Krishna Uppala

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Insights based on detailed data on consumer behavior, product performance and marketplace behavior are driving innovation and competition in the internet space. We introduce Everest, a SQL-compliant data warehousing engine, based on a column architecture that we have built and deployed at Yahoo!. In contrast to commercially available engines, this massively(More)
Advances in healthcare data management and analytics have opened new horizons for healthcare providers such as cost effective treatments, ability to detect medical fraud, and diagnose diseases at an early stage. Central to these abilities is the need for fast ad-hoc query processing of large volumes of complex healthcare datasets. End users who work with(More)
Advertisers and big data mining experts alike are today are dealing with complex datasets of increasing variety (first and third party data), volume (events, impressions, clicks), and velocity (real time bidding). Creating predictive models to customize advertiser requirements and campaign analytics to show targeted ads to users who are most likely to(More)
Online display advertisers extensively use the concept of a user segment to cluster users into targetable groups. When the sizes of such segments are less than the desired value for campaign budgets, there is a need to use probabilistic modeling to expand the size. This process is termed look-alike modeling. Given the multitude of data providers and on-line(More)
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