Over two million analysts worldwide use R, and they come from an extremely diverse pool of industries that ranges from journalism to financial services to life sciences.
If you replace R with data analytics, this could seen as a very appealing future of Big Data and data analytics. Something like a generalized version of data analytics at work.
But before loosing myself in this perspective, I thought I should take a look at the present and see how what is done now is going to lead to that amazing tomorrow:
- Tim O’Reilly said a couple of years ago “Data is the Intel inside” and since then we’re seeing lots and lots of companies trying to materialize this slogan.
- More new technologies for storage, processing, and analysis are developed and reaching the market then in the 10 previous years.
- People are starting to embrace big data overcoming their fear of privacy invasion
All these are good signs that we could consider as a good basis for the future. On the other hand the past and today’s reality tell a different story:
- Even if technology costs decreased over time, the investment in creating data startups are still high.
- Financial institutions are not investing (too much) into data technology companies.
- There are only a few companies that are able to accumulate significant amounts of useful data.
- There are even fewer companies that are able to use effectively the huge amounts of data.
What worries me is that even if we will continue to see both a commoditization and impressive improvement of data solutions, by the time all tools will be in place and accessible to everyone, as per the opening paragraph, really valuable data will reside in just a few private well locked silos.
Original title and link: The Appealing Future of Big Data and Data Analytics ( ©myNoSQL)