in common understanding defined as “data about data”, and its meaning in the context of databases as “information (data) stored about data, the structures or objects related to data”. The SQL92, SQL99, SQL2003, and I suppose also SQL2008 and the next coming ISO standard document versions, define an information schema called INFORMATION_SCHEMA supposed to contain a minimum of metadata about a database’s underlying objects, namely view descriptors, one base table descriptor and several domain descriptors [1]. The information schema is independent from databases’ internal system metadata implementations, fact that makes it a valuable approach in retrieving common metadata, at least from this perspective being possible to write vendor independent code as long the vendor adheres and implements the ISO/IEC 9075 standard(s).

    SQL Server 2008 makes available the Information Schema Views through INFORMATION_SCHEMA schema available in each database storing information about all database objects contained in the respective database. In order to retrieve the views available under the INFORMATION_SCHEMA schema and their definitions, could be used the following query:

-- retrieving objects' definition for INFORMATION_SCHEMA 
SELECT s.name [schema_name] 
, o.name [object_name] 
, sm.definition  
FROM sys.all_sql_modules sm 
    JOIN sys.all_objects o 
       ON sm.object_id = o.object_id  
   JOIN sys.schemas s 
      ON o.schema_id = s.schema_id  
ORDER BY o.name 

    Unfortunately there are no descriptions stored together with the database objects, and even if most of the view names are self-describing, there are a few cases in which more information are required. Here is the list again with the views and their descriptions together with the link to the MSDN section that gives more information on view’s definition:
No View Description
CHECK_CONSTRAINTS Returns one row for each CHECK constraint
2. COLUMN_DOMAIN_USAGE Returns one row for each column that has an alias data type
3. COLUMN_PRIVILEGES Returns one row for each column that has a privilege that is either granted to or granted by
4. COLUMNS Returns one row for each column
5. CONSTRAINT_COLUMN_USAGE Returns one row for each column that has a constraint defined on it
6. CONSTRAINT_TABLE_USAGE Returns one row for each table that has a constraint defined on it
7. DOMAIN_CONSTRAINTS Returns one row for each alias data type that has a rule bound to it
8. DOMAINS Returns one row for each alias data type
9. KEY_COLUMN_USAGE Returns one row for each column that is constrained as a key
10. PARAMETERS Returns one row for each parameter of a user-defined function or stored procedure
11. REFERENTIAL_CONSTRAINTS Returns one row for each FOREIGN KEY constraint
12. ROUTINES Returns one row for each stored procedure and function
13. ROUTINE_COLUMNS Returns one row for each column returned by table-valued functions
14. SCHEMATA Returns one row for each schema
15. TABLE_CONSTRAINTS Returns one row for each table constraint
16. TABLE_PRIVILEGES Returns one row for each table privilege that is granted to or granted by
17. TABLES Returns one row for each table
18. VIEW_COLUMN_USAGE Returns one row for each column that is used in a view definition
19. VIEW_TABLE_USAGE Returns one row for each table that is used in a view
20. VIEWS Returns one row for views

       As stated above, the information schema is available for each database, therefore the information schema views return only the records available in the current database to which the current user has access.

1. Above their informative character, the INFORMATION_SCHEMA definitions could be used in order to understand more about the systems tables used as source for the respective views and the relations between them.
2. Microsoft recommends not to use the INFORMATION_SCHEMA views in order to determine the schema of an object and use instead the sys.objects system catalog view [2], warning that appears in several pages from information schema documentation.
3. As it seems the SQL Server 2008 doesn’t implement all the views defined in information schema, for example ASSERTIONS, CHARACTER_SETS, COLLATIONS, TRANSLATIONS, SQL_LANGUAGES, etc. It’s also interesting to note that the respective information are available in .Net through the OleDbSchemaGuid class (see also this).

[1] ISO/IEC. (1992) ISO/IEC 9075:1992,  Database Language SQL. [Online] Available from: http://www.contrib.andrew.cmu.edu/~shadow/sql/sql1992.txt (Accessed: 8 August 2010)
[2] MSDN. (2010). Querying the SQL Server System Catalog. [Online] Available from: http://msdn.microsoft.com/en-us/library/ms189082.aspx (Accessed: 9 August 2010)

07 August 2010

Database Design: Object Dependencies I - Introduction


    Around the various data islands existing in the blue and the models that support them are created a whole range of database objects (views, stored procedures, user-defined functions) and other type of non-database objects (classes, strong-typed datasets, reports, ad-hoc queries, etc.) With each reference to a database object is created a database dependency, or simply dependency, between the database object and the objects that reference it, thus any change occurring in a database object could impact the various referents resulting in broken links, invalid calls or any type of error that might brake the calling applications or the isolated pieces of code (e.g. reports, ad-hoc queries, SQL scripts-based logic).

