Archive for Analytics category

Paige Roberts presenting to full room with Zynga case study slide showing

DBTA Data Summit – The Rise of DataOps

The recent DBTA Data Summit provided a lot to think about. I did a short talk in the “Analytics in Action” track about how data analysts, architects and engineers can turn the endless waves of disruption we keep getting hit with into opportunities to boost bottom line. There were some very cool talks by other folks as well. For me, the highlights of the conference were Michael Stonebraker’s keynote, and the Data Kitchen folks diving into the principles of DataOps.

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Davin Potts, CEO Appliomics, Founder KNIME, Core Python Commiter

One on One with Davin Potts

At the recent Data Day Texas event, I sat down with Davin Potts, who I have known for many years, and had a long conversation about a wide variety of subjects. Over on the Vertica blog, I broke the conversation into chunks, but I wanted to put it all together in one place so you can see what we chatted about end to end. So, here’s all of it, from machine learning to open source, from Python to Knime, and why the heck DO we move data out of a database to analyze it?

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Metron Eye On Cyber Security

Cyber Security with Apache Metron and Storm

A few weeks ago at Hadoop Summit, I caught up with some friends from the project I worked on last year with Hortonworks, including Ryan Merriman who is now an Apache Metron architect. Since Apache Metron was a project I knew virtually nothing about beforehand, I quizzed Ryan about it. The conversation evolved into a discussion of the merits of Storm versus Flink and Heron, something I’ve been meaning to delve into for months here.

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Big Data Analytics Miss

Four Reasons Why Big Data Analytics Projects Fail, Or Do They?

A few months back, I was presenting with a friend at a Chief Data Officer summit in Dallas, and my co-presenter put up a slide that said, “60 % of all big data analytics projects fail.” Someone in the audience asked, “Why do they fail?” My friend said, “I think Paige could answer that better than I could.”

Put on the spot, three reasons that have been confirmed from multiple sources jumped immediately into my head. I used those three to answer the question. But later, when I had time to think, I realized there was one other reason that shows up repeatedly, but often gets downplayed or written off as not the REAL problem, when in my opinion, it very much is.

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Pancakes in Space

NASA, Star Trek, Pancakes and IBM Watson

I spent the weekend before last doing the NASA SpaceApps Challenge, and for the second year in a row, my team won the local competition with a combination of seemingly trivial geeky knowledge and twisted thinking. Our challenge: To boldly make pancakes where no pancakes have ever been made before. More precisely, we answered the challenge, Print Your Own Space Food. Here’s a quote from the challenge description:

Think Food Replicators, from an early sci-fi show. Investigate the benefits and feasibility of allowing astronauts to print their own food on the International Space Station or other space facility. What would it look like? What will it be made of? How will it be possible? Create a recipe for a 3D printed meal.

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