Last week, from March 23-25, 2011 were amongst the 3 most important and exciting days for anyone remotely connected with Microsoft technologies. They were the days when the Tech-Ed 2011 (India) was hosted by Microsoft at the Lalit Ashoka Hotel in Bengaluru, Karnataka.

Microsoft Tech-Ed 2011

Microsoft Tech-Ed is the premier technical education and networking event for tech professionals interested in learning, connecting and exploring a broad set of current and soon-to-be released Microsoft technologies, tools, platforms and services.This year, Tech-Ed 2011 had been divided into a series of multiple tracks mentioned below:

1. Developers
2. Infrastructure Professionals – Focused on solutions that save time, reduce costs and provide an efficiently managed data center
3. Architects – Focus is on bringing in uniqueness and offering niche topics
4. Management – Focused on innovating and reinventing oneself to win the dreams that have been built over the years
5. Interoperability – The focus here is on how businesses today can seamlessly interoperate and integrate with multiple vendor systems, technologies and applications using highly flexible Microsoft technologies
6. Information workers – These sessions focus on how Microsoft hardware and software can help us lead a more productive and comfortable lifestyle
7. Chalk Talks – conducted for the first time in Tech-Ed, these are “free-style” sessions making them a great place to have a great dialog and Q&A with the who’s who of Microsoft technologies

We, being developers, are ultimately most interested in the Developers track, which was further divided into:

1. The Next Web
2. Client Development
3. Database Development
4. Unleash a more beautiful web
5. Core Dev
6. Cloud Services and the Windows platform
7. Business Intelligence
8. Visual Studio Tools
9. Sharepoint Development

Read more about Tech-Ed 2011 (India) at http://www.microsoft.com/india/teched2011/

Through the next couple of posts, I will be sharing with you my experience on the wonderful time I had at the Tech-Ed event.

Opening Keynotes

Tech-Ed 2011 began by the registration of what I believe to be a crowd of at least 3000 participants. Once the registration was complete, we all started to proceed towards the main keynote area for the keynotes.

On Day 01, we were lucky to have keynotes from esteemed leaders like Mr. Qi Lu, President, Microsoft’s Online Services Division and Mr. Yousef Khalidi a Distinguished Engineer (Windows Azure) at Microsoft.

Opening his keynote session, Mr. Qi Lu appreciated India’s IT workforce as the world’s 2nd largest developer ecosystem. His session was focused on how this developer ecosystem can contribute to the making of a new web and how Microsoft’s online division is working towards this goal by developing new ways to interact and providing intelligence through services.

He introduced the concept of the consumer cloud – one that is an online service which can understand user intent using natural user interfaces like the Microsoft Kinect to enable task completion by local commerce and personal relevance. He demonstrated how Microsoft’s Bing has the vision to usher in a new cloud organizing paradigm by combining the Web of pages and the Web of people for better target-ability, measurability and predictability of the search results.

Mr. Yousef Khalidi focused on how we have grown and come almost a full circle as we moved from centralized, thin clients to distributed computers and now on to large data centers running scaled-out commodity hardware. He explained how Windows Azure is an example of Platform-as-a-Service (PaaS). However, the best take-away from his session was the definition of a “cloud” – A cloud is a style of computing provided as a service over the Internet using dynamically scalable, virtualized hardware and resources.

By the end of the session, I was left with great surprise for Windows Azure after learning that prime-time applications like Windows Gaming, Bing Twitter, Docs.com and Microsoft Hohm use Windows Azure.

Post lunch – Sessions on Database Development

After the lunch at the pool-side (being at a Microsoft event has it’s benefits), it was time for the power-packed break-out sessions.

The first of these sessions was from Vinod Kumar (blog) on the ““Unexplained” of SQL Server Security”.

Vinod demonstrated the secure SQL Server login process using the Microsoft’s Network Monitoring tool (download here). He showed the audience that not for a single handshake is the user password being exchanged over the wire. Later, he took the audience for a deep dive into SQL Server security by demonstrating how permissions can be restricted to a particular group of columns in a table to restrict the user of SELECT * and how one can use Policy Management to implement SQL Server security. He also demonstrated how auditing can be made secure and system provided an ability to detect an attempt to intrude via impersonation by the use of SQL Server certificates.

