Category Archives: Data warehouse

I see a lot of confusion on what exactly is the difference between a data warehouse and a data mart.  The best definition that I have heard of a data warehouse is: “A relational database schema which stores historical data … Continue reading →

What is the best methodology to use when creating a data warehouse?  Well, first off, let’s discuss some of the reasons why you would want to use a data warehouse and not just use your operational system: You need to integrate many different sources … Continue reading →

When building a data warehouse, it is important that primary keys of dimension tables remain stable.  To accomplish this, it is strongly recommended that surrogate keys be created and used for primary keys for all dimension tables instead of using … Continue reading →

If you’ve been working with databases for any length of time, you have heard the term normalization. Normalization is the process of efficiently organizing data in a database.  There are two goals of the normalization process: eliminating redundant data (for … Continue reading →

ETL is the most common method used when transferring data from a source system to a data warehouse.  But there are cases where you might want to use ELT.  What is the difference between the two?  Read on: Extract, Transform, … Continue reading →

Source tables change over time. A data mart or data warehouse that is based on those tables needs to reflect these changes.  This blog post will explain different solutions for solving this problem. When moving data into a data warehouse, taking … Continue reading →