Data science is a practice of studying the data and extracting insights from it. The data can be structured as well as unstructured.

Studying what the information comes from and what it represents can help in creating business and IT strategies. The individuals who have studies data science or are experts of data science, are also called Data Scientists.

The Data Scientists are responsible for the following tasks:

  • Convert data in to understandable information
  • Interpret rich data sources
  • Manage large amount of data
  • Merge data
  • Ensure consistency
  • Create visualizations to help in understanding the data
  • Communicate and report data findings

Since the internet boom, the world has seen many buzzwords such as the world wide web, cloud computing, virtualization, big data, byod.

However, data science has usually experienced criticism coming from academics and journalists alike, who fail to see any difference between data science and statistics and they feel it doesn’t come with a clear definition.

In a Joint Statistical Meetings of American Statistical Association, an applied statistician named Nate Silver went on say that “data-scientist is a sexed up term for a statistician. Statistics is a branch of science. Data scientist is slightly redundant in some way and people shouldn’t berate the term statistician”.

There are some things that an individual needs to have knowledge on when they work with data science. They are:

  • Statistics
  • Programming language (R, Python, SAS)
  • Excel
  • Data visualizations
  • Big Data
  • Big Data Frameworks
  • Optimization
  • Non-linear systems
  • Linear algebra
  • Hardware
  • Calculus

It is the job of the data scientists to ensure that the data is understood by others.

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