Monday, January 6, 2014

Different ways of getting started with Big Data

For those who are getting started with Big Data, there are a multitude of options with their own pros and cons. Without going further in detail about each of them, below is a mind map with some of the options. Based on the budget allocated to the initiative, time-to-market, core expertise of the company, industry regulations and various other factors the appropriate one can be picked.
For example, there is a better probability that a startup planning a Big Data initiative would be more towards a cloud based service to avoid the initial CAPEX and also for the sake of instantaneous scalability. Similarly, for a bank there is better probability towards an in-premise commercial distribution (like CDH from Cloudera, HDP from Hortonworks) as they can concentrate on their line of business than on the issues that arise with the Big Data environment and also because of the industry regulations.
{pick*me*2} by { lillith } from Flickr under CC
For those who are following the Big Data space, a week never goes by without the mention of a new startup / framework / funding. It will be some time before we see consolidation, with only the strong players left.


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