After Vinod’s session into the internals of Microsoft SQL Server, we had a session on “SQL Server Denali – What is new for Database Developers” by Prachi Bora, a Program Manager at Microsoft India R&D. She covered some of the exciting new features of SQL Server “Denali”, which include:

1. Statistical Semantic Search
2. “Surrounds With” feature
3. Substring matching in Intellisense
4. Conditional Breakpoints

After the tea break…”What did I do?”

After the tea break, we had a wonderful session on the worst T-SQL practices by none other than our very own SQL Server MVP – Mr. Jacob Sebastian!

The hall was packed with more than 200 attendees, and everyone participated whole-heartedly as Jacob ran through some of the most common T-SQL worst practices that he has seen in T-SQL code over the years. Everyone in the hall was, I am sure, recalling the various lines of code that they would need to go back and change as soon as they resumed office on Monday! Jacob highlighted the various performance and computational issues that might arise due to a simple slip of the mind on account of the developer attempting to finish off a task in a hurry. The session has left such an impression that I will, for my record, be writing a detailed post on the various points highlighted by Jacob. Stay tuned!

After Jacob’s session, it was a once-in-a-lifetime opportunity for all present in the hall at the time as Mr. Prem Mehra, a program manager with the SQLCAT (SQL Customer Advisory Team – http://sqlcat.com) at Microsoft in Redmond stepped up on stage. The honourable Mr. Mehra has over 49 years of experience in the IT industry, and it was simply mesmerizing to watch him talk about some of “The Largest, Mission-Critical Deployments of Microsoft SQL Server around the world!” He talked about some SQL Server deployments spanning leading US insurance providers, health-care organizations, financial institutions, banks and betting web-sites.

During the session, someone asked Mr. Mehra a question regarding the comparison of Microsoft SQL Server with the competition in terms of scalability, high availability and reliability. In response, Mr. Mehra simply presented the following slide and left the audience to judge for themselves. For me, it was a proof of something I have always believed – the product we love, Microsoft SQL Server, is simply the best!

Closing time – Demo Extravaganza!

As the evening set in, it was time to end the day on an action-packed, excited note. We gathered back into the main keynote hall, where we had a half hour of the most electrifying demos – all completed in less than 3 minutes each! What a magical atmosphere had been created – almost as if it was Hogwarts and Harry Potter himself was presenting!

Stay tuned for a detailed account of excitement on Tech-Ed 2011 (India) Day 02!

Until we meet next time,

Be courteous. Drive responsibly.

This is part of the series of posts that I am running under the title "Under Appreciated Features of SQL Server". The series has been inspired by Andy Warren’s editorial on SQLServerCentral.com.

The UPDATE Statement

Today, I will attempt to approach describing the OUTPUT clause in a slightly different manner. We will simply forget about it for a moment. We will talk about something much more simple and well-known like the UPDATE.

But, the UPDATE statement is not that simple – it’s actually two statements rolled into one – a DELETE and an INSERT are actually wrapped into a single statement.

Does that sound familiar? I am sure that you would have heard about the two special tables that SQL Server provides – the DELETED and INSERTED tables (Reference: http://msdn.microsoft.com/en-us/library/aa214435(SQL.80).aspx). These tables are used within triggers to:

• Extend referential integrity between tables
• Insert or update data in base tables underlying a view
• Check for errors and take action based on the error
• Find the difference between the state of a table before and after a data modification and take action(s) based on that difference

Here’s a quick example:

USE AdventureWorks2008R2
GO
--Step 01: Create two tables - the test table, and an Audit table
CREATE TABLE MyTABLE (MyId INT, MyCity VARCHAR(20))
CREATE TABLE MyAudit (MyChangedId INT, OldCityValue VARCHAR(20), NewCityValue VARCHAR(20), ModificationDate DATETIME)
GO

--Step 02: Insert some test data into these tables
INSERT INTO MyTABLE VALUES (1,'Gandhinagar'),
                           (2,'Ahmedabad'),
                           (3,'Mumbai'),
                           (4,'Delhi'),
                           (5,'Bangalore')
GO

