Data-Warehouse/Mart

This is one of the larger sections in this knowledge-base. It covers on how you extract the information from various sources , put it all together, link it, clean it, transform it and then load it in a place and form so that one can fulfill all the Data & Information requirements of an organization. Data Warehousing can also be named as "offline Integration" of data. This section talks about a full-fledge Data Warehouse Initiative. However can start small, while keeping in mind the long term road-map.


Chapters In Data-Warehouse/Mart : -

Data Warehouse Overview

This chapter is setting the scene. It provides the end to end high level landscape of Data Warehouse. Much of this chapter talks on how Data Warehouse is different from Transaction systems, and what are we in for. Lets Look at What & why of Data Warehouse, its components & framework and what are the challenges for a typical DW project.\n

DW Project Scoping and Planning

This phase is similar to any other project only till the basic principles. The workings and engagements of the project team is fairly different. DW projects fail when we try to apply conventional methods. Look at the journey which starts from finding a sponsor and ends with signing Project Agreement. \n

DW Business Requirement Phase

Its time to get into details on the business requirements. Business requirements are less to do with detailing of business objectives, information needed and scorecards & dashboards. This phase is tough as it forces a clarity on business thinking.

DW Dimensional Modeling Concepts

Dimensional modeling is essentially a logical modeling of business requirements. It is different from data modeling. Lets look at what's dimensional modeling, why is it different?, why is it needed to be different?, what are special situations and how do we deal with them?.\n\n

DW Testing and Implementation

Like some other aspects, Data warehouse testing is fairly different from a transaction processing system. The amount of data and possible test scenarios can run into huge sets. The trick is to find a right balance.

DW Maintenance Enhancement

Challenges are two ways. If user gets engaged, the expectations rise, and any failure to provide adequate performance levels or to add enhancements lead to rejections. On the other hand, user may also be resistant to come out of routine reporting & analysis methods. This chapter look at the addressal of these challenges.

Data Warehouse Project Plan- Work Break-Down Structure

We have covered many diverse topics in Data Warehouse Section. This chapter is dedicated to bring them all into a list and sequence of activities that you will do to make a data warehouse project happen. We have covered different data warehouse topics at various stages. This chapter puts them all together in an integrated fashion. Though most of the activities here are linked to the data warehouse, may of them are linked to the overall BI including OLAP and end-user tools. One has to note that Data Warehouse initiative is not implemented alone. It is always associated with the implementation of the end-user tools (like query tools, data mining tools, reporting tools...). We will have one topic page assigned to each major phase of a Data Warehouse project.