Data Wins: The WibiData Blog

Writing Machine Learning Algorithms in WibiData

22 February 2012 By Aaron Kimball Comments.

In a previous blog post, we shared some detail on how WibiData's architecture and APIs enable large-scale storage, serving, and analysis of user-centric data. One of the primary use cases for this platform is online recommendations: programmatically determining the most relevant content, advertisements, or products to display to users on a web site. To perform this operational analysis, we've introduced new operators called producers and gatherers that are a more natural fit for expressing these analytic tasks. This post is a deeper dive into how WibiData's producer/gatherer framework works. We'll motivate this with the specific

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Another perspective on WibiData

15 February 2012 By Aaron Kimball Comments.

Recently, I've been speaking about WibiData at Hadoop User Groups and other meetups. Garrett Wu is our Director of Engineering and designed many of the fundamental concepts of WibiData's computation and data model. In this presentation to the Bay Area Software Engineering meetup, Garrett presents WibiData in his own words. For those who couldn't make it, both video and slides are available. WibiData at BASE View more presentations from wibidata.

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Speaking at Structure:Data in New York

10 February 2012 By Aaron Kimball Comments.

Over the past few weeks, I've had the privilege of sharing lessons learned about working with Hadoop and HBase with a lot of big data enthusiasts in the Bay Area and LA. Next month I'll be on the road again, to give a presentation at GigaOM Structure:Data '12 in NYC. The conference runs March 21-22. Come see my session, "Analyzing Large-Scale User Data with Hadoop and HBase." And please introduce yourself to me; I'm always interested in meeting more big data practitioners and learning more about how you wrangle big data to get results.

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How WibiData Works

6 February 2012 By Garrett Wu Comments.

Over the past year, we've had the privilege of helping a lot of great customers get more value out of their data by using WibiData to store, analyze and serve information about their users. What makes WibiData such a powerful tool? Why is it more effective than just cobbling together your own solution on top of Hadoop and HBase? In this post, we'll peel back the covers and look at how some key components of WibiData work to give you more leverage over your data. Why WibiData Data about users has challenges associated with it that you don'

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