--Step 03: Create a test trigger to demonstrate the most typical use of DELETED & INSERTED tables
CREATE TRIGGER trig_MyTable
ON MyTABLE
FOR UPDATE
AS
BEGIN
    INSERT INTO MyAudit (MyChangedId, OldCityValue, NewCityValue, ModificationDate)
                SELECT [DELETED].[MyId],
                       [DELETED].[MyCity],
                       [INSERTED].[MyCity],
                       GETUTCDATE()
                FROM [DELETED] [DELETED]
                INNER JOIN [INSERTED] [INSERTED] ON [DELETED].[MyId] = [INSERTED].[MyId]
END
GO

--Step 04: Perform a test update
SET STATISTICS IO, TIME ON

UPDATE mt
SET mt.MyCity = 'New Delhi'
FROM MyTABLE mt
WHERE mt.MyId = 4

SET STATISTICS IO, TIME OFF

--Step 05: Take a quick look at the data
SELECT MyId, MyCity FROM MyTABLE
SELECT MyChangedId, OldCityValue, NewCityValue, ModificationDate FROM MyAudit

--Step 06 - Perform some cleanup
DROP TABLE MyTABLE
DROP TABLE MyAudit

Upon running these scripts, you would notice that this is quite an reasonable method to maintain a custom log of critical transactions/queries.

The OUTPUT Clause

However, it might be possible that sometimes, you may not want to use triggers (because of personal choice, or because of the fact that triggers can be disabled); or this is a one-off debugging exercise or just an effort to learn the internals of SQL Server. In such cases, the recently introduced OUTPUT clause can be very useful.

USE AdventureWorks2008R2
GO
--Step 01: Create two tables - the test table, and an Audit table
CREATE TABLE MyTABLE (MyId INT, MyCity VARCHAR(20))
CREATE TABLE MyAudit (MyChangedId INT, OldCityValue VARCHAR(20), NewCityValue VARCHAR(20), ModificationDate DATETIME)
GO

--Step 02: Insert some test data into these tables
INSERT INTO MyTABLE VALUES (1,'Gandhinagar'),
                           (2,'Ahmedabad'),
                           (3,'Mumbai'),
                           (4,'Delhi'),
                           (5,'Bangalore')
GO

--Step 03: Perform a test update
SET STATISTICS IO, TIME ON

UPDATE mt
SET mt.MyCity = 'New Delhi'
    OUTPUT [deleted].[MyId], [deleted].MyCity, [inserted].MyCity, GETUTCDATE()
    INTO MyAudit
FROM MyTABLE mt
WHERE mt.MyId = 4

SET STATISTICS IO, TIME OFF

--Step 04: Take a quick look at the data
SELECT MyId, MyCity FROM MyTABLE
SELECT MyChangedId, OldCityValue, NewCityValue, ModificationDate FROM MyAudit

--Step 05 - Perform some cleanup
DROP TABLE MyTABLE
DROP TABLE MyAudit

What’s the benefit?

Drastically reduced & simplified code, and yet we get the same results. At the end of the day, it’s all about the benefits of a particular approach. So, do we have any improvement? We had the I/O and TIME statistics ON during the UPDATE statements. Let’s see what stories they tell us.

Here’s the output from the conventional trigger-based approach.

Table ‘MyTABLE’. Scan count 1, logical reads 1, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.

(1 row(s) affected)

(1 row(s) affected)

SQL Server parse and compile time:

   CPU time = 0 ms, elapsed time = 8 ms.

Table ‘MyAudit’. Scan count 0, logical reads 1, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.

(1 row(s) affected)

(1 row(s) affected)

SQL Server Execution Times:

   CPU time = 0 ms,  elapsed time = 120 ms.

SQL Server Execution Times:

   CPU time = 0 ms,  elapsed time = 131 ms.

SQL Server parse and compile time:

   CPU time = 0 ms, elapsed time = 0 ms.

SQL Server Execution Times:

   CPU time = 0 ms,  elapsed time = 0 ms.

And here’s the same from the OUTPUT clause:

SQL Server parse and compile time:

   CPU time = 10 ms, elapsed time = 15 ms.

Table ‘MyAudit’. Scan count 0, logical reads 1, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.

Table ‘MyTABLE’. Scan count 1, logical reads 1, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.

