Constant Contact Labs Developer Blog

Data Management

  • CSV Column Discretization with Java Posted Monday, January 3, 2011 Huan Lai 0 Comments


    When mining a large amount of data, often times you end up with a lot of columns with continuous values. While this is the most “pure” version of the data, sometimes you want to cluster these values into bins to do things like creating histograms or just easy analysis of the distribution of the data. I ran into this when I ran a few Hadoop jobs that spit out CSVs as their output. After looking around online for a while, I couldn’t find any readily available solution, so I wrote up something really quickly to do just this.

     
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  • An Android “coupon tracking” app using QR Codes Posted Friday, October 1, 2010 Eric Lubin 1 Comment

    I recently decided to learn Android programming and of course I wanted to use the Constant Contact Web Services, but I also wanted to program against some other features of my phone (that’s why I bought it in the first place!).  I was trying to think a little “outside the box” and still have a useful application.  I thought about using maps, photos, or GPS, but ultimately decided that bar code scanning would be fun!  The result is Coupon Tracker for Constant Contact.

     
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  • Visualizing Information Posted Friday, June 4, 2010 Huan Lai 0 Comments

    With the massive amount of information to sort through, finding everything that you need becomes a difficult and tedious task, especially when that information is dispersed across several different places. Alongside the data mining project that we are currently working on, the problem of contact management has always intrigued us. With some of our customers having well over 25,000 contacts being managed by Constant Contact, and most likely even more information about these contacts and others spread out amongst several other mediums, there had to be a better way to do things, to easily extract valuable information out of that.

     
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  • Applying Data Mining Techniques to MapReduce Posted Thursday, May 27, 2010 Huan Lai 3 Comments

    Here at the Labs, we have been playing around with the MapReduce programming model (namely the open-source Hadoop implementation) for a while, but have been relatively conservative up till now. Most of the jobs that we have done thus far have been relatively simplistic, being more or less basic aggregation functions, with the most difficult part being the shear size of the data itself. This time around, we are planning on being a little more adventurous with the techniques we will be using to analyze the data, mining deeper than we had before. Before actually diving in, I did some reading of books and papers from both academia and industry to get an idea of the landscape and what we could try. Here’s a basic summary of some of the more interesting things that I’ve stumbled upon and possible ideas that we will tackle in the near future.

     
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