AtScale Blog

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 been credited with having a deep understanding of what makes businesses succeed and fail.   Earlier today, she released the 2018 version of her internet trend reports: 294 slides delivered in 30 minutes on the Code Conference stage.  You might not have caught everything.   Here are our highlights.

“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 in just a few words.  Buying technology is hard. And Enterprise IT buyers are often left with the hard task of determining if the new piece of technology they just heard about is pure hype or if it has hope.  Where are they to find consistent guidance?

Yesterday, Gartner published the 2018 Magic Quadrant for Business Intelligence.  The MQ research for BI has been in existence for close to a decade. It is THE document of reference for buyers of Business Intelligence technology.

At face value, not much seems to have changed...BUT, if you take a closer look, you'll notice that some of the biggest changes in the history of the Magic Quadrant just occurred....

Every year, many of you reach out to thank us for our analysis of Gartner's famous Magic Quadrant for Business Intelligence.  Thank you all for your feedback! 

This year,  we've decided to go one step further: in addition to our written analysis, we will be sharing our perspective as part of our upcoming "BI on The Data Lake Checklist" webinar.

Be sure to register here: the Gartner Magic Quadrant for Business Intelligence (BI) 2018 is bound to surprise you and our analysis will help you navigate its subtleties...

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 that extract data out of Hadoop? Is there a better way to do BI on Big Data?!

Industry leaders know that their challenges with 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 (‘the things they don’t know they don’t know). 

This last category is often the most tragic for organizations.  Luckily, we now have helpful resources from Tom Davenport's latest webinar on Data Strategy to key research data points on chief data executive's priorities.

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 all of them work.  There are indeed many reasons why business users and IT departments choose particular analysis tools.   Here are a few things to consider. 

Yesterday, Gartner published the 2017 Magic Quadrant for Business Intelligence.  The MQ research for BI has been in existence for close to a decade; it is THE document of reference for buyers of Business Intelligence technology.

Yesterday, Gartner published the 2016 Magic Quadrant for Business Intelligence.  The MQ research for BI has been in existence for close to a decade. It is THE document of reference for buyers of Business Intelligence technology.