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March 6, 2019

The True Cost of Doing Big Data…the Old Fashioned Way…

Despite the challenges associated with data warehousing, enterprise IT leaders have accepted it as a necessary evil of deriving value from information within Hadoop and other Big Data ecosystems. How much does it cost to create data warehouses or datamarts…

Hadoop: What has changed?!

Every once in awhile, our team gets questions about the validity of Hadoop. Why it exists, why people should consider using it, etc. In the below video, I provide a few examples of cases across common industries like financial services…

Big Data: Hope or Hype?! What the research says…

“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run” - Roy Charles Amara Mr Amara, an American researcher and futurist, probably didn’t anticipate how much wisdom was encapsulated…

March 5, 2019

What’s the best BI tool for Hadoop?

Every once in awhile, the ultimate question comes up: *"What is the best analysis tool for BI on Hadoop?!" * AtScale is not in the business of favoring one tool versus the other. We are in the business of making…

March 4, 2019

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…

Performance on Hadoop, Now!

If your team has been trying to connect your Business Intelligence (BI) tools to your Hadoop environment, you're familiar with the typical issues: performance, security and the inability to model the data in a way that business users like to…

CDOs: They Are Not Who You Think They Are

Google the word “CDO” today and your search will mostly results return articles about the “Chief Digital Officer”. However, if you came to this blog, you’re probably looking for guidance on the other title this acronym refers to: “The Chief…

Big Data: The Unknown Unknowns

Industry leaders know that their challenges with big data analytics are spread across 4 areas: confirmation (‘the things they know they know’); intuition (‘the things they don’t know they know’); inspection (‘the things they know they don’t know’); and revelation…