What happens when data science meets laws and regulations? With the increasing ability to leverage Machine Learning to predict customer behavioral patterns, test Hypotheses of health outcomes, infer demand in almost every business transaction, many companies are now embarking on a “Data Science” project. How do decision makers use data science to glean insights into their businesses, improve and expand output and grow the profit margin without creating complex regulatory, legal and ethical problems?
In this session learn:
- Why it is important to formulate the right quantitative questions that can be answered with big data analytics,
- How to employ the right principles for big data collection, preservation, cleansing and analysis
- What legal and regulatory issues govern the use of big data
- Industry specific regulation (e.g., Life Sciences, Financial Services) that add complexity to data science
- The ethical issues associated with big data analytics
Attendees will take away a framework for approaching and mitigating the risks inherent in big data analytics. This will also serve as the introduction to a standard way of approaching data science, the Good Data Analytics Principles (“GDAP”).
Speakers: Ronke Ekwensi, Bryn Bowen