March 4, 2019

Three Trends From Dataworks Summit 2018

We did it again! The AtScale team was present at the Dataworks Summit 2018 in San Jose, California. We hope you had the opportunity to attend some, if not all, of the great sessions that we suggested. If you missed…

Posted by: Lucio Daza

Three Important Questions to ask about Chief Data Officers

Disruptive technologies inevitably lead to the emergence of new job functions across all levels of an enterprise. The emergence of cloud computing is no different. Companies are positioning themselves to take advantage of the benefits cloud computing provides and with…

Posted by: Dan Schulwolf

The Ultimate Big Data Architecture Checklist

The joy of working as a Customer Success Solution Architect is that I have the opportunity to work with many different customers and each challenges us with a different Big Data use case. I've worked with enterprises that offload their…

Posted by: Rudy Widjaja

The Hidden Costs of Self-Service BI Initiatives

While it may be tempting to focus our efforts only on self-service BI in terms of security and access control mechanisms, it is important to also place emphasis on economies to achieve success. When an enterprise develops a self-service BI…

Posted by: Javier Guillen

The Future of Tech: Cloud, AI and your budget…

If you're a sucker for great market data like I am, you must have heard of Mary Meeker. Mary is partner at Kleiner Perkins Caufield & Byers. She's known in the Valley as a specialist in digital businesses and has…

Posted by: Bruno Aziza

The 1990’s called, they want their OLAP back.

In 1992, Arbor Software shipped the first version of Essbase. Which stands for Extended Spreadsheet Database. In 1998, Microsoft shipped Microsoft SQL Server Analysis Services. The time of multi-’dimensional’ databases had come into full being and almost 30 years later…

Posted by: Mike Haynes

TECH TALK: Scale-Out Business Intelligence with Hadoop

The growing popularity of big data analytics coupled with the adoption of technologies like Spark and Hadoop have allowed enterprises to collect an ever increasing amount of data - in terms of breadth and volume. At the same time, the…

Posted by: Joshua Klahr