Month: Apr 2017

Posted on

Prepare data: football-data.co.uk (part 1)

In the post Gather data: football-data.co.uk I described, how you can load CSV data into the Exasol database. As the data is now available at the Stage Layer in the database, I must now prepare the data and persist it at the Raw Data Layer, so that I can easily use it for building predictive models.

With part 1 of this post I want to explain, what Data Vault modeling is and how the Data Vault model for the data structure of football-data.co.uk looks like. With part 2 I will explain, how you load data into the developed Data Vault model.

Continue reading “Prepare data: football-data.co.uk (part 1)”

Posted on

Gather data: football-data.co.uk

When I started this project, my biggest problem was to find a source for historic football statistics and historic football odds. Fortunately, I found Joseph Buchdahl’s website football-data.co.uk. This website is just great! He offers CSV files for 22 football leagues and about 19 seasons. He updates the data mostly two times a week. So I used this data as the starting point for my analytical system.

Continue reading “Gather data: football-data.co.uk”

Posted on

Analytical Architecture: TripleA DWH

As described in How to beat the bookie: Value Betting I want to use Value Betting to beat the bookie. To identify value, I have to be able to calculate the probability of a specific sports event (e.g. Home-Win for Team A) as accurately as possible. Therefor, I have to develop, test, simulate and process different predictive models.  As a DWH architect I know, that a good data architecture helps a lot to support such a developing process. That’s why I formed the concept of the TripleA DWH – the Advanced Agile Analytical Data Warehouse – a data architecture aimed to automate data science processes.

Continue reading “Analytical Architecture: TripleA DWH”