(1 row(s) affected)

(1 row(s) affected)

SQL Server Execution Times:

   CPU time = 0 ms,  elapsed time = 58 ms.

SQL Server parse and compile time:

   CPU time = 0 ms, elapsed time = 0 ms.

SQL Server Execution Times:

   CPU time = 0 ms,  elapsed time = 0 ms.

While there is no difference in the I/O (1 scan, 2 logical reads), the execution time has definitely improved with a total of (8+120+131) ms = 159ms with the trigger based approach v/s (15+58) ms = 75ms with the OUTPUT clause.

Finally, the OUTPUT clause can be used with all 3 of the major T-SQL statements – UPDATE, INSERT and DELETE!

Some finer points

The OUTPUT clause does not support:

1. Subqueries or user-defined functions that perform user or system data access, or are assumed to perform such access. User-defined functions are assumed to perform data access if they are not schema-bound
2. A remote table, view, or common table expression as it’s target
3. A target with a FOREIGN KEY constraint, or referenced by a FOREIGN KEY constraint
4. Triggers on the target
5. A target participating in replication

Besides the above, be careful with the behaviour of @@ROWCOUNT. It will only return the number of rows affected by the outer INSERT statement.

Lots more information can be obtained by visiting the Books-On-Line page at: http://msdn.microsoft.com/en-us/library/ms177564(v=SQL.110).aspx

In Conclusion – a small challenge

Now that you are powered with the knowledge of the OUTPUT clause, can you answer the following Question of the Day at SQLServerCentral?

http://www.sqlservercentral.com/questions/T-SQL/72013/

Do leave a note as to how you did, and what are your thoughts on the same.

Until we meet next time,

Be courteous. Drive responsibly.

This is part of the series of posts that I am running under the title "Under Appreciated Features of SQL Server". The series has been inspired by Andy Warren’s editorial on SQLServerCentral.com.

Did you ever wonder if you could create a temporary result set and use that within a single SELECT, INSERT, UPDATE or DELETE statement? I bet you have, and before SQL Server 2005 came along, I am sure that you used either sub-queries, cursors or temporary tables  to achieve the desired results.

Starting SQL Server 2005, we have a much better, and much more efficient method of achieving this – the common table expression, or the CTE. Much has been written about CTEs and their benefits, and hence I will be mostly presenting a summary of all the great articles and posts on the topic that I have chanced upon till date:

1. An introduction to CTEs – http://www.simple-talk.com/content/article.aspx?article=260
2. The things that you can do with a CTE – http://msdn.microsoft.com/en-us/library/ms175972.aspx
3. A few data points on CTE – http://msdn.microsoft.com/en-us/magazine/cc163346.aspx#S3

Something interesting – CTE in a CREATE VIEW statement

Yes, CTEs can be used in a CREATE VIEW statement as is demonstrated by the queries below:

USE AdventureWorks2008R2;
GO
CREATE VIEW vSalesCTE
AS
    -- Define the CTE expression name and column list.
    WITH Sales_CTE (SalesPersonID, SalesOrderID, SalesYear)
    AS
    -- Define the CTE query.
    (
        SELECT SalesPersonID, SalesOrderID, YEAR(OrderDate) AS SalesYear
        FROM Sales.SalesOrderHeader
        WHERE SalesPersonID IS NOT NULL
    )
    SELECT Sales_CTE.SalesPersonID, Sales_CTE.SalesOrderID, Sales_CTE.SalesYear
    FROM Sales_CTE;
GO

--Use the VIEW containing a CTE
SELECT vcte.SalesPersonID, COUNT(vcte.SalesOrderID) AS TotalSales, vcte.SalesYear
FROM vSalesCTE vcte
GROUP BY vcte.SalesYear, vcte.SalesPersonID
ORDER BY vcte.SalesPersonID, vcte.SalesYear

Don’t overestimate CTEs – don’t use them multiple times within the same query

As is the case with everything, CTEs in excess can also cause more harm than good. CTEs are more of “expandable” blocks of code, and hence, if you use them more than once in a query, you will end up with performance issues. This is because the entire data set is populated the number of times a CTE is used. For cases where you need to use the same data set again and again, use temporary tables or table variables instead.

I hope that CTE’s opened up a whole new programming paradigm for all. If you have not started experimenting with CTEs, I recommend that you start doing so – it will be fun.

