I have started discussing this topic with some people at the Swiss Association for Analytics event in March.
If you haven’t been living in a cave for the last few years, you are aware of the new buzz word in our field: Big Data. I’m not a big fan of this term. Indeed, the real challenge with high volume of diversified and (un)structured data is to make sense of them. This is why I prefer terms such as data mining and analytics. Anyway, for more information about the three “D” of Big Data, have a look at the end of this post.
My main concern about Big Data is not the term used, but its current application within industry. Although a lot is written about Big Data, I think that very few companies really use Big Data. Of course, analytical competitors are fully using and benefiting from Big Data: companies such as LinkedIn, Facebook, Twitter, Google, Amazon, etc. Most of them are both part of it and use it. Although huge, these companies only represent a small percentage of all industries using analytics.
At least in Europe, most companies are not yet at the level of Big Data. Most of these companies (whether medium or large) are yet working on data quality and business intelligence (reporting). Some of them are just starting to use data mining. It is already challenging enough for these companies to leverage structured data. Don’t get me wrong: I’m not against Big Data. However, I think companies should not start Big Data projects by taking data (noise?) from any possible sources, just because some key players have Big Data projects (with data they generated, for example). In conclusion, I think that the term is badly chosen and the discussion level is far above reasonable, compared to the real use by the industry. But wait, I just added to the discussion with this post…damned!