By Michael L. Gonzales
- Reviews making plans and designing structure and enforcing the information warehouse.
- Includes discussions on how and why to use IBM tools.
- Offers guidance, tips, and workarounds to make sure greatest performance.
- Companion website comprises technical notes, product updates, corrections, and hyperlinks to suitable fabric and training.
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Extra info for IBM data warehousing : with IBM business intelligence tools
Instead, we will concentrate on core aspects of any ROI, or other value propositions that you must consider. Applying ROI Aside from the issue of soft versus hard benefits associated with BI efforts, there are other problems to consider when applying ROI. For example: Attributing too much savings to DW efforts that would come anyway. Let’s say your company was moving from a mainframe architecture to a distributed UNIX environment. Then any savings that may (or may not) be realized by that effort should not be attributed solely, if at all, to the warehouse.
Data marts. This part of the architecture represents data structures used specifically for OLAP. The presence of data marts, whether the data is stored in star schemas that superimpose multidimensional data in a relational environment or in proprietary data files used by specific OLAP technology, such as DB2 OLAP Server, is not relevant. The only constraint is that the architecture facilitates the use of multidimensional data. The architecture also incorporates critical technologies and techniques that are distinctively BI-centric, such as: Spatial analysis.
Will data mining models be a necessary part of your future? Who knows? It is important to note that these types of technologies are less widely known to general user communities and warehouse team members. In part, this may be because they are typically left to a few in-house technical geeks or outside third parties. It is the limited exposure of these types of technologies that creates the problems. Consider the impact. If users cannot describe the business requirement or frame it in such a way as to provide clues to planners, it may go unnoticed or, worse, simply ignored.
IBM data warehousing : with IBM business intelligence tools by Michael L. Gonzales