Data Systems Group at MIT

Posts Tagged ‘AI; MIT; Data Systems Group; Big Data;’

MIT, Brown Develop Interactive Machine Learning Tool for Analytics July 2019

July 01, 2019 – Researchers from MIT and Brown University have developed an interactive machine learning tool that lets anyone, from data scientists to small business owners, use analytics to solve real-world issues. The interactive system, called Northstar, runs in the cloud but has an interface that supports any touchscreen device, from smartphones to large interactive whiteboards. Users can…

Read More

Why Is Enterprise Data Integration So Challenging? June 2019

A.M. Turing Award Laureate and database technology pioneer Michael Stonebraker delivered a welcome keynote at Data Summit 2019, titled “Big Data, Technological Disruption, and the 800-Pound Gorilla in the Corner.”

In his presentation, Stonebraker—who is an MIT Adjunct Professor and Tamr co-founder—offered his views on many of the thorny big data challenges facing enterprises today, the established and newer technologies available to address these issues, and the intractable problem that remains the 800-pound gorilla in the room.

Read More

The case for learned index structures – Part II 1/9/18

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data…

Read More

The case for learned index structures – part I 1/8/18

Whenever efficient data access is needed, index structures are the answer, and a wide variety of choices exist to address the different needs of various access patterns. For example, B-Trees are the best choice for range requests (e.g., retrieve all records in a certain time frame); Hash-maps are hard to beat in performance for single…

Read More

How machine learning will accelerate data management systems – December 2017

In this episode of the Data Show, I spoke with Tim Kraska, associate professor of computer science at MIT. To take advantage of big data, we need scalable, fast, and efficient data management systems. Database administrators and users often find themselves tasked with building index structures (“indexes” in database parlance), which are needed to speed up data…

Read More