IC Colloquium : Data Exploration Challenges in the Age of Big Data
Event details
| Date | 22.09.2016 |
| Hour | 16:15 › 17:30 |
| Location | |
| Category | Conferences - Seminars |
By : Surajit Chaudhuri - Microsoft Research
Abstract:
As we continue to accumulate variety of data at an unprecedented rate, the complexity of formulating data exploration queries as well as the cost of executing such queries continue to grow. Therefore, reducing both the complexity of query formulation as well as the cost of executing exploratory queries is becoming increasingly important. We begin by discussing an example-driven approach to formulating data exploration queries to simplify the challenge of query formulation. We then reflect on why approximate query processing techniques that promise to reduce cost of exploratory queries have so far failed to gain adoption. We comment on implications of some of the recent developments in approximate query processing and conclude with a few open challenges.
Bio:
Surajit Chaudhuri is a Distinguished Scientist at Microsoft Research and leads the Data Management, Exploration and Mining group. As a Deputy Managing Director of MSR Redmond Lab, he also has oversight of Distributed Systems, Networking, Security, Programming languages and Software Engineering groups. His current areas of interest are enterprise data analytics, data discovery, self-manageability and cloud database services. Working with his colleagues in Microsoft Research, he helped incorporate the Index Tuning Wizard (and subsequently Database Engine Tuning Advisor) and data cleaning technology into Microsoft SQL Server. Surajit is an ACM Fellow, a recipient of the ACM SIGMOD Edgar F. Codd Innovations Award, ACM SIGMOD Contributions Award, a VLDB 10-year Best Paper Award, and an IEEE Data Engineering Influential Paper Award. Surajit received his Ph.D. from Stanford University in 1992.
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Abstract:
As we continue to accumulate variety of data at an unprecedented rate, the complexity of formulating data exploration queries as well as the cost of executing such queries continue to grow. Therefore, reducing both the complexity of query formulation as well as the cost of executing exploratory queries is becoming increasingly important. We begin by discussing an example-driven approach to formulating data exploration queries to simplify the challenge of query formulation. We then reflect on why approximate query processing techniques that promise to reduce cost of exploratory queries have so far failed to gain adoption. We comment on implications of some of the recent developments in approximate query processing and conclude with a few open challenges.
Bio:
Surajit Chaudhuri is a Distinguished Scientist at Microsoft Research and leads the Data Management, Exploration and Mining group. As a Deputy Managing Director of MSR Redmond Lab, he also has oversight of Distributed Systems, Networking, Security, Programming languages and Software Engineering groups. His current areas of interest are enterprise data analytics, data discovery, self-manageability and cloud database services. Working with his colleagues in Microsoft Research, he helped incorporate the Index Tuning Wizard (and subsequently Database Engine Tuning Advisor) and data cleaning technology into Microsoft SQL Server. Surajit is an ACM Fellow, a recipient of the ACM SIGMOD Edgar F. Codd Innovations Award, ACM SIGMOD Contributions Award, a VLDB 10-year Best Paper Award, and an IEEE Data Engineering Influential Paper Award. Surajit received his Ph.D. from Stanford University in 1992.
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Practical information
- General public
- Free
- This event is internal
Contact
- Host: Anastasia Ailamaki