In Winter 19 I did a two-part blog series on the (at that time) new SAQL timeseries statement. Yesterday I got an email requesting a 3rd part to the blog series looking at what you can do with timeseries directly in the UI, since this has been enabled after the original blogs were written. I ...
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 ...
When we create dashboards in Einstein Analytics most of us rely on the UI. In the dashboard editor, we click “New Step” select our dataset, define the measure and a grouping whereafter we add it to the dashboard. In other words, with point and click, we can create a great dashboard that gives insight into the data. ...
June has approached in fact we are almost midway through June, which means it’s officially Summer. And since I have crossed the “pond” and gone to Austin Texas, I cannot help but think “Wow, this is hot” and so it the Einstein Analytics Summer19 release. Some production environments have already been updated this past weekend ...
Sometimes you have a really great idea for a chart. You know exactly what you want, you have the calculations ready only to realize that the specific chart in mind does not 100% support what you want to do. It’s a typical use case that pops up on a regular basis. A few weeks ago ...
In the past 8 blogs of this blog series, we have covered a lot of ground. We started out looking at the anatomy of a binding followed by data serialization examples and finally data manipulation. In this blog, there will not be an introduction to a new concept. While writing these blogs I have completed ...
This blog series has almost come to an end. From part 1 of this blog series I have tried to demystify the binding syntax and come with different examples of how to use data selection and data serialization, and I hope bindings have become a little more approachable than before. But there is another layer ...
When we build dashboards and show the dashboard to end users they have an expectation to see data in a table view. Maybe not in the beginning, but for the most part they do want to be able to see the details. In Einstein Analytics we do this by adding a values table. But how ...
Maps are great on a dashboard. Why? Well, the brain can easily decode a map as all the data is visual, no text is needed to understand the data story. This is why I think maps should be used in Einstein Analytics. You probably already know that Einstein Analytics comes with some out of the ...