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Highlights from day 3 of IBM Insight 2015

Manager of Portfolio Strategy, IBM

In another jam-packed day at IBM Insight 2015, a huge announcement in the general session set the bar higher than ever. IBM announced acquisition of The Weather Company’s product and technology businesses. The Weather Company’s data platform hosts the fourth most-used mobile app in the US. Cloud-based services handles 26 billion requests a day. As a result, IBM is ramping up the new IBM Watson Internet of Things unit with a powerful cloud platform for cognitive business.

The media coverage of this announcement has been significant. A quick Internet search shows FortuneThe New York Times, The Wall Street JournalThe Washington Post and Wired are just a few publications covering the news. Check out the official IBM press release for details. The combination of technology and expertise from the two companies will serve as the foundation for the new Watson Internet of Things unit and Watson Internet of Things Cloud platform, building on a $3 billion commitment made by IBM in March 2015 to invest in related offerings and services.

Widespread innovation

Also in the general session, we heard an inspiring story from Local Motors. The organization is on a mission to keep everyone safer by innovating on a 100-year-old process for manufacturing cars. They are working on a way to develop the world’s first 3-D printed car, and they are working toward the goal of building autonomous vehicles.

Fredi Lajvardi, an inspiring teacher, also spoke at the general session. He chronicled the story of how the sons of undocumented Mexican immigrants learned how to build underwater robots, and the team went up against MIT in the process. Lajvardi is a nationally recognized Science, Technology, Engineering and Math (STEM) educator and the subject of the critically acclaimed documentary Underwater Dreams and the motion picture Spare Parts.

The general session ended with celebrities Ron Howard and Brian Grazer talking about how they bring epic stories in math and science to life on the screen. Their presentation covered many of their movies from A Beautiful Mind to Apollo 13. A book signing followed, and Grazer was taking selfies on stage.

Vast data science commitment

Immediately following the general session, the EXPO was hopping, and my talk on “Spark in the IBM Analytics Platform” drew a crowd of over 120 attendees interested in what building on Spark really means. IBM has built the analytics platform on Apache Spark because data science is rapidly emerging as a core business opportunity, and Spark was designed for data science. In addition, new roles such as data scientist, data engineer and chief data officer (CDO) are rapidly emerging.

IT analysts report organizations are investing in this area, and data science spend is outpacing traditional IT spend by six times. Data scientists build deep analytics such as machine learning, natural-language processing and image recognition. The output is a complete data product that can be embedded anywhere. It includes data access, the ability to update algorithms, visualization and seamless integration across the enterprise.

Business leaders can afford these big bets because open source technology is up to the task. Spark is a processing framework built for speed, ease of use and sophisticated analytics that enables applications to run 100 times faster in memory and 10 times faster when running on disk. It provides a unified programming model for batch, streaming graph data and machine learning, and it enables solution developers to easily build and embed analytics capabilities.

According to Gartner, "by 2018, 30 percent of streaming, near-real-time data integration and data management use cases will be supported by stacks that include Apache Spark." Spark helps developers focus first on the business problem rather than putting implementation first. It also enables data scientists, developers and data engineers to work together to access all data, build analytics models quickly, iterate quickly in a unified programming model and deploy analytics everywhere. Spark is one of the fastest growing ecosystems in the history of open source.

http://www.ibmbigdatahub.com/sites/default/files/insighthighlightsday03_embed.jpgAfter my session, I spoke with clients and IBM Business Partners in the EXPO. Questions around how Spark works with IBM InfoSphere Streams, IBM InfoSphere BigInsights and IBM SPSS predictive analytics software were plentiful. Across Insight 2015, The Spark story was heard loud and clear.

And after a few hours at the booth, I listened to the annual Women in Technology panel that included two PhDs and top executives from four different organizations. The discussion centered around how to build skills to become influential and successful leaders and the technical skills that are required for careers in data and analytics. Each year, Inhi Suh, vice president, strategy and business development for IBM analytics at IBM, sponsors the event.

Some big draws

I like taking a look at the attendance for various sessions at Insight. For example, these sessions were quite popular: 

  • The Internet of cars: Real-time analytics to improve safety, reduce congestion and more
  • Fusing deep visability, rich context and machine learning to detect cybersecurity threats
  • Applying real-time predictive modeling for powerboat racing at Silverhook

Day three at Insight 2015 proved to be a very busy day. If you were not able to attend the conference, check out the general sessions, keynotes and interviews with VIPs. For some deeper dives into other key areas, consider participating in these events:

  • Datapalooza: Register for this inaugural Datapalooza event, 10–12 November, 2015. It enables attendees to take their data science skills to the next level through hands-on experience, one-on-one coaching and learning how to build a practical data science product in just three days. And in doing so, they'll experience addressing real-world data science challenges that require creative pattern thinking, machine learning, cognitive computing, natural-language processing and stream computing.

And be sure to explore the informational IBM Analytics resource page on Spark.