Peter Krensky is a Director, Analyst on the Business Analytics and Data Science team, specializing in data science and machine learning, including predictive and prescriptive analytics, citizen data science, augmented analytics, DSML team structure, AI talent management, and data and analytics education and scholarship.
Prior to joining Gartner, Mr. Krensky was a research analyst with Aberdeen Group. There he covered a broad spectrum of business intelligence topics, including advanced analytics, data discovery, self-service data preparation, sales and marketing analytics, data governance, and Hadoop. Before his time as an analyst, he spent a year living in Sao Paulo, Brazil, where he worked as an Operations Assistant for a reinsurance broker.
Miller do Brasil
Data and Analytics Leaders
Analytics, BI and Data Science Solutions
Data and Analytics Strategies
B.A., cum laude, History, Amherst College
1How data science and machine learning deliver business benefits
2How to get started with data science and machine learning
3How to build, nurture and place data science teams
4What software tools to adopt and invest in for data science and machine learning
5When to build, buy, outsource data science and machine learning solutions