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Data Analyis in
Decision Making
Hello!
I am Vikrant Narayan
Data Analytics enthusiast
You can find me at @vikrant.m.narayan@gmail.com
2
“ Decision making can sometimes
seem like an inner civil war
- Jim Rohn
3
Is Data enough?
● Events from the past have shown us that, just
looking into past data and analysing attributes of
data points, do not guaranty success.
● We need to ask ourselves if data and data
analysis is enough to guaranty success of the
model.
4
Is Data enough?
● The answer to the question is NO.
● There have been instances where similar data
analysis models have been used but the results
of the models have been drastically different.
5
Data Analyis.
How does it work?
Et tu, Google?
● Data analytics was used to study the data about
influenza virus and predict future outbreaks.
● The model worked perfectly for a few years
before it eventually failed.
7
Reliability
● If data analysis does not guaranty success, is it
okay to rely on them in more serious domains
like, say, medicine and law enforcement?
● We find that data is involved in real life decision
making, in spite of all these failures.
8
What decides
Success?
Pattern Recognition
● Analysing patterns between successful and
unsuccessful models reveal that the success of
the model depends on the decision making.
● They show that results depend on instinctive
decisions and risk management.
10
Role of Data
● Data analysis is primarily for breaking up the
data and understanding the data.
● Data might not be preferred to put back the
broken pieces together.
11
Relevance to managers
● Managers should be able to not just collect data
points and analyse them numerically, but also to
make decisions and take risks for the data analysis to
be succesful.
13
15
Thank You!

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Data Analysis in Decision Making: Is Data Enough

  • 2. Hello! I am Vikrant Narayan Data Analytics enthusiast You can find me at @vikrant.m.narayan@gmail.com 2
  • 3. “ Decision making can sometimes seem like an inner civil war - Jim Rohn 3
  • 4. Is Data enough? ● Events from the past have shown us that, just looking into past data and analysing attributes of data points, do not guaranty success. ● We need to ask ourselves if data and data analysis is enough to guaranty success of the model. 4
  • 5. Is Data enough? ● The answer to the question is NO. ● There have been instances where similar data analysis models have been used but the results of the models have been drastically different. 5
  • 7. Et tu, Google? ● Data analytics was used to study the data about influenza virus and predict future outbreaks. ● The model worked perfectly for a few years before it eventually failed. 7
  • 8. Reliability ● If data analysis does not guaranty success, is it okay to rely on them in more serious domains like, say, medicine and law enforcement? ● We find that data is involved in real life decision making, in spite of all these failures. 8
  • 10. Pattern Recognition ● Analysing patterns between successful and unsuccessful models reveal that the success of the model depends on the decision making. ● They show that results depend on instinctive decisions and risk management. 10
  • 11. Role of Data ● Data analysis is primarily for breaking up the data and understanding the data. ● Data might not be preferred to put back the broken pieces together. 11
  • 12.
  • 13. Relevance to managers ● Managers should be able to not just collect data points and analyse them numerically, but also to make decisions and take risks for the data analysis to be succesful. 13
  • 14.