Thursday, April 26, 2012


Big Data, Big Business, is the market ready?


Source: The Wall Street Journal
Last April 18th perhaps the first Big Data specific initial public offering was made by Splunk Inc., a company that developed a software which helps companies to analyze data, but not any data, it’s ‘machine data’ as they call it. At the IPO, the company was valued at $3.28 billion, selling at a revenue multiplier of 28! For instance, Google trades at a revenue multiplier of 5 which goes to show how excited the market is about this Big Data technology. Splunk raised $229.5 million, and at the NYSE close, its stock price jumped 109%. The software that companies such as Splunk offer, help businesses to manage their increasing amounts of data and in this way avoid data inflation. Apparently, the market is getting very excited about this new IT trend, but are companies really prepared to handle these loads of information?

It seems that what firms are requiring nowadays are data scientists. It’s not only about having the engineering skills to build complex mathematical models to process the data, but also about being able to shape the data in order to get a story from it. Once these skills are fulfilled, a deep understanding of the business is also needed in order to be able to ask the right questions from which to make the data work for them. Big Data will give decision makers more information on which they can rely on, but just having more information may overwhelm them and it will not mean they will be able to use it in the right way towards the business objectives.

It is clear now that there will be a rising demand for these data scientists, however the supply side does not seem to be moving at the same rate. Universities still do not teach courses which prepare people for this, and they can hardly be found at recruitment agencies. Nevertheless, just as 30 years ago IBM started a generation of Cobol programmers, it seems as though market forces will lead to a generation of data scientists to cope with the massive amount of everyday data that is being accumulated.

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1 comment:

  1. As an educator it would have been nice to know what it takes to make one a data scientist. However I think the definition is still a little hazy.

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