As a company that sits at the intersection of Business and IT, we aspire to turn BI professionals into Hadoop Heroes. We want Big Data leads to have the tools to make Hadoop accessible to Business Analysts in a self-service manner - while guaranteeing scale, speed and security.
And we do so, without changing BI users' habits or retooling the beautiful applications they have already built using tools like Tableau, QlikSense or Microsoft Excel.
We recently came across an amazing article by industry thought leader Meta Brown (she’s the author of numerous articles and books that have helped generations of Business Analysts get more value out of data). We thought we'd share some of the highlights below (primarily our top 3) but please see here the full article.
1) Analysts need detailed raw data. "Never dispose of data without a good reason". In AtScale lingo, we call this: “Never throw away data”
2) Analysts need data that is current, complete, consistent and correct.
3) Analysts need data that is organized appropriately.
In AtScale lingo, we call this: “The value of the semantic layer”. Every analyst, regardless of the tool they use should be able to tap into one consistent and persistent semantic layer.
If you're interested in finding out more about this subject, we also suggest you tune in into this on-demand webinar on the Do’s and Don’ts of BI on Hadoop.
The session details:
- The Gotchas of Big Data: What matters and what's a distraction
- OLAP on Hadoop: The best architectural options (ROLAP, MOLAP, in-memory)
- Data Warehouse Design: the benefits of schema on demand vs. schema on load
Watch it here