Twelve Myths About Data Science

Hi at all,
in the last days, I follow a very interesting course about the “Twelve Myths About Data Science” on Linkedin.
The instructor is Ben Sullins, an engineer, data miner and programmer. From this course, I learn different things… summarizing:

  • Big Data is a journey
  • Many clients use dozen of Big Data sources for a single question
  • Big Data are not easy to setup, you have to take in account: Cloud vs Machine, Response Time, Backup, Location of data (zoning)
  • Big Data will not replace relation database
  • Big Data is not one thing, but a combination of modules
  • Big Data is not cheap
  • Big Data are not designed to be fast, but scalable and resilient
  • Big Data can not be handled only by data scientists, but you need data engineers (architecture), data scientists (strategic role), data analysts (decision making)
  • Big Data is not necessary: True Big Data is a problem and you’d be lucky to not have to worry about it

I suggest to follow this little course (this is my third).
Good night,

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