I don‘t see the correlation between title and content, as well the value of the information presented as long you don’t develop the ideas. The facts might be true, though they look pretty isolated, they lack unity. Graphics without some interpretation bring little value.

There are also some aspects that can be easily questionable:

  • Managers don’t need to understand the inner working of data science — they need to understand the outputs and put them in context, and is a data scientist’s responsibility to help in the process.
  • How would you handle the data manually? The reasons why are needed automatic or semiautomatic data pricessing can be found between the characteristic of big data: velocity, veracity, variety, variability, validity or volability.
  • Why would leave data scientists their jobs as long they are highly paid?
  • If you don’t have an infrastructure then you must build one and there are many open source tools for that.
  • I think you are missing the point what statistics is about and how it can help in the process.

Probably, exploring 1-2 ideas would bring more value to the readers than listing facts that don’t make sense and have no anchor in the text or reality whatsoever. Keep writing!

IT professional/blogger with more than 19 years experience in IT - Software Engineering, BI & Analytics, Data, Project, Quality, Database & Knowledge Management

IT professional/blogger with more than 19 years experience in IT - Software Engineering, BI & Analytics, Data, Project, Quality, Database & Knowledge Management