Since its inception, Microsoft's SQL Server Business Intelligence (BI) team has been guided by the overriding goal of making business data usable and accessible to as many people as possible. As the team's general manager, Bill Baker works with the people who design and develop BI tools such as Integration Services (formerly data transformation services—DTS), Analysis Services, and Reporting Services. Baker recently talked with SQL Server Magazine about SQL Server 2005's new BI tools and how they work together to streamline delivery of business-critical information.
How are SQL Server 2005's BI enhancements meeting Microsoft's goals for serving the BI community? And how long has your team has been working on these enhancements?
Our goal since we started the SQL Server BI team has been to give as many people as possible in every organization greater insight into their business and the market. We call this "BI for the Masses," and with every version of SQL Server and Microsoft Office, we take further steps to make BI available to every person at every level of a company. For example, in the integration space, SQL Server 2005 Integration Services delivers far greater throughput and more data warehousing and BI functionality out of the box. In addition, customers need to analyze far more data from many more sources and with more immediacy than ever before. In the analysis space, our investments in the Unified Dimensional Model (UDM) and proactive caching move SQL Server 2005 Analysis Services beyond the niche-OLAP market and into the mainstream. Our new Report Builder in SQL Server 2005 Reporting Services opens up report authoring way beyond the Visual Studio audience we support well today. Our vision is about getting the right information, in the right format, to the people who need it—when they need it. Every BI investment we make supports that goal.
Initial planning for SQL Server 2005 started several years ago, but we are now starting to see the fruits of our labor and are definitely in "ship mode." Through our beta releases and Community Technology Previews (CTPs)—advance previews into the upcoming beta—we are receiving incredible customer feedback on our features and implementations.
What kind of feedback have you been getting from beta testers, and which features are they most enthusiastic about?
Our customers tell us they really appreciate how comprehensive our BI solution is. Our solution not only enables seamless integration of components, but it's cost-effective, which is essential. We are getting great feedback on the BI Development Studio—formerly called the BI Workbench—which provides one development environment for Integration Services, Reporting Services, data mining, and Analysis Services. Beta testers have also praised the integration of the BI engines into SQL Server Management Studio—formerly called the SQL Server Workbench—which combines the functionality of Enterprise Manager, Query Analyzer, and Analysis Manager into one integrated tool. Beta testers also appreciated the overall ability SQL Server 2005 gives them to deploy and manage BI applications.
According to news reports, Microsoft and some large customers have deployed SQL Server 2005 Beta 2 in production environments. What is your recommendation for deploying Beta 2 and running it in production? What caveats do you have for businesses eager to move to the new version now?
We're amazed at how many customers ask us to support their Beta 2 implementation in production. Honestly, we don't recommend it since there is no Service Level Agreement (SLA) for Beta 2, but that has not stopped several customers. So far, they are having good experiences, but our recommendation is to get experience with the beta bits, start developing your applications, and plan to roll out your applications with the final version of SQL Server 2005.
How compatible are SQL Server 2000's BI tools (OLAP, DTS, data mining) and SQL Server 2005's new BI tools? Because some of SQL Server 2005's BI tools—such as Integration Services—are completely rewritten, will they still work with SQL Server 2000 data and packages?
This is an area where we need to be very, very clear with our customers because the choice to upgrade or migrate varies depending on the situation. Our commitment is to be transparent about what will upgrade automatically and what will require migration, and we have migration aids for any objects that don't come over automatically.
For example, we will continue to support SQL Server 2000 DTS packages running beside SQL Server 2005 Integration Services. However, if you want to use some of the new SQL Server 2005 Integration Services features or performance, you will need to migrate your packages. We do not automatically migrate DTS packages because they usually contain code, very often in script, and the new SQL Server 2005 Integration Services has newer and better ways to do what that code used to do. In some cases, the benefits of the new technology will be worth rewriting the packages.
SQL Server 2000 Analysis Services supports only clustering and decision-tree data-mining algorithms. Does SQL Server 2005 add support for other algorithms?
Yes. The next version of SQL Server Analysis Services will include five new algorithms in the extensible data-mining solution. We have a great partnership with Microsoft Research that lets us cooperate on new data-mining algorithms, so we've identified the most popular requests and added algorithms for association sets, neural nets, text mining, and other needs. (Editor's Note: For more information about the new data-mining algorithms, see "Data Mining Reloaded," page 21.)
We also made enhancements to data mining, including a set of rich, graphical model editors and viewers in the BI Development Studio. We added support for training and querying data-mining models inside the extraction, transformation, and loading (ETL) pipeline. Developers will benefit from easy integration of data mining into their applications, and analysts will receive finer-grain control over their models. We're excited about these enhancements because they address making data mining and data quality operational.