This year’s Magic Quadrant for Data Science and Machine Learning Platforms scored six Data Science and Machine Learning (DSML) Platforms as leaders. The amount of leaders has remained the same, compared to last year’s number of leaders. But has the composition of the leading area changed?
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In my eight years as a consultant, I’ve probably seen more dashboards than I can count. Still, most of them don’t have the impact they should have. Nine out of ten times, people start looking at the data. Is there something wrong with the underlying data-sets? Or is the visual not clear enough? Looking at those elements isn’t bad, but in my opinion, you’re looking in the wrong direction.
The Gartner Magic Quadrant for Business Intelligence is a piece of analyst reporting we look forward to every year. Both the dept and the scope of this research makes it worth the read. But not many people take the time to really dig into the details of the report.
Keeping your skills up to date is crucial when you work with the newest technology. At Rockfeather, we challenge each other to be the best version of yourself. That’s why I attended the mastering DAX course. DAX (Data Analysis Expressions) is a formula expression language. Next to Power BI, DAX is applied in Excel Power Pivot and tabular models in SQL Server. Learn it once, use it tomorrow.
Every year Tableau invites its most valuable partners to kick off the new year together. The theme for this year was Accelerate, so let’s get right to the point. This exciting event was focused on three main areas.
In this interview, Jonathan Aardema talks with Prof. Eric Postma (professor of Cognitive Science and Artificial Intelligence at the University of Tilburg) about the why, how, and what of artificial intelligence applications. What do we see in practice, and what does science say about it?
Creating sustainable businesses is definitely one of the biggest challenges for big corporations. The ‘why’ in this story is clear as daylight, it is the ‘how’ and ‘what’ that is nagging them.