Data Sources and Business Intelligence Tools for Data Warehouse Deluxe - dummies

Data Sources and Business Intelligence Tools for Data Warehouse Deluxe

By Thomas C. Hammergren

You won’t be lucky enough to find any single-source environments when you’re building a data warehouse deluxe. Now, you have a whole new set of problems that you must deal with, including the ones in this list:

  • Different encodings for similar information: Different sets of customer numbers come from different sources, for example.

  • Data integrity problems across multiple sources: The information in one source is different from the information in another when they should be the same.

  • Different source platforms: As an example, an IBM mainframe that has DB2/MVS databases might contain the data in one of the sources, another IBM mainframe that has VSAM files might have another set of source data, a set of servers might contain data within Oracle databases, and the rest of the source data might all be stored in SQL Server databases on Windows servers.

Although the exact number of data sources depends on the specifics of your implementation, data warehouse deluxes tend to have an average of eight to ten applications and external databases that provide data to the warehouse.

The broad range of subject areas and the wealth of data in a data warehouse deluxe means that you usually have several different ways of looking at that warehouse’s contents. This list shows the different ways that you can use a data warehouse:

  • Simple reporting and querying: Like with data warehouse lite, the purpose of the warehouse deluxe is to “Tell me what happened.”

  • Business analysis: You use the warehouse to “Tell me what happened — and why.”

  • Dashboards and scorecards: In this model, a variety of information is gathered from the data warehouse and that information is made available to users who don’t want to mess around with the data warehouse — they want to see snapshots of many different things. Its purpose is to “Tell me a lot of things, but don’t make me work too hard to get the answers I want.”

  • Data mining or statistical analysis: In this area, statistical, artificial intelligence, and related techniques are used to mine through large volumes of data and provide knowledge without users even having to ask specific questions. Its purpose is to “Tell me something interesting, even though I don’t know what questions to ask, and also tell me what might happen.”

You’re likely to employ at least three — and perhaps all four — of these types of data warehouse user-access techniques when you use a data warehouse deluxe. Although tool vendors increasingly try to provide suites of products to handle as many of these different functions as possible, you do have to deal with different products — and so does your user community.

Don’t assume that you can simply select a single vendor whose products satisfy all the business intelligence capabilities your users need. Make sure that you carefully check out the vendors’ products — all of them — because you have no guarantee that a top-notch OLAP vendor’s data mining tool is equally as good, for example.

Don’t be afraid to mix and match; you have no reason to shortchange your data warehouse’s users simply to avoid having to deal with one more vendor.

When evaluating your user access needs, ask yourself the following questions:

  • Do my users want the best-of-breed tools, which might not necessarily be integrated, requiring professional developers to build visualization solutions?

  • Do my users want a well-integrated platform that enables integration between user-access strategies so that they can develop all visualization solutions themselves?

Answers to these questions (and if you answer “Yes” to one of them, you answer “No” to the other) can help you evaluate the business intelligence tools.