Case Study
A Manager’s Guide to Graph Data Science HOW MODERN DATA SCIENCE TEAMS CREATE AND SHARE ACTIONABLE INSIGHTS
A Manager’s Guide to Graph Data Science HOW MODERN DATA SCIENCE TEAMS CREATE AND SHARE ACTIONABLE INSIGHTS
A Manager’s Guide to Graph Data Science HOW MODERN DATA SCIENCE TEAMS CREATE AND SHARE ACTIONABLE INSIGHTSA Manager’s Guide to Graph Data Science Introduction Your data science team brings value to the business by building and improving analytics and ML models to help your stakeholders make better decisions. For such analytics and ML to be valuable, they must be based on thoughtful data science approaches that leverage appropriately structured data to capture the context of the business, events, and/ or entities you wish to provide insights about. Historically, data scientists have structured their data points in a record oriented or tabular format (rows and columns) to help power analytics and ML. However, this approach often leaves out or makes it challenging to access connec