Context and Segmentation

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After the 2014 U.S. Midterm elections, the Daily Show aired a piece about how the elections looked in comparison to past results.  While observing how comments of the Democratic Party being in a shambles mirrored comments about the Republicans in 2012, Jon Stewart makes an aside remark about context: That joke was brought to you by context.  Context...look at how silly the world would be without context. This kind of biting sarcasm is a hallmark of the Daily Show, but it tends to be missing from higher education discussions (except on Twitter, of course).  The biggest bone I have to pick about the lack of context in higher ed has to do with student segmentation. To put it simply, there is no uniform definition of "a college student".  Now this may be…
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Responsible vs. Accountable…the Retention Edition

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I'm going to do that thing where as a parent, I use something my kids do in order to make a point.  Since I have twin 12-year old identical girls, the topic of responsibility comes up a lot. My kid reference is about Nose Goes and a typical event looks like something this: 1) Dad kindly asks girls to clean their room 2) Girls play Nose Goes...both touch their noses at the same time and then stare at each other 3) Nobody cleans the room The takeaway is that I made the mistake of inferring that BOTH of the girls are responsible for cleaning their room.  This brings up the concept of responsibility vs. accountability.  Here's the context that I'm using for those two words.  'Responsible' means that the person or persons…
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Monetize the Data :-(

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Yuck. I really don't like that phrase. I get it...especially in certain cases. Facebook gives users access to a free and (somewhat) valuable tool, so they have every right to use the data as they see fit (within ethical limits, of course). Where there is a reasonable expectation set between the user and the company about who does what with the data, there are definitely cases where companies can "monetize the data". But in educational technology? Nope. I think that's where companies really start to skirt the line. I've got a fair bit of involvement in the ed tech space. I've started my own analytics company, I network and partner with many technology companies, and I have advised other ed tech businesses. What I don't see is a model where…
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Breaking down a post about Early Alerts

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Jim Ritchey at Delta Initiative posted a nice item about early alerts in Higher Ed.   I think he's spot in as to the questions and issues he raises. To that end, I wanted to break down his post and respond from Blue Canary's perspective.  Blue Canary has recently launched Lighthouse -- our early alert retention solution.  Read on for some insights: [line] "One solution component where it is difficult to evaluate benefits is early alert systems" Difficult, but not impossible.  It's hard to measure the benefits, but if you are adopting a solution, your vendor ought to be willing to work with you to show evidence of success [line] "Organizations are learning that how the score is calculated and what data the calculation uses is critical to effectively matching…
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It’s So Simple, Anyone Can Use It!

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I dig infomercials.  Whether it's Tony Little, Billy Mays (R.I.P.), the Sham Wow guy, or the Godfather -- Ron Popeil, I've always been intrigued by their unabashed shamelessness in the face of overt consumerism.  As I think back to the great infomercials of the past, though, I draw a strong parallel between what these pitchmen/women do and what we do in the data & visualization space.  That parallel is around simplicity. The good infomercials realize that there needs to be a concise takeaway from the product demonstration: Ginsu knife: can cut a tin can and a tomato Matthew Lesko: the government is giving away free money Veg-o-Matic: it slices, it dices, it juliennes   Nevermind the veracity of the statements (or the relevance...how often does one need to julienne vegetables?).…
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Hive For Un-Structured Data

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The Hadoop ecosystem today is very rich and growing. A technology that I use and enjoy quite a bit in that ecosystem is Hive. From the Hive wiki, Hive is "designed to enable easy data summarization, ad-hoc querying and analysis of large volumes of data”. To add to that statement, Hive is also an abstraction built on top of Map Reduce that lets you express data processing using a SQL-like syntax described in detail here. Hive reduces the need to deeply understand the Map Reduce paradigm and allows developers and analysts to apply existing knowledge of SQL to big data processing. It also makes expressing Map Reduce jobs more declarative. One thing I do hear a lot from folks is that Hive, being schema driven and having typed columns, is…
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#itsnotbigdata

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I'm taking a big step with my social networking persona...I'm starting a hashtag.  Do I have to register it with ICANN?  Biz Stone?  Jimmy Fallon & Justin Timberlake?  The new hashtag is #itsnotbigdata. My reasoning is this -- big data (or Big Data or "Big Data") is at the peak of inflated expectations on the Gartner Hype Cycle.  That means that every blogger and her brother is using the term so that it'll garner more hits on the interwebs.  Problem is, it's not always used accurately and consistently.  Now I like data...I like technology...I like software...but I don't like when buzzwordy terms get thrown around haphazardly with no regard for the downstream effects.  And what are the downstream effects?  It's article after article incorrectly utilizing the term Big Data thereby…
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Quick Start Hadoop Development Using Cloudera VM

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So your company has some Big Data needs and decided to use Hadoop for processing all the data. As a developer you wonder where to start? You download and install Hadoop from Apache . You get started fairly quickly and begin writing your first Map Reduce job. Pretty soon you realize you need a workflow engine like Oozie and soon after that you think Hbase might be a good fit for what you are trying to accomplish or use Hive instead of writing Java code for Map Reduce. The Hadoop ecosystem has grown quite a bit and manually installing each piece can become frustrating and time consuming. A low barrier alternative to being productive quickly with Hadoop technologies is to use a vendor distribution like the one from Cloudera. Since…
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Your Secret Sauce is not so Secret

Analytics, Models
  In the predictive analytics space, there is always talk about secret sauce.  The roots of it make sense to me.  Think about the financial industry...if you built a model that could predict future trends in stock prices, you'd probably want to keep that a secret.  In the education space, though, the logic starts to break down. First of all, education is a highly collaborative space and it represents a social good.  Keeping a valuable secret that might help students succeed is antithetical to the nature of education.  Second, education is a complex ecosystem of people, processes, policies, content, etc.  I would have strong doubts about anyone who claimed to have a formula that worked for a wide variety of institutions.  Third, I think it creates an element of distrust.…
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