Our journey in Sports Data Analytics started back in 2015 and what a ride it has been! Back in 2015, in the offices of Aspire Academy, we were invited to brainstorm on a performance platform that could serve professional football on one side and individual sports on the other. Thanks to the trust of Aspire Academy an amazing project was brought to life, a new experience for the Clariba team was initiated and my personal journey in sports performance analytics began!

Sometimes, the client has to make modular structures to satisfy the needs of each department separately, but when the necessity for mixed information between departments appears, joining such modules is a requirement. The response to this problem is Linked Universes.

SAP Analytics Cloud is just for Analytics. This is how we usually misunderstand the true potential of SAP Analytics Cloud. In this post, we explain key features that SAP Analytics Cloud provides for successfully planning, budgeting and analyzing data. This blog comes from our expertise working in different scenarios we have satisfactorily developed for our customers.

Some tools can be more productive than others. Throughout our experience in implementing an optimal machine-learning pipeline in production, we have learned to appreciate the raw strength of the combination of SAP HANA with SAP Data Services. The amount of time that can be saved by reformulating the approach and optimizing it to use this combination is significant, compared to a vanilla approach involving usage of Python for data wrangling, cleaning, discovery, and normalization, which are significant aspects of machine learning pipeline development.