This week, we learned about data warehousing and business intelligence systems (DW/BI) from the Data Warehouse Toolkit by Kimball, Ralph, and Margy Ross. These systems consider the needs of the business and then design the system with technology in mind. In organizations, record keeping and analytical decision making are important. The performance of the business can be analyzed with these tools. The information should be easily accessible and comprehensible to the business user and not in developer jargon. It should be simple and fast for the user. The system should be labeled consistently or if they measure different things, labeled differently. The system should adapt to change and protected.
A DW/BI manager should understand their user's job responsibilities, goals, and objectives. They should know who the best users are and find new users. They should give useful information to their users that can be trusted and is accurate. The system they make should be reliable, trustworthy, updated, and keep everyone happy.
Dimensional modeling is the preferred technique for presenting data that is understandable to the user and fast. These are often in the third normal form (3NF) which are free of redundancies. They are often called entity-relationship diagrams (ERD or ER diagrams) who describe the relationship between tables.
Star Schemas are dimensional models in relational database management systems. If they are multidimensional database environments, they are online analytical processing cubes (OLAP) where data is stored and indexed like performance aggregations or summary tables. They give better query performance because they are optimized and have more functions than SQL but require more computation. OLAP cubes have good security options, richer analysis, support type 2 changes, support fact tables, and ragged hierarchies.
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