Sep 2, 2016

Failed Big Data Projects

"Failure can happen for many reasons: Not starting with clear business objectives, Not making a good business case, Management Failure, Poor communication, Not having the right skills for the job" - Forbes

All seem theoretical rather than practical because Google had everything there was not reason for Google Flu to fail; but it did failed.  One of the reasons for failure is when you rely on public data which varies hugely. A company building analytics over its own data for own purpose is not likely to fail.  A company's Master Data Management or Data Warehouse might fail leading to Big Data failure.

Another BIG BIG big data failure is not doing data analytics as was the case of Blockbuster.

No matter data size one/company needs to do data analysis but how far and how much is the question to be asked and answered intelligently. A bank doing sentiment analysis on twitter and not analyzing the customer complaints and feedback's is doing silly. A bigger question is what organization is currently doing with data available at fingertips before investing huge in big data; though investing huge in Big data is another big data failure.

In an introductory course on Big Data I learned about a big data project which predicts whether a random walking person on street will take left or right turn; Dude!!! I can flip coin and guess.

Data used to prognosticate Ebola's spread in 2014 and early 2015 yielded wildly inaccurate results. Similarly, efforts to predict the spread of avian flu have run into problems with data sources and interpretations of those sources. - http://cacm.acm.org/magazines/2016/6/202655-what-happens-when-big-data-blunders/fulltext. 

Another Big data failure is training organizations making big with big data and data science training's and individuals dreaming to make big money with short course on big data. 

 In the End it is Exciting and it has lot more success case studies than failures
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