Archive for the Databases category

Arun Kumar
Arun Kumar

ML/AI Systems and Applications: Is the SIGMOD/VLDB Community Losing Relevance?

Databases, Machine Learning

Overview of DEEM 2018 The ACM SIGMOD Second Workshop on Data Management for End-to-End Machine Learning (DEEM) was successfully held last June in Houston, TX. The goal of DEEM is to bring together researchers and practitioners at the intersection of applied machine learning (ML) and data management/systems research to discuss data management/systems issues in ML […]

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Aditya Parameswaran
Aditya Parameswaran

Visual Data Exploration: A Fertile Ground for Data Management Research

Analytics, data exploration, Databases

Information visualization is an essential tool in the arsenal of a data scientist: visualizations help identify trends and patterns, spot outliers and anomalies, and verify hypotheses. Moreover, visualizations are visceral and intuitive: they tell us stories about our data; they educate, delight, inform, enthrall, amaze, and clarify. This has led to the overwhelming popularity of […]

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Azza Abouzied and Paolo Papotti
Azza Abouzied and Paolo Papotti

Courting ML: Witnessing the Marriage of Relational & Web Data Systems to Machine Learning

Big Data, Databases, Interview, 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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Vijay Srinivas Agneeswaran
Vijay Srinivas Agneeswaran

Google Spanner: Beginning of the End of the NoSQL World?

Big Data, Databases

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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Mohamed Mokbel
Mohamed Mokbel

Thinking Spatial

Databases, Recommendations, Spatial, Systems

Self-driving cars, ride-sharing service (e.g., Uber and Lyft), and Pokemon Go are just three examples of recent disruptive applications that gained huge market share and publicity. It is expected that each self-driving car will generate 2 PB of data per year, with 10 Million of such cars by 2020. Uber has 2+ Billion rides so […]

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