Until we meet next time,

Be courteous. Drive responsibly.

This is part of the series of posts that I am running under the title “Under Appreciated Features of SQL Server“. The series has been inspired by Andy Warren’s editorial on SQLServerCentral.com.

Introduction

Normally, we all work with subsets of rows that meet a pre-defined, user defined criteria (Ex. records corresponding to transactions done on any given date, etc). Any subset of user-defined records or rows is called a “window”. Please note that the keyword here is user-defined. A window thus corresponds to rows returned as a result of a particular user query.

Any function that operates on each rows of this user-defined set of rows or “window” is called a “windowing function”. Windowing functions are an ISO defined SQL standard, and Microsoft SQL Server (2005 and up) provides us with the option to use ranking and aggregate windowing functions. Today we will study a few of these powerful functions.

SQL Server Books-On-Line is a great learning resource for these, and hence I have basically compiled the information in Books-On-Line as an introduction to the windowing functions.

OVER clause

The OVER clause determines the partitioning and ordering of the rowset before the associated window function is applied. This is similar to the function of the GROUP BY and the ORDER BY clause, but is executed during the SELECT operation itself – so that the output of these operations can be provided to the ranking functions we will see in a minute. The ORDER BY clause has been enhanced to work with the OVER clause that allows us to create ordered partitions.

The advantage that the OVER clause and the windowing functions have over the conventional GROUP BY and ORDER BY implementations is that the partitions and ordering for each function is independent. To do this conventionally, we would have required the use of sub-queries – the OVER clause is far more efficient than that. In the following example, I take the script provided in Books On Line and attempt to reproduce just one aggregate operation (SUM) using the conventional methods.

--Enable the actual execution plan to see the performance benefits of the OVER clause
--Refer (http://beyondrelational.com/blogs/nakul/archive/2011/03/10/some-underappreciated-productivity-features-of-ssms.aspx)
--or use Ctrl+M

--Clear out the procedure cache
DBCC FREEPROCCACHE
GO

USE AdventureWorks2008;
GO
SELECT SalesOrderID, ProductID, OrderQty
    ,SUM(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Total'
    ,AVG(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Avg'
    ,COUNT(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Count'
    ,MIN(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Min'
    ,MAX(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Max'
FROM Sales.SalesOrderDetail 
WHERE SalesOrderID IN(43659,43664);
GO

--Clear out the procedure cache
DBCC FREEPROCCACHE
GO

USE AdventureWorks2008;
GO
SELECT sd.SalesOrderID, sd.ProductID, sd.OrderQty,
       (SELECT SUM(sd1.OrderQty) FROM Sales.SalesOrderDetail sd1 WHERE sd1.SalesOrderID = sd.SalesOrderID) AS 'Total'
FROM Sales.SalesOrderDetail sd
WHERE sd.SalesOrderID IN (43659, 43664)
GROUP BY sd.SalesOrderID, sd.ProductID, sd.OrderQty

Let’s see how the actual execution plan came along. (To display the actual execution plan, you may refer my previous post or use Ctrl+M before executing the query)

The screen-shot says it all! Performing all aggregation operations – SUM, AVG, COUNT, MIN and MAX using the OVER clause are far more efficient than doing a single SUM operation using the conventional methods.

Finally, please note that the OVER clause cannot be used with the CHECKSUM aggregate function.

Ranking functions

As the name suggests, ranking functions return a ranking value for each row in the particular window/partition. Ranking may be unique depending upon the type of ranking function used. Please note that all ranking functions are non-deterministic. You may want to keep this in mind for performance considerations.

