Executive Briefing: Top 10 Big Data Blunders
Who is this presentation for?Data Engineers, Data Stewards, Data Curators, Data Scientists, Chief Data Officer and Chief Information Officers
Prerequisite knowledgeFamiliarity with the major concepts of data science, data management and databases
What you'll learn
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.
Dr Michael Stonebraker, Adjunct Professor, MIT, & Co-Founder/CTO, Tamr will discuss his Top 10 Big Data Blunders.
Dr. Stonebraker, a pioneer of database research and technology for more than 40 years, understands the mistakes enterprises often made — and knows how to correct as well as avoid them. He was the main architect of the INGRES relational DBMS, and the object-relational DBMS, POSTGRES. These prototypes were developed at the University of California at Berkeley, where Dr. Stonebraker was a professor of computer science for 25 years. More recently at MIT he was a co-architect of the Aurora/Borealis stream processing engine, the C-Store column-oriented DBMS, the H-Store transaction processing engine, which became VoltDB, the SciDB array DBMS, and the Data Tamer data curation system.
By learning about the major blunders, attendees will understand how best to future-proof their Big Data management and digital transformation needs. Common blunders Dr. Stonebraker will address span 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 discussed, he’ll share a variety corrective tips, strategies and real-world examples.
is an adjunct professor at MIT CSAIL and a database pioneer who has been involved with Postgres, SciDB, Vertica, VoltDB, Tamr and other database companies. He co-authored the paper “Data Curation at Scale: The Data Tamer System,”
presented at the Conference on Innovative Data Systems Research (CIDR’13).
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