The document discusses why companies do not need perfectionist data scientists and should instead focus on small groups working on problems step-by-step. It notes that very few people are true perfectionists, and seeking them out would be too expensive. Instead, having multiple small groups of data analysts working on targeted problems can help companies make incremental improvements while spending less money. The conclusion is that companies do not need single highly-skilled data scientists but can achieve results through collaborative work by groups of analysts.

1. NO
PERFECTIONIST
NEEDED

2. THIS IS KAUSTUBH
SRIVASTAVA
FROM SRM

4. PERFECTIONIST
• Data who are very good and excelling
are very less in numbers, thus the
company should be focusing on small
issues to resolve the problem one by
one

6. DATA SCIENTIST
• Small group was of data scientist working
on small topics would be more efficient for
a company
• Company should be looking for small
advancement cause looking for a
perfectionist will mean shelling out money,
which companies does not want

8. EXPERTISE
Its not about the correct advice the
data scientist has to think about but
to solve the problem permanently
while no group of people should be
affected

9. TARGET
• All class of people should be profited
• The company should gain profit by
the solution
• The data analyst to be used so that
less fees has to be paid by the
company

11. MONEY SPENT
• Too much of money has to spent on
doing data analysis as the field is
started to grow and very less people
know about the subject.
• Scientist are the one who are the
most highest paid

12. INSIGHTS
• There is no need to spend money on
perfectionist
• Small data analyst can do the same work in
more time and small amount of money
• Task can be assigned to a group of data
analyst

14. CONCLUSION
There is no need of very good data
scientist, rather it an be performed by
small analyst in a group step by step.

15. THANK YOU