SAQL simply explained – Part 5

In the last blog of this SAQL series, we saw how powerful SAQL really can be by joining datasets together using the cogroup statement. But we are not stopping there, we can do more powerful stuff. Another way of joining different streams is with the union statement, so in this blog, we will uncover that ...

SAQL simply explained – Part 4

What we have covered so far in the SAQL series have been some basic features, however, it can be a lot more powerful. Let’s say you have two different datasets you want to use for a single query; it could be cases and opportunities for an account. Well, with SAQL we can leverage co-grouping to ...

Einstein Discovery: How good is my model really?

As artificial intelligence, and specifically machine learning, is conquering today’s business world, a new way of human machine interaction enters our professional lives. We are more and more guided by predictive models that prioritise our work and give recommendations to improve our business. Once widely adopted, this embedding of so-called augmented analytics can bring tremendous ...

Einstein Analytics: A robust approach for performing period over period analysis (using a single date picker)

Einstein Analytics dashboard pattern for dynamic Period over Period Analysis using a single date picker. Highlights: * Works with a single standard date widget * Works with absolute dates * Works with relative date bonus Allows switching between \"current period vs. prior period\" (example: Jan-Feb 2019 vs. Nov-Dec 2018) & \"current period vs same period prior year\" (example: Jan-Feb 2019 vs. Jan-Feb 2018)

SAQL simply explained – Part 2

In the first part of this blog series, I explained what is SAQL and the anatomy of SAQL. This will be the foundation for the rest of this series. The SAQL query we covered was simply, in fact, there was no reason to write that query in SAQL, which I also mentioned isn’t recommended for ...