Producing highly accurate Predictive Models in Social Data Mining can be a challenge. Feature Engineering using traditional methodologies can only take you so far. Finding that needle in a haystack requires creative thinking, large time investments and can require hundreds of iterations to achieve highly accurate results.
Today, Spark is used in production at Toyota Motor Sales USA to power the Toyota Customer 360 Insights Platform and Social Media Intelligence Center.
Through this presentation we will discuss how Toyota’s R&D Data Science Team came to choose Spark as their premiere engine for large-scale data processing and Machine Learning, the lessons learned, and the journey to deploying Spark in the Enterprise.
Brian Kursar is director of data science – research and development for Toyota Motor Sales, USA. In this role, Kursar has end-to-end responsibility for predictive analytics on Big Data across the enterprise. He is the chief architect on the Customer 360 Advanced Analytics and Insights platform at Toyota which powers the Toyota Social Media Intelligence Center as well as the recently launched Customer Return on Experience Analytics Application.
In 2011, his work was recognized in the Gartner BI Excellence awards as a Semi Finalist for architecting Toyota’s first Big Data Analytics application. Kursar has been with Toyota for 12 years. Prior to Toyota, he spent four years developing global supply chain solutions and consulting for the U.S. government in housing and urban development multimedia solutions.