DATA WAREHOUSES AND DATA MARTS

DATA WAREHOUSES AND DATA MARTS
If you have been following the literature on data warehouses for the past few years. you would, no doubt, have come across the terms "data warehouse" and "data mart." Many who are new to this paradigm are confused about these terms. Some authors and vendors use the two terms synonymously. Some make distinctions that are not clear enough. At this point, it would be worthwhile for us to examine these two terms and take our position.

Writing in a leading trade Magazine in 1.998, Rill button stated. "The single most important issue lacing the IT manager this year is whether to build the data warehouse first or the data mart first." This statement is true even today. Let us examine this statement and take a stand.

THREE DATA LEVELS IN A BANKING DATA WAREHOUSE 

Data granularity refers to the level of detail. Depending on the requirements, multiple levels of detail may be present. Many data warehouses have at least dual levels of granularity.

Figure 2-4 Data granularity.

Before deciding to build a data warehouse for your organization, you need to ask the following basic and fundamental questions and address the relevant issues:

• Top-down or bottom-up approach'?
• Enterprise-wide or departmental'?
• Which first, ----data warehouse or data mart?
• Build pilot or go with a full-fledged implemental ion?
• Dependent or independent data marts?

These are critical issues requiring careful examination and planning. Should you look at the big picture of your organization, take a top-down approach, and build a mammoth data warehouse'? Or, should you adopt a bottom-up approach, look at the individual local and departmental requirements, and build bite-size departmental data marts?

Should y01,1 build a large data warehouse and then let that repository feed data into lo-cal. departmental data marts'? On the other hand, should you build individual local data marts, and combine them to form your overall data warehouse? Should these local data tunits bc independent of one another? Or, should they be dependent on the overall data warehouse for data feed? Should you build a pilot data mart'? These arc crucial questions.