Enterprise Data Science
Strata Data Conference Grows Up
Jun 09, 2017By Peter Wang
The Strata conference will always hold a place in my heart, as it’s one of the events that inspired Travis and I to found Anaconda. We listened to open source-driven talks about data lakes and low-cost storage and knew there would be a demand for tools to help organizations and data scientists derive value from these mountains of information.
So, as a longtime Strata attendee, it’s really been amazing to see how quickly the event has evolved. What began as the merger of O'Reilly and Cloudera’s big data conferences just five years ago has morphed from a stuffed elephant, Hadoop-centric show to an event that showcases some of the most advanced applications of artificial intelligence and machine learning.
While it appeared that foot traffic seemed a little lighter than previous shows, sources tell us that attendance was up. This, of course, got me thinking about what companies attended and which were noticeably absent. The biggest booths were occupied by traditional IT platform infrastructure companies like new Anaconda partner Microsoft, Intel, IBM and Google, which really highlights the maturation of the event.
Among the previous mainstays not presenting at this year’s conference were the more traditional database vendors, like Teradata. Where were the database players? My theory centers around the fact that these vendors can now serve artificial intelligence and machine learning demands from their existing SQL database products, making it less critical to put all of their surfers behind the Apache big data wave.
As the narrative around the commercialization of Hadoop centering on the data lake plays out, people seem to be asking “what is the value of all of this data being centralized?” This curiosity may have helped attendance levels for my “Data Science Beyond the Sandbox” presentation, where a collective sigh seem to fall over the room as everyone realized that they're all facing the same struggles around lifecycle management of data science models and getting them into production environments.
Overall, it was great to see the interest in Anaconda Enterprise and I’m still a little (pleasantly) surprised at the broad awareness of Anaconda in general. Everyone that came to the booth and that I spoke with was familiar with Anaconda and how it helps move Python data science projects into production environments. I even mentioned to one of my colleagues halfway through the event that I hadn’t yet had to explain what Anaconda was or does to anyone.
It’s exciting to see Strata continue to evolve into a more data insights focused event, highlighting computations, machine learning and AI.