Webinar: How to Avoid the 10 Big Data Analytics Blunders — Best Practices for Success in 2021

By on

To view just the slides from this presentation, click HERE>>

This webinar is sponsored by:

About the Webinar

As a steward for your enterprise’s data and digital transformation initiatives, you’re tasked with making the right choice. But before you can make those decisions, it’s important to understand what not to do when planning for your organization’s big data initiatives.

Michael Stonebraker shares the top 10 big data blunders that he has witnessed in the last decade or so. As a pioneer of database research and technology for more than 40 years, Michael understands the mistakes enterprises often made and knows how to correct and avoid them. By learning about the major blunders, you’ll know how best to future-proof your big data management and digital transformation needs. Common blunders include problems from not planning on moving everything to the cloud to believing that a data warehouse will solve all your problems to succumbing to the “innovator’s dilemma.” To illustrate the blunders, he shares a variety of corrective tips, strategies, and real-world examples.

About the Speakers

Dr. Michael Stonebraker

Co-Founder, Tamr

Michael Stonebraker is an adjunct professor at MIT CSAIL and a database pioneer who specializes in database management systems and data integration. He was awarded the 2014 A.M. Turing Award (known as the “Nobel Prize of computing”) by the Association for Computing Machinery for his “fundamental contributions to the concepts and practices underlying modern database systems as well as their practical application through nine start-up companies that he has founded.”

Professor Stonebraker has been a pioneer of database research and technology for more than 40 years, and is the author of scores of papers in this area. Before joining CSAIL in 2001, he was a professor of computer science at the University of California Berkeley for 29 years. While at Berkeley, he was the main architect of the INGRES relational DBMS; the object-relational DBMS POSTGRES; and the federated data system Mariposa. After joining MIT, he was the principal architect of C-Store (a column store commercialized by Vertica), H-Store, a main memory OLTP engine (commercialized by VoltDB), and SciDB (an array engine commercialized by Paradigm4). In addition, he has started three other companies in the big data space, including Tamr. He also co-founded the Intel Science and Technology Center for Big Data, based at MIT CSAIL.

Anthony Deighton

Chief Product Officer, Tamr

Anthony Deighton, Chief Product Officer at Tamr, oversees product and solutions strategy for Tamr’s growing data mastering solutions. Anthony was most recently CMO at Celonis and Senior Vice President of Products at Qlik, and has over 20 years of experience building and scaling enterprise software companies. Anthony helped found the Employee Relationship Management (ERM) business unit at Siebel Systems and it grew to over 300 customers, $20 million a year in license revenue. He holds a bachelor’s degree from Northwestern University and an MBA with high distinction from Harvard Business School.

Leave a Reply