Data warehouses use timestamps to keep track of data that is changing over time. A common term that is used to describe implementations of historically changing data is slowly changing dimensions. There are several types of slowly changing dimensions, explained in various sources (examples here and here). In this post I will focus on how…
Agile methodologies typically focus on software development. It may appear as if writing code is the only aspect of agile delivery. But we know that most applications use data and this data must be stored somewhere, preferably in a database. This is an integral part of any application. The question then becomes: how do we develop…
Relational databases introduced data modeling concepts where we represent a data model with tables, fields and relationships. A new generation of NoSQL databases which are more suitable for big data environments no longer rely on relational data models. We have to think about data modeling in a different way, primarily to ensure that data is…
In data warehousing and business intelligence implementations we usually start by choosing between two most popular approaches. One of them is the enterprise normalized data warehouse approach as defined by Bill Inmon, the father of data warehousing. The second approach is a collection of dimensional data marts based on a common bus architecture as popularized…