6 min read
Gartner put on a most delightful Data & Analytics Summit in Grapevine, Texas, the week of March 6, 2017. One could easily call this the Gartner Big Data Summit, but I think Gartner’s approach here – to combine data, analytics, new applications, master data management, open source, and more – reveals the breadth of what organizations are thinking about, planning, and doing with their data. While it’s fresh, I wanted to comment a bit on three tweets that I sent out last week about the show.
Most importantly (in my eyes), these tweets are about conversations I had with customers, prospects, and practitioners – not with analysts or vendors at the show. And please, don’t get me wrong: there were some very stellar presentations from analysts (Hello, Merv Adrian) and vendors alike. These observations are from my time manning the booth, giving my presentation, and conducting meetings with customers and prospects. I look for trends, when I am hearing something from more than one attendee. Or, sometimes, simply that moment where I think, “Huh, I never thought of that.” So, here we go:
Tweet #1 – “We’ve been saving unstructured data for a long time and are now looking to do something with it.”
Ok, this one might fall into the “duh” category. However, stick with me. There were 2 types of people who said this to me:
Tweet #2 – “I want to refresh data for my BI and analytics tools on Hadoop when I want to, not schedule them."”
Multiple customers and prospects approached me with this comment. The gist was as one of them so eloquently put it: “I want to sit there and hit refresh on my BI data on Hadoop all day long.” Makes sense to me, but this is way out of my wheelhouse. Enter my good friend Steve Wooledge, VP of Marketing at Arcadia Data!
Check out the on-demand webinar, "4 Ways to Scale Interactive BI and Analytics on a Data Lake" webinar, scheduled for Wednesday, April 5th at 10am PT/1pm ET. At this webinar, you will learn about four different ways to provide analytics on the data lake. What are the pros and cons of each, such as connecting your existing BI tools to Hadoop-based platforms? What are the best deployment strategies for supporting 100s or 1000s of concurrent users across many business units?
And maybe, just maybe, Steve will tell us all how to refresh BI Data on Hadoop all day long!
Tweet #3 – "Hardware? Nodes? New projects for us start in the cloud."
This discussion was a lot of fun and another eye-opener. A prospect sat in on my presentation on “3 Keys to Digital Transformation” and had some follow-up questions. As we were talking, he was more and more convinced that MapR should be a consideration for him. Then I got the golden question: “How soon can you guys spin up a PoC?” Cool, this is going great, I thought. I mentioned that it depended on a number of factors, like node configuration and hardware availability, but we’d need to get the experts out on-site and get the marketing dude (me) out of the way. His priceless response:
“Pfffffft, Hardware? Nodes? New projects for us start in the cloud.” He gave me a bit of this look, too:
Like the comment above on wanting unstructured data on the cloud and structured data on-premises, I think the maturity of this market is leading to strong opinions. This is good. Strong opinions show that big data solutions are being planned for and used in production. Strong opinions on intentions make vendors react. Keep them coming, folks.
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