10 Key Takeaways about the Future of Big Data from Data Summit 2016

By Joyce Wells

May 23, 2016

Held earlier in May in New York City, Data Summit 2016 provided attendees with the opportunity to learn more about strategies for succeeding in an increasingly data-driven world.

The event drew IT managers, data architects, application developers, data analysts, project managers, and business managers to hear industry-leading professionals deliver educational presentations on industry trends and technologies, networks with peers, and participate in hands-on workshops.

Here are 10 key takeaways from sessions at Data Summit 2016:

The future of IoT interoperability: To enable interoperability in IoT, the future will be 100% API-based. – Joe Caserta, president and CEO of Caserta Concepts.
Why Spark matters for predictive analytics: Apache Spark with its real-time in-memory processing capability and built in redundancy / fault tolerance of the executor nodes, forms an ideal platform to build predictive data analytics platforms. - Abhik Roy, database engineer, Experian
Make sure you read the fine print in cloud service agreements to know what the public cloud provider is responsible and what you are responsible for – it may not be what you think. – Michael J Corey, president, Ntirety – A HOSTING Company, and Don Sullivan, system engineer database specialist, VMware
Leveraging IoT data for marketing requires care: Companies will need to ensure that IoT-based offers and interactions with customers are in keeping with their brands – George Corugedo, CTO of RedPoint Global
The value of Apache Drill: As the data volumes and data sources go up, the time to analytics also increase while profits go down. Apache Drill is a relatively new tool that can help solve this difficult problem by allowing analysts and data scientists to query disparate datasets in-place using standard ANSI SQL without rebuilding their entire data infrastructure. – Jair Aguirre, lead data scientist at Booz Allen Hamilton
Relational is not going away: NoSQL does not replace relational. It augments it. Also - we will increasingly see database management platforms that offer the ability to plug in a choice of engines, such as a graph engine or document engine for different use cases - Craig S. Mullins, principal of Mullins Consulting
Time to learn about NoSQL and other big data technologies is now: For example, anyone who is not yet familiar with Oracle Database 12c R2 should know that they "are going to see a deeper and broader connection to the big data products and to NoSQL." Better to learn about it now than to have to try to get up to speed after you have got 12c R2 in your shop - Charles Pack, technical director, CSX Technology
Data platform essentials: There are three key areas to focus on when building a stable platform to support current data architecture: persistence, context, and access - John O’Brien, principal analyst and CEO, at Radiant Advisors
The new Y2K problem: January 1, 2000 threatened widespread havoc for computer systems, but ultimately turned out to be manageable. Now, there’s a new Y2K-type bug (aka, the UNIX Millenium Bug), which is feared to cause problems for 32-bit UNIX-type systems on January 19, 2038. It seems long time from now but there are people already working on it. - Tassos Sarbanes, mathematician/data scientist, Investment Banking, at Credit Suisse
Best way to learn about big data tools is to just dive in: People who are new to big data often lack a comprehensive view of how end-to-end solutions are actually constructed. The easiest way to get started with Hadoop is to download your own sandbox and start playing with it. - James Casaletto, principal solutions architect, Professional Services, at MapR