importance of data science

1
Importance and Use of Data Science

• https//www.besanttechnologies.com/training-course
  s/data-science-training-in-bangalore

2
Importance and Use of Data Science

• Data Science Concepts Data Science attracted
  attention that perhaps no other technological
  revolution has achieved.
• In India, too, the wave of Data Science has been
  massive and, like any other trend, is one of the
  most important, technological, India was quick to
  adapt to this technology.
• In the process, India managed to produce some of
  the most skilled data science experts, who not
  only created an impact on our country, but
  positively influenced companies around the world.

3
Importance and Use of Data Science

• As the world entered the era of big data, the
  need for storage also grew. It was the main
  challenge and concern for the company's
  industries until 2010.
• The main focus was on the creation of structures
  and solutions for storing data. Now, when Hadoop
  and other structures correctly solve the storage
  problem, the focus has been changed to process
  this data.
• Data Science is the secret sauce here. All the
  ideas you see in Hollywood sci-fi movies can
  really come true through Data Science.

4
Importance and Use of Data Science

• Data Science is the future of Artificial
  Intelligence. Therefore, it is very important to
  understand what Data Science is and how you can
  add value to your business.
• Big DataTraditionally, the data we had was, for
  the most part, structured and small in size, that
  could be analyzed using simple tools of BI.
• Unlike data in traditional systems, which were
  largely structured, most data is unstructured or
  semi-structured.

5
Importance and Use of Data Science

• Let's take a look at the data trends in the
  following image, which shows that, by 2020, more
  than 80 of the data will be unstructured.
• This data is generated from different sources,
  such as financial records, text files, multimedia
  forms, sensors and instruments.
• Simple BI tools are not capable of processing
  this huge volume and variety of data.
• That's why we need more complex and advanced
  analytical tools and algorithms to process,
  analyze and extract meaningful insights.