Nowadays, Big Data is more than just a buzzword. This set of strategies allowing for an efficient data processing is already set up in many business sectors: banks, insurance companies, manufactures, e-commerce, retail, etc. Companies using these strategies are performing better and take less risks. This is why the Big Data market has an annual increase of 10 % and is estimated at $84 billions for 2026 (Big Data Vendor Revenue and Market Forecast, 2011-2026).
However, the technical solutions  required to establish these data strategies are mostly unknown to the general public and require the intervention of data experts.  Indeed, a good data strategy implies the knowledge of frameworks such as Hadoop and Spark, of flow aggregators, cloud solutions, dedicated programming languages, libraries for data analytics, as well as strong skills for statistics, visualization and popular science writing.
Companies willing to start their data transition are thus facing a confusing situation. A data strategy has to be set up in order to stay competitive, but the task is very difficult: where to begin with? Why? How? Which technology? Whith whom? Numerous companies have thus failed their data transition and lost huge amounts of money on the way.
In this article, we present the available options for a company willing to start a data transition, as well as the best strategy to undertake in order to achieve a sucessfull transition.

Read More