In
continuation to my last post Part 1, today, I would like to bring few more
observations from the industry that revolve around whether data scientists are
supposed to run algorithms (or) they are meant towards solving business
solutions?
q Firstly,
hardly any checks exist for “does whatever data scientists applied for mining
the data (let it be small or big) is helpful in providing solutions that can be
combined with the sphere of real world understanding and their needs? (Reasoning
or Strategic Reasoning)”.
q Secondly,
ignoring client requirements deeply and presenting the technologies they are
comfortable in, which cannot be heart and soul of data sciences.
q Finally,
its became a habit of searching a better algorithm once and using the same for years
ignoring new data dimensions which are adding day-by-day, wherein, its failure
later provides blame on complete data sciences.
