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The SQL Server Sample Databases: Adventureworks Derivatives

Last updated Mar 28, 2003.

We’re in a series that explains the main sample databases that you can use with SQL Server, and in this tutorial I’ll show you how to find, install and work with the sample databases based on AdventureWorks.

There are two other databases built on the Adventureworks platform, which is another reason I’ve come to like it as I described in the last article in this series. There’s a great overview as well from Microsoft on these databases here.

I’ve heard criticism in the past of the Adventureworks database that it is “too large” or “too complicated”. In future tutorials I’ll show you examples of some more simple queries, focusing in on only one schema.

And that’s the focus of the first of the databases built on the Adventureworks platform — AdventureworksLT, or “Lite”.


Although this sample database was the last to be built on the Adventureworks platform, we’ll consider it first. This database was born out of that very criticism I mentioned a moment ago. Because Adventureworks is larger than the other sample databases and includes almost everything you could want to test or try, it’s necessarily more complicated. It’s a bit like going from a corner market to a large super-store. And yet most of us are fine with that — we go to the super-store all the time and just visit the isles we care about. It should be the same with the databases, but people just wanted a smaller, simpler one. And so here it is.

You can download AdventureworksLT from the locations I give at the bottom of this article, just as you can the others. Just like the others, I recommend you back it up once you’ve installed it on your system, that way you can play with it and restore it when you’re done.

The AdventureworksLT database is based on a product sales scenario from its larger brother. It has a different design, which is more de-normalized than Adventureworks. This means that you can get to a coherent set of data with only a join or two, or even no joins at all in your SELECT statements. This makes it easier to deal with for simple examples.

It’s also much smaller than Adventureworks, which weighs in at around 183 Megabytes. AdventureworksLT is down to 7 Megabytes, which not only makes the footprint on your system smaller but it’s easier to store on a thumb drive or download. It has twelve tables instead of Adventureworks’ seventy.

I’ve mentioned “schemas” before, which are new for SQL Server 2005. To oversimplify a bit, they provide a name that acts as a “container” for other objects. You can use a schema to separate and secure objects like tables in your databases. For instance, you could create a schema called “sales” and then create a table in it called “customers”. You could also create a schema called “finance” and create another “customers” table there. You can then select data from each of them like this:

FROM sales.customers;
FROM finance.customers;

Each of these tables is different because they “live” in separate schemas. You can then secure these tables based on the schemas.

In Adventureworks, there are five schemas and the dbo default schema. In AdventureworksLT, there is only one schema (called SalesLT) and the dbo default schema.

Let’s take a look at a couple of simple queries from AdventureworksLT. Here’s a simple query that returns the first and last names of customers along with their e-mail addresses:

, LastName
, EmailAddress
FROM SalesLT.Customer

You could of course add a WHERE clause to that to get a subset of the data. Here’s a slightly more complicated three-join query that gets back a mailing label format:

 RTRIM(a.Firstname) + ' ' + RTRIM(a.LastName)
, b.AddressLine1
, b.AddressLine2
, RTRIM(b.City) + ', ' + RTRIM(b.StateProvince) + '  ' + RTRIM(b.PostalCode)
, CountryRegion
FROM SalesLT.Customer a
INNER JOIN SalesLT.CustomerAddress c 
  ON a.CustomerID = c.CustomerID
  ON b.AddressID = c.AddressID
ORDER BY a.LastName ASC;

For more joining fun, you can find a full diagram of AdventureworksLT here.


The next sample database we’ll take a look at is Adventureworks DW. This database is used for two purposes: Data Mining and On-Line Analytical Processing (OLAP). Together these functions are part of a Business Intelligence infrastructure. Let’s take a quick look at each.

Data Mining is the process of numerically deriving information from large sets of data. In Data Mining, you’re looking for patterns and trends in your data. You can then define these patterns and trends into a mining model, which you use to do sales forecasting, predictions and so on.

Microsoft SQL Server Analysis Services (SSAS) provides a mechanism to create, collect and display your mining models. I won’t cover that complete process here – that’s a set of articles on its own — but you can use the AdventureworksDW sample database to learn about these concepts.

On-Line Analytical Processing (OLAP) is less numerically and pattern oriented than a Data Mining structure is. It involves de-normalizing and consolidating lots of data into another structure so that it can be looked at in multiple ways. Not only does that allow you to do predictions, but it also allows you to do discovery on your data. I have a series of articles on these topics starting here, if you want to learn more, and InformIT has a ton of information on both Data Mining and OLAP.

With that short background, we can talk a little about the structure of the AdventueworksDW database. It actually has structures for both of these functions. It contains sample structures for the Data Warehouse, which holds the base data for the other functions, data structures and layouts for Data Mining, and OLAP structures. The entire structure is built around analyzing the Adventureworks business scenarios I detailed in my last tutorial in this series, focusing on sales and finance, which is a pretty common use for Business Intelligence.

The Data Warehouse section of the database lets you play with SQL Server Integration Services (SSIS) to practice your Extract, Transform and Load (ETL) processes, arguably one of the biggest maintenance and support areas in a Business Intelligence landscape.

The Data Mining structures in AdventureworksDW support analysis such as clustering customer selections, mailing campaign efficiencies, and general forecasting.

Finally, the OLAP structures allow you to check how efficient your sales force is, actual and budget spending, and so on.

As you can imagine, there’s a lot of data here — to see a good break-out of the structures check the AdventureworksDW database diagram found here, and to learn more about these scenarios check out the overview from Microsoft here.

InformIT Articles and Sample Chapters

An oldie but a goodie — This sample chapter from all the way back in SQL Server 7.0 talks about restoring databases.

Books and eBooks

Using Excel Visual Basic for Applications is a great book that uses pubs to teach you about Visual Basic for Applications.

To search for more info yourself, check out the search engine on Safari, the online book resource at InformIT.

You can search for print books here on InformIT as well.

Online Resources

This is the link for the SQL Server 2000 sample databases (pubs and Adventureworks).

This is the link for the SQL Server 2005 sample databases (all the AdventureWorks flavors).

This is the link for the SQL Server 2008 sample databases.