Data Science Strategies and 2019 Predictions Webinar

Gartner predicts that more than 40% of data science tasks will be automated by 2020, resulting in increased productivity and broader usage of data and analytics. Despite the current hype around “big data,” an overabundance of data can actually create a host of problems that prevent robust and timely predictive analytics and the implementation of IoT data effectively. As a result, many industrial companies today are faced with the challenge of overwhelming unstructured data that’s difficult to harness.

In this on-demand webinar Matthew Honaker, PhD will highlight the top data science strategies of 2018 and share his predictions for 2019. Including:

  • The dangers of too much data
  • Evergreen strategies to ensure data quality for predictive analysis
  • The best way to start building a predictive analytics strategy
  • Why and how data science services have become a lifeline in an IoT Deployment

Meet the Speaker

Matthew Honaker, PhD

Principal Data Scientist – Bsquare

At Bsquare, Matt focuses on building robust and scalable predictive models using machine learning, application of statistical methods, and development of actionable business insights through data science, all on IoT data.