Important tools for Data Analytics | Data Science training in Pune | MITSkills

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Important tools for Data Analytics.
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• Important tools for Data Analytics.
• Artificial intelligence is making waves all
  across the globe. It is changing the way
  organizations work and is enhancing the overall
  productivity of the firms. The biggest
  application of machine learning in the
  organizations is data analytics. It refers to the
  process of digging out useful data and using it
  to get insights about the businesses, make
  predictions and to prepare strategies.
  Efficacious analysis of data can garner immense
  benefits for the firm.
• Data is thus treated as an asset for every
  organization and is, in fact, the fuel that makes
  organizations run properly. However, the
  organizational data is of no use without data
  analytics. That is why companies seek data
  analysts and experts who can analyze the data and
  provide useful information to the companies.
• The big data analytics market is huge and is
  expected to escalate even further thereby
  providing opportunities to a plethora of dynamic
  candidates. In this scenario, the intensive
  know-how of data analysis with working knowledge
  of data analytics tools can give you a
  competitive edge over others.  MIT Skills offers
  a job-oriented course in data analytics that will
  broaden your knowledge, sharpen your analytics
  skills and accustom you to vital data analytics
  tools.

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Here are some vital data analysis tools that are
used in the present scenario 1.  Excel It is
the most elementary and widely used tool for data
analysis. It is a great tool for the beginners
and helps in performing the basic grunt work. The
fact that it has a massive user community makes
it popular. Excel can be used to summarize data,
basic data manipulation and for data
visualization. It is also used by the analytics
team to explain the observations to the business
team. 2.  SAS SAS is the most widely used data
analytics tool by virtue of being versatile,
robust and easy to learn. Two major apps are
enterprise miner and visual analytics. Several
new features and modules have been added to this
tool. The new additions include anti-money
laundering, SAS analytics for SMEs, and SAS for
IoT.
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• Here are some vital data analysis tools that are
  used in the present scenario
• 3.  Python
• Python is one of the most popular languages in
  the present era as it is fast and easy to learn.
  Features of analytics have been added to the
  language to make it a powerful data analysis
  tool. The tool provides statistical and
  mathematical analysis. Apart from analytics, it
  can also include machine learning.
• 4.  R
• The R language is being used for the past 20
  years. The language was designed to perform
  analytics. It contains several packages including
  big data support, Microsoft support, data
  mapping, data visualization and statistical
  analysis. The only constraint of the tool is that
  it is single threaded.

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• Here are some vital data analysis tools that are
  used in the present scenario
• 5.  Tableau
• Tableau is a tool that facilitates data
  visualization. It has a drag and drop interface
  that helps in data mining and performing
  different kind of data analysis. Its machine
  learning algorithms decipher the type of data and
  the best method to analyze it.
• 6.  Spark
• Spark is a big data analytics tool that runs in
  real time. The traditional analysis tools were
  disk-based and had batch processing during the
  night. However, this tool runs in memory thereby
  leading to a faster analysis of data. The biggest
  advantage of the tool is that it is an open
  source tool and free of cost.
• MITSkills Provide Post Graduate Course in Data
  Analytics. This Masters Course in Business
  Analytics allows students to develop a thorough
  understanding of Big Data analysis, Hadoop and R
  Programming.