Six Major Areas of Data Science?

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Six Major Areas of Data Science?
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The six major areas of data science include the
following

• Multidisciplinary investigations.
• Models and methods for data.
• Pedagogy.
• Computing with data.
• Theory.
• Tool evaluation.

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• Multidisciplinary investigations. Considering
  large, complex systems with interconnected
  pieces, data scientists use varying methods to
  collect large amounts of data.
• Models and methods for data. Data scientists need
  to rely on experience and intuition to decide
  which methods will work best for modeling their
  data, and they need to adjust those methods
  continuously to hone in on the insights they seek.

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• Pedagogy. It is up to data scientists to work
  with companies and clients to determine the best
  ideologies to apply while collecting and
  analyzing information about their customers and
  products.
• Computing with data. The biggest thing that all
  data science projects have in common is the
  necessity to use tools and software to analyze
  the involved algorithms and statistics, because
  the size of the pool of information they are
  working with is so massive.

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• Theory. Data science theory is an evolving and
  sophisticated professional arena with countless
  applications.
• Tool evaluation. There are many tools available
  for data scientists to use to manipulate and
  study huge quantities of data, and it's important
  to always evaluate their effectiveness and keep
  trying new ones as they become available.

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