Kimball University: Eight Guidelines for Low-Risk Enterprise Data Warehousing - InformationWeek
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Kimball University: Eight Guidelines for Low-Risk Enterprise Data Warehousing

New data sources and BI delivery modes make it that much harder for EDW initiatives to succeed. Here are eight recommendations for controlling project costs and reducing risks.

In today's economic climate, business intelligence (BI) faces two powerful and conflicting pressures. On the one hand, business users want more focused insight from their BI tools into customer satisfaction and profitability. Conversely, these same users are under huge pressure to control costs and reduce risks. The explosion of new data sources and new delivery modes available for BI really makes this dilemma acute.

How can we fail?

We could do nothing, thereby overlooking important customer insights and specific areas where we could be more profitable. We could start a task force to produce a grand architectural specification covering the next five years, which is just another way of doing nothing. We could implement several high-priority spot solutions, ignoring overall enterprise integration. We could start by buying a big piece of iron, believing that it is so powerful that it will handle any type of data, once we decide what that data is.

You get the idea. Even though some of these ways to fail seem obviously dumb, we can nevertheless find ourselves in these positions when we respond with a crisis mentality.

How can we succeed? How can we move forward quickly and decisively while at the same time clamping down on risk? EDW development is never easy, but this article presents eight guidelines for approaching this intimidating task in a flexible, reasonably low-risk way.

Work on the Right Thing

We recommend a simple technique for deciding what the right thing is. Make a list of all your potential EDW/BI projects and place them on a simple 2x2 grid, like the one at right.

Figure out, with your end users, how valuable each of the potential projects would be, independent of the feasibility. Next, do an honest assessment of whether each project has high-quality data and how difficult it will be to build the data delivery pipelines from the source to the BI tool. Remember that at least 70 percent of BI project risks and delays come from problems with the data sources and meeting data delivery freshness (latency) requirements.

Once projects have been placed on the grid, work from the upper right corner. Project A shown above has high business impact and is eminently feasible. Don't take the easy way out and start with low-risk project D. That project may be feasible, but even if you do a great job, it won't have much impact. Similarly, don't start with project C. The users would love to have it, but there are big feasibility issues which translate into big risks.

Give Business Users Control

A few years ago, data warehousing was relabeled as "business intelligence." This relabeling was far more than a marketing tactic because it correctly signaled the transfer of the initiative and ownership of the data assets to the business users. Everyone knows instinctively that they can do a better job if they can see the right data. Our job in IT is to sort through all the technology in order to give the users what they want.

The transfer of control means having users directly involved with, and responsible for, each EDW/BI project. Obviously these users have to learn how to work with IT so as to make reasonable demands. The impact-feasibility grid shown above is not a bad place to start.

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