Tracking Database Dependencies

    Many organizations use to document such dependencies in data dictionaries or any other type of documentation, one of the reasons being the easier identification of the objects that are impacted the by changes occurring in the database structure. One of the problem is that the documentation is often application-oriented, targeting thus the application using the data, and if there are multiple applications consuming the same data, then it’s not so easy to aggregate all the dependencies especially when they are stored in Excel files or any other type of documents. When such information are stored in various dispersed documents, repositories, with (complicated) permissions access, performing an impact analysis for the targeted changes could become complicated as some digging must be done in order to get to the information. That’s one of the reasons for which an organization might consider storing in the source database as much of the business logic related directly to data. Encapsulating queries and procedural logic in views, stored procedures, user-defined functions or any other similar objects seems a good idea in order to reduce the maintenance of code, hide the complexity of a database from the consumers (users, services, web/desktop applications, etc.), and from several other considerations. The most important of these considerations is the fact that databases store not only the respective objects and statistics about them, but could store also the dependencies between them, making easier the impact analysis or any type of analysis based on the dependency between objects. I said “could” because it’s at the discretion of developers, architects or any other type of professional with decision power on whether they want to take advantage of such functionality.

Foreign Key Constraints

     The simplest and most natural dependence information to store are the primary-foreign key relations implemented in the form of a constraint. The foreign key constraints, as they are called, identify and enforce the relationship between two tables; “identify” because it makes the relation explicit, and “enforce” because it checks the validity of foreign-primary key values pairs when records are inserted, updated or deleted, enforcing thus the referential integrity of the database. When a deletion is attempted on a record, the database engine checks if there is any dependent record (in the same or other table) that references the respective record, and if such a constraint is defined, the deletion is aborted raising also an error message. A check is performed also when a record is inserted or updated in the child table, the respective actions being aborted if the foreign key reference is not valid. On the other side a foreign key constraint could bring additional complexity during migration tasks, though with a little effort and a good architecture the overhead is minimized. In addition the foreign key constraints could be used by third party tools to provide some degree of automation when joining tables or for other purposes.

Object Dependencies

      More complex dependency regard the dependency between database objects  – views, stored procedures, user-defined functions or tables. In some cases is enough to see that there is a dependency between two objects, though in more complex situations would be useful to know which specific attribute is used from the dependency objects, especially when using the metadata for automation tasks. By creating the dependency tree, the tree of objects resulted from the dependency between the various database objects, it’s possible to provide, at least in theory, more accurate impact assessments.

     So until now were considered the dependencies between database objects , though, as highlighted above, there are many other objects stored outside of a database and referencing database objects. It makes sense to have a global repository in which to store information about dependencies, preferably in a relational database which could be easily interrogated using simple flat or hierarchical queries.


    The object definitions, statistics, dependencies and other type of information stored about data or the structures or objects related to data are encompassed under the denomination of metadata, which in common understanding is defined as “data about data”. The metadata could be used not only as input for impact analysis but also for automating business logic, functionality that opens new perspectives in development. Einstein’s believe that “problems cannot be solved by the same level of thinking that created them” is reflected in the world of databases by the fact that the metadata stored about database objects help to solved problems related to the objects and the data the databases contain. For example during a data migration project the two database structures could be mapped at table and attribute level, being possible thus to create validation rules in an automated manner.

     Even if databases come with a predefined structure of storing metadata, the various solutions developed on top of such databases require additional metadata to be stored, and in theory it would be great if databases’ metadata structures could be extended for this purposes, though given the risks involved in altering such structures lead to the existence of parallel metadata repositories, in which an important percent of the database’s metadata are duplicated.

Beyond Database Dependencies

    Talking about data mappings, integration projects and integration functionality/features rely heavily on data mappings, they involving a degree of automation too. Integration of data doesn’t necessarily occur only at application level, in the context of web’s evolution, the tendency is to link and integrate the various data islands (see linkeddata.org), especially the ones with public character, and provide thus cross-database functionality. Many of the problems such an approach implies are solved at metadata level, new metadata and dependency levels being required for this purpose.

