Title: Important tools for Data Analytics | Data Science training in Pune | MITSkills
1Important tools for Data Analytics.
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2- 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.
3Here 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.
4- 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.
5- 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.