The Big Data ISTC: A Retrospection by Michael Stonebraker, Samuel Madden and Timothy Mattson

The Big Data ISTC is a research project sponsored by Intel that ran for five years (August 2012- August 2017).  This blog post highlights some of the accomplishments and lessons learned during this period. Big data is usually categorized into … Continue reading

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VisualCloud: A DBMS for Virtual Reality

By Brandon Haynes, Artem Minyaylov, Magdalena Balazinska, Luis Ceze and Alvin Cheung of the University of Washington Our ability to collect videos en masse can revolutionize how we interact with the world by enabling powerful virtual reality (VR) video applications … Continue reading

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ISTC Releases Open Source Code for S-Store Transactional Streaming System

By John Meehan and Stan Zdonik, Brown University & Nesime Tatbul, Intel Labs and MIT Today, the ISTC for Big Data released the first version of our S-Store transactional stream processing system. S-Store is open-source software and available for download … Continue reading

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Improving Clinical Decision-Making with Big Data

An Interview with Peter Szolovits, MIT CSAIL Doctors, nurses and other healthcare professionals have always had to “read” and respond quickly to often-imperfect data under stressful circumstances. What has changed over time is the volume and types of data that … Continue reading

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Polystore Databases to be Examined at IEEE, CIDR Conferences

Polystores, a more-modern approach to sharing heterogeneous data that addresses Big Data’s volume, variety and velocity demands, will be the topic of discussion at two upcoming conferences: The first IEEE Workshop on Methods to Manage Heterogeneous Big Data and Polystore Databases, … Continue reading

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PipeGen: A Data Pipe Generator for Hybrid Analytics

By Brandon Haynes, Alvin Cheung, and Magdalena Balazinska, University of Washington As the number of big data management systems continues to grow, users increasingly seek to leverage multiple systems in the context of a single data analysis task. A critical challenge … Continue reading

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Interactive Search and Exploration over Large Multidimensional Data

by Alexander Kalinin, Ugur Cetintemel and Stan Zdonik of Brown University In the Big Data era, professionals across scientific areas need efficient, interactive ad-hoc data analysis. Ideally, they need generic and reusable systems tools for interactive search, exploration and mining … Continue reading

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Analytic Monitoring for the Internet of Things

By Peter Bailis, Stanford Infolab, and Sam Madden, MIT CSAIL An increasing proportion of data today is generated by automated processes, sensors and devices—collectively called the Internet of Things (IoT).   Inexpensive hardware, widespread access to communication networks, and decreased … Continue reading

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Genomics Data, Analytics and the Future of Climate Change

By Vijay Gadepally, MIT CSAIL, in collaboration with the Chisholm Laboratory at MIT Meet Prochlorococcus marinus, a marine cyanobacterium that’s intricately linked to the global carbon cycle, widely present in seawater, and possibly holds secrets to future climate change. These … Continue reading

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Urban Analytics for Smart Cities: Connecting Data to People

By Kristin Tufte, Portland State University “A Smart City is one where data and technology improve people’s lives.¹” Governments, NGOs and academic researchers are looking to data and analytics to create more livable cities. Ideas and innovation are flowering. The … Continue reading

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