03 August 2010

Strategic Management: Balanced Scorecard (Definitions)

"An evaluation method, created by Robert Kaplan and David Norton, that consists of four perspectives (customer, learning, business, and financial) and is used to evaluate effectiveness." (Teri Lund & Susan Barksdale, "10 Steps to Successful Strategic Planning", 2006)

"A strategic management system that connects activities to strategic goals and measures how much the activities contribute to achieving those goals. It provides a broader view of the business than merely looking at financial data. Devised by management theorists Robert Kaplan and David Norton." (Steve Williams & Nancy Williams, "The Profit Impact of Business Intelligence", 2007)

"A type of scorecard application that tracks an organization's progress from various perspectives simultaneously." (Ken Withee, "Microsoft® Business Intelligence For Dummies®", 2010)

"A formal approach used to help organizations translate their vision into objectives that can be measured and monitored using both financial and non-financial performance measures." (Leslie G Eldenburg & Susan K. Wolcott, "Cost Management" 2nd Ed., 2011)

"A performance measurement approach that links business goals to performance metrics." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"A management tool that measures and manages an organization's progress toward strategic goals and objectives. Incorporates financial indicators with three other perspectives: customer, internal business processes, and learning and growth." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

"A balanced scorecard tallies organizational performance in financial, customer service, internal process, and innovation and learning areas." (John R Schermerhorn Jr, "Management" 12th Ed., 2012)

"First proposed by Kaplan and Norton in 1992, the balanced scorecard focused on translating strategy into actions, and promoted a move away from traditional financial measures. Instead, organizations were encouraged to develop a broad range of financial and nonfinancial lead and lag measures that provided insight into overall operating performance." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

"One of the widely adopted performance management frameworks is the balanced scorecard technique designed by Kaplan and Norton. Balanced scorecards involve looking at an enterprise (private, public, or nonprofit) through four perspectives: financial, customer, learning and growth, and operations." (Saumya Chaki, "Enterprise Information Management in Practice", 2015)

"A tool for linking strategic goals to performance indicators. These performance indicators combine performance indicators relating to financial performance, consumer satisfaction, internal efficiency, and learning and innovation." (Robert M Grant, "Contemporary Strategy Analysis" 10th Ed., 2018)

"A balanced scorecard (BSC) is a performance measurement and management approach that recognizes that financial measures by themselves are not sufficient and that an enterprise needs a more holistic, balanced set of measures which reflects the different drivers that contribute to superior performance and the achievement of the enterprise’s strategic goals. The balanced scorecard is driven by the premise that there is a cause-and-effect link between learning, internal efficiencies and business processes, customers, and financial results." (Gartner)

"A strategic tool for measuring whether the operational activities of a company are aligned with its objectives in terms of business vision and strategy." (ISQTB)

"An integrated framework for describing strategy through the use of linked performance measures in four, balanced perspectives ‐ Financial, Customer, Internal Process, and Employee Learning and Growth. The Balanced Scorecard acts as a measurement system, strategic management system, and communication tool." (Intrafocus) 

01 August 2010

Resources: SQL Server Troubleshooting I

    Last week the SQL Server troubleshooting-related topics came again on my table, and it’s actually quite an important topic. As I have disparate links I thought it makes sense to bring the links together in a post.

    When searching for information it’s always a good idea to start with the documentation or the support site, in what concerns SQL Server troubleshooting Microsoft has several valuable resources on what concerns performance issues, application performance, ad-hoc queries, blocking, stored procedure recompilation, clusters, etc.  Even if outdated, of interest could be also the Improving .Net Application Performance and Scalability resource,  with a chapter on SQL Server Performance and ADO.NET. Other resources could be found in Technet, for example Troubleshooting Performance Problems in SQL Server 2005, a similar document being available on SQL Server 2008 from MSDN. As a way to avoid the need for troubleshooting, it makes sense to check also the SQL Server Best Practices.

    There are several good books on this topic I heartily recommend, the first on my list is the book of C. Bolton et al, Professional SQL Server 2008 Internals and Troubleshooting. What’s interesting to note is that the book is available to browse and read on Scribd as part of a eBook Deal with Wiley, deal that includes several other programming and non-programming books (See Wiley’s profile on Scribd). The code for several chapters from the C. Bolton's book is available on Wiley’s website. Of interest are especially the chapters on DMV (dynamic management views) because performance troubleshooting often resumes in searching for hints in SQL Server internal tables. Another book, actually booklet, on DMV comes from Redgate, the SQL Server DMV Starter Pack, the pack being available also with a list of 30 sample scripts downloadable together as zip.

   Talking about scripts, there are many scripts available on DMV from Technet’s Script Repository. If you want to get an overview of your SQL Server configuration and health, you could check Diagnostic Information Queries available from Glen Berry’s blog for SQL Server 2005, respectively SQL Server 2008 and 2008R2.

Related Posts Plugin for WordPress, Blogger...