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Open-Source Data Management Dives Into Artificial Intelligence

Bethann Noble
Bethann Noble, Portfolio Marketing Manager, IBM Cognitive Systems - Photo by Matt Carr

The start of summer never fails to excite: ditching hot coffee or tea in favor of iced, trading sneakers for flip-flops, and taking the first plunge in the pool. Summer got off to an equally exciting start for IBM Power Systems* at three key events in the open-source database (OSDB) and big data communities. Heading in, I was eager to see to what extent “AI fever” would be taking hold in these communities. I had a hunch, and was not disappointed: The artificial intelligence (AI) waters were warm, and everyone was diving right in.

First stop was DataWorks Summit/Hadoop Summit. There, IBM and Hortonworks announced an expanded partnership to deliver the only fully open and integrated data science platform on the market: IBM’s Data Science Experience and Big SQL solutions for Hortonworks Data Platform, the open-source Apache Hadoop distribution IBM will in turn provide for its clients, phasing out IBM BigInsights (ibm.co/2tiUD1V).

That’s great news for data scientists and engineers. IBM’s Data Science Experience helps take the drudgery out of data cleanup and transformation, and Hortonworks support for IBM Power Systems means data scientists can seamlessly tap into GPU-accelerated deep learning training at scale with IBM’s PowerAI solution. Hundreds of DataWorks attendees visited the IBM booth and our meetup to learn more, and we also awarded our inaugural Cognitive Honors distinction to a Hortonworks Data Hero (ibm.co/2tNqpUY).

After that, we were off to MongoDB World, the largest annual community gathering for the fastest growing OSDB. Here too, the crowd was ready to learn how to do more and know more with unstructured data. After that, we were off to MongoDB World, the largest annual community gathering for the fastest growing OSDB. Here too, the crowd was ready to learn how to do more and know more with unstructured data. IBM Research Fellow Saśka Mojsilović inspired a packed keynote audience with a presentation on leveraging data science for social good (ibm.co/2vPbVGx ), and IBM’s breakout session on PyMongo drew a standing room-only crowd of developers who came away with practical examples and a recipe to deploy machine learning analytics on data stored in MongoDB.

Next stop: the second annual Postgres Vision conference. It became clear that a race to digital transformation doesn’t end with OSDBs. Rather, adopting open-source data management solutions such as PostgreSQL is a key step. Engaging keynote presentations from EnterpriseDB CEO Ed Boyajian and IBM Vice President Paul Zikopoulos contrasted the costs incurred by market laggards with the competitive advantages of market leaders.

On the second day, the keynote wrapped up with data scientist Hilary Mason, founder of enterprise AI consulting firm Fast Forward Labs (hilarymason.com). Following advice for success with machine learning in the enterprise, Mason emphasized the value of open-source technology and community values.

As businesses look to get started with applications of machine learning, one key to success will be building and acquiring specialized skill sets in data science and engineering. Based on the enthusiasm for learning and applying machine learning found at these events, organizations need not look farther than the open-source data management and big data communities to find an ideal pool of talent, already filled with the data scientists, engineers and developers who are diving into the journey to AI.

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