ISTC for Big Data 2016 Research Highlights

In 2016, ISTC for Big Data principal investigators, researchers and their students continued to break down the barriers to data analytics at scale, with creative new approaches and infrastructure software. Developments are being integrated into BigDAWG, the next-generation polystore architecture … Continue reading

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Write-Behind Logging

By Joy Arulraj, Matthew Perron, and Andrew Pavlo, Carnegie Mellon University In a joint collaboration between Carnegie Mellon University and Intel Labs, we explore the changes required in the logging and recovery algorithms in non-volatile memory database management systems (DBMSs). The results of this work … 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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Simplifying and Scaling Data Discovery

By Raul Castro Fernandez, MIT CSAIL People who need access to data for their jobs are spending more and more time searching for data of interest to the task at hand. This is particularly true for data-driven companies, where the … Continue reading

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Rethinking Streaming: Correct State Matters!

by Nesime Tatbul, Intel Labs and MIT CSAIL; Kristin Tufte, Portland State University; and Stan Zdonik, Brown University Stream processing has largely been thought of as real-time analytics. Data enters the system as streams and analytic functions (aggregates) are computed on the … Continue reading

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