Archive for the Analytics category
Yunyao Li and Shivakumar Vaithyanathan
November 14, 2018
Role of AI in Enterprise Applications
The recent return of AI summer and the enthusiastic uptake of AI in the commercial world can be loosely attributed to three innovations: Apple’s Siri, Google’s self-driving cars, and IBM Watson Jeopardy. This enthusiasm stems from the belief that AI will influence a wide range of applications across multiple industry segments. While such enthusiasm is, […]
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Aditya Parameswaran
June 25, 2018
Visual Data Exploration: A Fertile Ground for Data Management Research
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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Letizia Tanca
February 18, 2016
Wisdom: a “double V” for Big Data
Some months ago, I found an exciting piece of news on the Web: a top manager proclaimed [1]: “If the most important thing you offer is data, you are in trouble. (….) Algorithms is where the real value lies. Algorithms define action.” How interesting! It seems to suggest that everybody, including computer scientists and in […]
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Kristina Lerman
November 24, 2014
Why your friends have more to be thankful for
As Thanksgiving approaches, it may feel like everyone else has so much more to be thankful for. Just check your Facebook, Twitter or Instagram: your friends seem to dine at finer restaurants, take more exotic vacations, and attend more exciting parties. Research suggests this is not simply a matter of perception, but a mathematical fact […]
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Kristina Lerman
October 30, 2013
The Curses of Heterogeneity in Big Data
“Both theoretical and empirical research may be unnecessarily complicated by failure to recognize the effects of heterogeneity” – Vaupel & Yashin Big Data is daily topic of conversation among data analysts, with much said and written about its promises and pitfalls. The issue of heterogeneity, however, has received scant attention. This is unfortunate, since failing […]
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