Four ranking functions are available in Microsoft SQL Server, and they are as under:

Ranking Function	Brief description (per BOL)	Unique ranking?	BOL Link
RANK	Returns the rank of each row within the partition of a result set. If two records share the same rank, a gap is observed in the sequence, ex. if two records share the same rank #1, the next rank issued will be #3.	N	Click here
DENSE_RANK	Returns the rank of rows within the partition of a result set, without any gaps in the ranking. Ex. if two records share the same rank #1, the next rank issued will be #2.	N	Click here
NTILE	Distributes the rows in an ordered partition into a specified number of groups. The groups are numbered, starting at one. For each row, NTILE returns the number of the group to which the row belongs.	N	Click here
ROW_NUMBER	Returns the sequential number of a row within a partition of a result set, starting at 1 for the first row in each partition.	Y	Click here

To demonstrate these functions in action, I have  slightly modified the example provided to us in BOL as under:

USE AdventureWorks2008;
GO

--Ordering the result by the Postal Code
SELECT p.FirstName, p.LastName
    
    --Unique row-number
    ,ROW_NUMBER() OVER (ORDER BY a.PostalCode) AS 'Row Number'
    
    --Provide a rank, such that the largest Postal Code gets the highest rank 
    --Break in the sequence expected if more than one record share the same rank
    ,RANK() OVER (ORDER BY a.PostalCode) AS 'Rank'
    
    --Provide a rank, such that the largest Postal Code gets the highest rank
    --No break in the sequence
    ,DENSE_RANK() OVER (ORDER BY a.PostalCode) AS 'Dense Rank'

    --Break the result set in 4 groups.
    --Because for AdventureWorks, the result is a set of 13 records, we have the set with the
    --largest postal code has 4 records, rest have 3. The result seen in the column 'Quartile' is
    --actually the group number in which the record belongs to
    ,NTILE(4) OVER (ORDER BY a.PostalCode) AS 'Quartile'

    ,s.SalesYTD, a.PostalCode
FROM Sales.SalesPerson s 
    INNER JOIN Person.Person p 
        ON s.BusinessEntityID = p.BusinessEntityID
    INNER JOIN Person.Address a 
        ON a.AddressID = p.BusinessEntityID
WHERE TerritoryID IS NOT NULL 
    AND SalesYTD <> 0;

 

The results of executing the above script are as under:

• Ordering is by PostalCode to determine the RANK. Hence, we will have only two sets of values – beginning at the actual row number (i.e. 1 and 6)
• On the other hand, for DENSERANK(), we continue to have two sets of values, but they longer follow the Row Number
• Finally, notice that for NTILE, the SQL Server attempted to divide 13 records into 4 groups, which resulted in the 1st group being larger than the other 3

Reference

The following are good references for understanding windowing functions:

1. OVER clause – http://msdn.microsoft.com/en-us/library/ms189461.aspx
2. RANKING functions – http://msdn.microsoft.com/en-us/library/ms189798.aspx
3. Aggregate functions – http://msdn.microsoft.com/en-us/library/ms173454.aspx

In Conclusion

Windowing functions are so efficient and easy to use that starting the day I was introduced to them, I have always used them wherever possible. I suggest you too, give it a try. Do post your feedback and also mention the challenges that you have in working with windowing functions.

Until we meet next time,

Be courteous. Drive responsibly.

This month, we will exercise some gray cells. The T-SQL Quiz 2011 is now in progress, and I hope that by now, all of the T-SQL fans amongst you would have visited it.

For those who came in late, the T-SQL Quiz is an annual Quiz on T-SQL organized on this very web-site! I have been following it and participating since the last two years, and below is my experience so far:

• T-SQL Quiz is a great way to learn 30 new things in 30 days! – a crash course in the comfort of your home without any investment
• Some of the best Quizmasters contribute to the quiz – they have tons of industry experience, and are active community contributors
• You can have as many contributions as you wish
• T-SQL Quiz is always open for viewing – even after the submissions close. This can serve as great future reference when similar situations come up at work
• Anyone can participate!
• Most importantly, it’s fun!

So, how can I start?

Well, you start by visiting the T-SQL 2011 Quiz URL – http://beyondrelational.com/quiz/SQLServer/TSQL/2011/default.aspx – and then clicking on each day of the calendar to look at, and answer the question for that particular day.

But, I am online only once a week…

That’s not a problem. Each question is open for a period of 30 days, so you have plenty of time to research, learn about and then answer the question.

The rewards

This is the most interesting part – rewards! The first prize is an Apple iPad sponsored by Redgate Software!

So, what are you waiting for? Give T-SQL Quiz 2011 a try this week-end itself. I am sure you will enjoy the experience. If you have any questions, head over to the FAQs section at http://beyondrelational.com/quiz/faq.aspx

Until we meet next time,

Be courteous. Drive responsibly.