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Tuesday, April 24, 2018 
10:15 AM - 11:15 AM
| Level: | Business / Non-Technical
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A September 2017 study published in Harvard Business Review stated that only 3% of executives and managers surveyed found that their data met high-quality standards. Data science teams have unique needs, but we begin with 21st-century data requirements for advanced analytics, not necessarily the data quality practices of the 1990s. Based on over 10 years of practical experience, we will explore six best practices for launching effective data science teams that drive real business value:
- Ready to decide: How to identify if your business is truly prepared for automated decisions
- Ready to stream: How to spot the high-quality streaming data necessary for industrial-strength data science
- Ready to team: Tuning data management skill sets to support your data scientists
- Ready to deploy: Only 10% of data science models are deployed in production...how to advance the right model at the right time
- Ready to respond: Anticipating the customer feedback loop with advanced analytics
- Ready to dream: Prepping your executive management team to invest in full-stack data science teams
Susan Meyer has worked in data analytics and automation for over 20 years. She is currently employed at Monsanto as a Data Strategy Lead for its Supply Chain Quality Testing organization. Prior to Monsanto, Susan worked at MasterCard for 19 years as a business analyst, product manager, and data governance leader focused on data-driven product innovation. She holds an M.S. in Information Systems from the University of Missouri - St. Louis and a data mining certificate from The University of California, San Diego. Susan is a certified scrum master and Scaled Agilist who has worked with dozens of advanced analytics teams since 2006. She holds certifications in information privacy, privacy technology, and privacy program management from the International Association of Privacy Professionals.
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