There is so much confusion on how to model decision-making data for analysis. The number of products and tools the average company uses to store data has exploded. The database vendors are competing and releasing features at an astounding rate. One vendor says one thing while another vendor says another thing. The cloud vendors have also accelerated the pace of change. Do we still need a star schema? Do we create aggregate tables? How do we handle temporal data? How should we create slowly changing dimensions? These things are creating a confusing atmosphere for the data modeler.

It is true that data modeling has changed, but there is no need to throw out great practices that have served us for years and can continue to do so. This session will cover what has changed for data modeling, why it changed, and how to take advantage of those changes. Combine new thinking with classic data architecture and you will create great analytic and transactional systems for your data.