I’m looking forward to giving back to our Nashville SQL Community by presenting at this year’s SQLSaturday event. This is by far one of the best events in Nashville’s tech community and has been a great event for myself and others to attend every year. I can recall the first time I attended SQLSaturday years ago, I learned more in that one day than I had in my entire career. The information was so valuable, and I was immediately able to apply it the projects I was working on. Easy to say that it was worth more than the price of the free admission.

In this session, Applying Data Warehousing Principles: Going from Descriptive to Predictive, I will go into detail on how to effectively model data for a data warehouse using a dimensional model. We’ll highlight dimensional modeling basics such as, facts and dimensions, why this type of model is needed, and compare it to a normalized model you may find in your application database.

Come join me as I uncover different techniques for storing and loading data into dimensions to handle the tracking process of historical data changes. Once we’ve discussed the dimension model, I’ll reveal two ways it provides value back to the business through visualizations.

Throughout the presentation, I’ll have examples to help illustrate the concepts. The examples are derived from datasets available from FreddieMac covering loans and loan performance from 2005 through 2015. We’ll review the ETL (Extract, Transform, Load) steps to create a dimensional model and demonstrate how it can be used to quickly build a PowerBI dashboard. I will also review the source for machine learning applications, and use the new Machine Learning Services feature of SQL Server 2017 to predict if a loan will be delinquent or not.

I hope to see you at the event on January 13th and don’t forget to register HERE!