I don't know about you, but I'm a pragmatic. I like explanations, guidance, demonstrations to be clear, without any jargon or 'smoke' so that I can grasp and understand clearly what my interlocutor communicates. And one of my frustration within the Big data fuzzy world is that you already have thousands of possibilities, zillions of data sets and nearly that many programming languages in order to process data. If you don't believe me, have a look here below: But, that being said, let's focus on some clear, straight forward R text data mining solutions that you could find on the Qualitative Research in R blog. Check the link!
Showing posts from October, 2017
- Other Apps
I just read an HBR paper about the new mindset of the CIO (even if you can wonder if human beings are that binary...some projects can be revenue generating and some others are and will remain costs) - transforming a classical cost-centric to a revenue-generating department. One of the most interesting part of the publication are the four areas where CIO's and their corporations are looking for a new market approach: Digital products and business models: This means a shift from selling the equipment that runs a factory, for example, to selling performance information about that equipment along with insight about how to optimize its performance. GE has become a popular exemplar of this, as it leads the way to the digital industrial future. By the end of 2017, revenue growth from information-based products will be double that of the rest of the product/service portfolio for one-third of Global 2000 companies, according to IDC. Digital operations: Transformation of everything