Answer to the most commonly used terminology Data Science with their areas of crucial roles in solving issues with case studies. Likewise, let me know if anything is required. Ping me at google #bobrupakroy

1. Welcome to
Data Driven Science
( Data Science)

2. What is data science?
Is an interdisciplinary field about scientific
methods and techniques to extract
knowledge from the data. It is also known
as Data - Driven Science.
Or
In a simple way, we can say applying
statistical and mathematical algorithms or
following some proven scientific principles
to derive a solution rather than guessing.
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3.  It employs techniques and methodologies
drawn from many fields like mathematics,
statistics and computer science and so on.
 One not necessarily have to be a
mathematician or any computer science
engineer to understand the data science,
we’ll is needed is the curiosity to explore.
As a wise man says curiosity is the way to
perfection.
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4.  A core part of Data Science involves
analyzing massive amount of data to get
important insights and predict the future
as well.
Let’s see some of the success stories with
the help of Data Science
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5. Amazon
As mentioned in our early
Analytical videos
It’s hard to discuss about
Data Science success stories
without mentioning amazon.
They are among the early
adopters and are the only
company that have a patent that allows them to ship
goods before an order has even placed.
How about the product recommendation that we see
in the side of our amazon page, is also powered by
Data Science.
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6. Nissan
What Nissan is doing with the so call word Data Science?
Well Nissan realized Data Science = Success.
Nissan rather than digging itself and scratching their heads
for new models, car types, performance, luxury and so on
just like typical motor company does. What Nissan cleverly
did is they created a ‘request form’ where people expressed
their views and needs.
And by aggregating those important points with data
science Nissan got a clear vivid picture of the type of car
they should be making to fulfill the demand so that both can
be on WIN WIN side.
Now, Nissan is using Data Science at the core of its
development procedures to settle on better business
decision making process to measure its achievements.
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7. Other Companies with Data Science
 I believe you have hear of the consulting firms like
Deloitte, JPMorgan Chase & Co, they all use Data
Science as one of the core part of their success.
 How about General Electric(GE), is using data
science on the data generated from their various
machineries such as Jet Engines to identify new
approaches to advance their product. Even telecom
companies like T-Mobile are using customer
transactions and interactions data to predict
customer behaviors.
 After seeing other’s success stories with data
analytics, now all companies have started using data
science as a part of analytics to optimize their profits.
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8. Some more examples where data
science had played a crucial role in
solving the issues
 Image recognition
 Logistics
 Marketing
 Weather Predictions
 Airline traffics
 Medical Fields
 Fraud detections
 Internet search
 Digital advertisements
 And lastly the most important thing in Data Science it
is one of the core foundations for Artificial
Intelligence.
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9. Why Data Science is so important ?
 Let me first tell you,
How much data gets generated in a minute?
• Since 2013, the number of Twitter posts
increased 25% to more than 350,000 tweets per
minute.
• YouTube usage has more than tripled in the last
two years with user uploading 400 hours of new
video each minute of every day.
• Instagram users like 2.5 million posts every
minute!
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10. Why Data Science is so important ?
 Facebook users also click the ‘LIKE’ button on more
than 4 million posts every minute! That is nearly 6 Billion
Facebook posts liked each day!
 Around 4 million Google searches are conducted
worldwide each minute of everyday .
 Finally, data send and received by mobile internet
users 1500 000TB.
 So, with the above examples of how much data gets
generated, now imagine how much hidden insights
and patterns for accurate future predictions that we
can actually achieve by using data science.
Therefore is the reason why Data Science is so
important.
Rupak Roy

11. Kinds of job that a data science
professional ends up with
 Data Scientist: with a vast knowledge of Data Science, with
Machine Learning and Business Intelligence tools. Data
Scientist stands high as the Everest.
According to Forbes, annual demand for Data Scientist jobs
for United States itself will increase by 364 million by 2020.
The average salary for a Data Scientist is $113,436.
 Data Analyst: in 2019, the world will generate data 50times
more than now and with each day passes by the data
generated is infinity and with that to analyze those data, data
analyst jobs will never have to see the face of recession. In
Linkedin itself there are average 400 new jobs for every 12
hour
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12.  Data Science Trainer: in this present date with a lack of
the knowledge of these advance data science
techniques gives a vast opportunity to become the
fountain of data science for others.
 Business analyst: with the role of defining and managing
the business requirements, business analyst takes the lead
in every business decision making process of organization.
Hence, the definition of data science itself describes its
importance in every organization.
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13. So, are you Ready?
To set your career in one of the hottest job
of the century.
Rupak Roy