Archive for the Big Data category
Azza Abouzied and Paolo Papotti
February 14, 2018
Courting ML: Witnessing the Marriage of Relational & Web Data Systems to Machine Learning
The web is an ever-evolving source of information, with data and knowledge derived from it powering a great range of modern applications. Accompanying the huge wealth of information, web data also introduces numerous challenges due to its size, diversity, volatility, inaccuracy, and contradictions. This year’s WebDB 2018 theme emphasizes the challenges and opportunities that arise […]
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Surajit Chaudhuri
May 12, 2017
Approximate Query Processing – Where do we go from here?
I think we need to take a hard look at approximate query processing. Don’t get me wrong. The vision of approximate query processing is indeed compelling. In the age of Big Data, the ability to answer analytic queries “approximately”, but at a fraction of the cost of executing the query in the traditional way, is […]
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Vijay Srinivas Agneeswaran
April 27, 2017
Google Spanner: Beginning of the End of the NoSQL World?
Google has recently announced that its flagship wide-area database named Spanner has been made available on the Google Cloud. Google Spanner is the next generation globally-distributed database built inside Google and announced to the world through the paper published in OSDI 2012 [1]. This article explores the implication of Google Spanner, in particular to the […]
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Jignesh Patel
February 9, 2017
The data chatbots are coming
The big data era (now more than a decade old) ushered in dramatic shift in mentality whereby enterprises increased their appetite for making “data-driven” decisions. To a large extent, most enterprises have gotten very good at collecting data. Now, the next big challenge is to unlock non-trivial insights that are hidden in that data. There […]
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Felix Naumann
April 10, 2016
Reflections of a Data Skeptic
In the 21st century, our everyday lives are shaped by what machines tell us to do. Big data and their application to economy, policy, and our social life act as behavioral equalizers. And this they do under the assumption of optimization in both subtle and open ways. In fact, they are pushing individuals into uniform […]
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