I love the Strata + Hadoop World Conference (renamed Strata Data Conference) and once again the 2017 conference did not fail me in anyway. I wanted to take this opportunity to give you a quick recap since I had the privilege of attending.
I love how the keynotes are short and impactful. Wednesday delivered great insight from a conversation with Beau Cronin and Phil Keslin, CTO and Founder of Niantic. Another great session was from Rajiv Maheswaran from Second Spectrum. Niantic created Pokeman Go and some of the great insight that Phil brought was how they started with a strong architecture that they knew would scale. They had no idea that it would need to scale so fast or so soon. Although there were sleepless nights, they were prepared and able to solve both the compute and big data problems they encountered immediately. Rajiv’s topic was “When machines understand sports” and it was great to see how they were able to track the movement of the ball and players and how they could transform the data into facts about players, strategies and probabilities as well as changing the overall game. We watch a great deal of basketball, especially now with the NCAA Men and Women’s Championships going on, and to see data analytics applied to the game like never before is really cool. Is there anything that data analytics can’t impact?
On Thursday we got to see many of the good things that data analytics can help to achieve. For instance, Desiree Matel-Anderson from the Field Innovation Team talked about “Data in disasters: Saving lives and innovating in real time”. Desiree talked about hurricane Sandy and the Boston Marathon bombing as well as other recent events. She talked about how we can use social media and data analytics to determine the impact of the event and how they make it easier to better follow or respond to events in the future. For instance, looking at social media, they saw that people were tweeting for “help” after Sandy hit the coast, electricity was gone and the hurricane had subsided. There was no panic occurring during the storm hitting the land. These facts can help agencies like FEMA in future hurricanes help people feel more connected and can respond to them faster and with this historical data. Another great session was Maya Shankar who worked for the White House Office of Science and Technology Policy under President Barack Obama. She spoke about “Improving Public Policy with Behavioral Insights” and provided us with four conclusions as to the how those insights can guide next steps…
1) convert interest into impact
2) quantify impact
3) celebrate small-wins
4) generate organic buy-in
These conclusions are based on many years of work and delivered as proof to Washington DC insiders that “data tells you what people are doing” and “behavioral science tells you why.”
The rest of the day was filled with expo time and some great technical sessions. The majority of the topics for the conference focused on real-time machine learning and Artificial Intelligence (AI). In one presentation, Rob Craft from Google explained machine learning best… he said, machine learning is “one branch of the field of AI”, “a way of solving problems without explicitly codifying the solution”, and, last but not least, “a way of building systems that improve themselves over time.” Machine learning and AI are clearly the future with regard to data analytics and a great reason why they changed the name of the conference to Strata Data Conference. Don’t get me wrong… Apache Hadoop, Spark, Impala, Flink, Kafka, Beam, Apex, Kudo, etc are still being talked about. Data analytics means a lot of things to people and it varies in multiple aspects, but one thing that remains the same is the fact that data analytics drives change and impact. Whether it is changing our nation’s policies or making better video games, we were all at Strata + Hadoop World to learn more and use that information to make a difference. That’s why I love Strata + Hadoop World. So much to learn, so many people to learn from, and realizing that for once, our jobs are making an impact and what is better than that?
Source: Dell EMC Big data blog post