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How to Start Thinking Like
a Data Scientist
Based on an article by Thomas C. Redman
Insights from the article!
1. Start from studying small data around
1. Start from studying small data around
Open your eyes to the millions of small data
opportunities, and work a bit more effectively with data
scientists, analytics, and all things quantitative.
2. Dig deep into the data
2. Dig deep into the data
First, start with something that interests, even bothers,
you. Whatever it is, form it up as a question and write it
down.
2. Dig deep into the data
Next, think through the data that can help answer your
question, and develop a plan for creating them. Write
down all the relevant definitions and your protocol for
collecting the data.
Visualizing the data is important
Start drawing some pictures. Good pictures make it
easier for you to both understand the data and
communicate main points to others.
Draw the first picture with your hand (not tool).
Relevance to an Indian
Manager!
Being data savvy is the need of time
Slowly but steadily, data are forcing their way into every
nook and cranny of every industry, company, and job.
Managers who aren’t data savvy, who can’t conduct
basic analyses, interpret more complex ones, and
interact with data scientists are already at a
disadvantage.
Not everyone needs to become a quant. But it is worth
brushing up on the basics of quantitative analysis, so as
to understand and improve the use of data in your
business. We’ve created a reading list of the best HBR
articles on the subject to get you started.
Thank you
By Astha Jagetiya

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Data Scientist

  • 1. How to Start Thinking Like a Data Scientist Based on an article by Thomas C. Redman
  • 2. Insights from the article!
  • 3. 1. Start from studying small data around
  • 4. 1. Start from studying small data around Open your eyes to the millions of small data opportunities, and work a bit more effectively with data scientists, analytics, and all things quantitative.
  • 5. 2. Dig deep into the data
  • 6. 2. Dig deep into the data First, start with something that interests, even bothers, you. Whatever it is, form it up as a question and write it down.
  • 7. 2. Dig deep into the data Next, think through the data that can help answer your question, and develop a plan for creating them. Write down all the relevant definitions and your protocol for collecting the data.
  • 8.
  • 9. Visualizing the data is important Start drawing some pictures. Good pictures make it easier for you to both understand the data and communicate main points to others. Draw the first picture with your hand (not tool).
  • 10.
  • 11. Relevance to an Indian Manager!
  • 12. Being data savvy is the need of time Slowly but steadily, data are forcing their way into every nook and cranny of every industry, company, and job. Managers who aren’t data savvy, who can’t conduct basic analyses, interpret more complex ones, and interact with data scientists are already at a disadvantage.
  • 13. Not everyone needs to become a quant. But it is worth brushing up on the basics of quantitative analysis, so as to understand and improve the use of data in your business. We’ve created a reading list of the best HBR articles on the subject to get you started.
  • 14.
  • 15. Thank you By Astha Jagetiya