Saturday, December 1, 2012

A New Way of Developing Expertise in Big Data

I am focusing on new ways of developing expertise in the Hortonworks ecosystem.  This is a project that will take time.  The reason I wanted to do this is for two key reasons:

  1. Most training is backward thinking and the Big Data boom is the perfect place to innovate how to build expertise using the concepts of Big Data.
  2. Big data, technical infrastructures, virtualization and the cloud are all changing too rapidly to use the old traditional methods of learning.  The old ways of taking classes, buying books, reading whitepapers and doing searches on the Internet is too time consuming and not effective enough.
One of the goals of big data is to process and get value out of large volumes of data.   Data that comes from a lot of different sources, data that is usually not stored and often thrown away.  Okay, so you want to learn Big Data or any other technology like Cloud, Virtualization, Business Intelligence, C programing, etc.   However the traditional ways are not effective and here is why:

  • Education classes no matter how good they are, cannot possibly encompass all the real life knowledge out there and the information is out of date as soon as you finish the class.
  • The Internet is your best friend and your worst enemy.  There are volumes of information, but which information is the best, can you trust and is current.  If you are new to an area getting past this is too slow.
  • Books are great for learning, but reading books take too much time and they do not contain all the real life information out there.
  • Social Media has tons of great real life information on Twitter, Facebook, blogs, whitepapers, books, Youtube, corporate websites, university classes and technical classes. 
  • Technical conferences bring knowledge experts to a location for a week, but can you get away to the 4-6 key conferences you'd like to attend in a year.
  • Real life knowledge being learned by graduate students in study groups, customers solving real world problems and experts building reference architectures and best practices.    The problem with this information is it can be hard to get access to or even know where to go or who has it.

So from all the resources above, the knowledge is there to become an expert in an area like Big Data.  The hard part is getting access to achieve a high ROI in the shortest time possible.  So part of becoming an expert is dealing with a data problem.  My goal is to learn to create experts in the shortest time possible (velocity), from a lot of different sources (variety),  from an overwhelming level of information (volume) for an individual and build confidence that the expert is learning from the absolute best information in the best way (value) in the shortest time possible.

As I work to help Hortonworks build the best world class training in the world, I will also be working on developing expertise using big data.

The things I do to keep busy between baseball coaching seasons.  :)

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