Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA

Executive Briefing: The 6 keys to successful data spelunking

Ken Johnston (Microsoft), Ankit Srivastava (Microsoft)
1:50pm2:30pm Thursday, March 28, 2019
Average rating: ****.
(4.80, 5 ratings)

Level

Beginner

At the rate data sources are multiplying business value can often be developed faster by joining data sources rather than mining a single source to the very end. Successful spelunking is the new 90/10 rule: gain 90% of the high-value business impact for just 10% of the work.

Ken Johnston and Ankit Srivastava share four years of hands-on practical experience sourcing and integrating massive numbers of data sources to build the Microsoft Business Intelligence Graph (M360 BIG). You’ll explore a framework to help you glean value from multiple data sources, along with practical examples and techniques for producing full and partial joins across datasets you could never imagine integrating. Examples will include how to integrate with Dun & Bradstreet, the value of integrating with the Web Graph, and even how to tap into the LinkedIn commercial social graph.

Photo of Ken Johnston

Ken Johnston

Microsoft

Ken Johnston is the principal data science manager for the Microsoft 360 Business Intelligence Group (M360 BIG). In his time at Microsoft, Ken has shipped many products, including Commerce Server, Office 365, Bing Local and Segments, and Windows, and for two and a half years, he was the director of test excellence. A frequent keynote presenter, trainer, blogger, and author, Ken is a coauthor of How We Test Software at Microsoft and contributing author to Experiences of Test Automation: Case Studies of Software Test Automation. He holds an MBA from the University of Washington. Check out his blog posts on data science management on LinkedIn.

Photo of Ankit Srivastava

Ankit Srivastava

Microsoft

Ankit Srivastava is a senior data scientist on the core data science team for the Azure Cloud + AI Platform Division at Microsoft, where he focuses on commercial and education segment data science projects within the company. Previously, he was a developer on the data integration and insights team. He has built several production-scale ML enrichments that are leveraged for sales compensation and senior leadership team metrics.