What is Data Analytics?

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1stepGrow academy
What is Data Analytics?
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Table Of Content
01
What is Data Analytics?
02
Types of Data Analytics.
03
Importance of Data Analytics
04
Conclusion
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What is Data Analytics?
Data Analytics refers to the collection of
qualitative and quantitative methods for gaining
valuable information from data. It involves a
variety of processes which include extracting
data as well as classifying it into the field of
data science to be able to discover patterns,
relationships connections, and useful insights
from it.
In simple language, data analytics is the science
of evaluating raw data to make outcomes from the
data. Data analytic techniques help you to carry
raw data and find patterns to take out useful
ideas from it.
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Types of Data Analytics
Predictive Analytics
Descriptive Analytics
Diagnostic Analytics
Cognitive Analytics
Prescriptive analytics
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Types of Data Analytics
Descriptive Analytics
Predictive Analytics
Diagnostic Analytics
This type of data analytics analyzes historical
data to understand what has taken place. It is
the most simple method of data analytics.
Diagnostic data analytics examines past data to
explain the cause of an anomaly. This type of
analytics aims to answer why did this happen?
from a descriptive analytics result.
Predictive analytics is giving hints that it is
something related to future prediction. Yes, it
is as it tells about what is going to happen.
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Types of Data Analytics
Prescriptive analytics
Cognitive Analytics
Prescriptive analytics uses machine learning,
business rules, and algorithms in business. For
example If we want to prescribe what steps we
need to take to improve the sales for the coming
year.
Cognitive Analytics is an intelligent technology
that uses a variety of analytical techniques that
analyze huge datasets and provide structure to
data that is unstructured.
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Importance of Data Analytics
Reduce the cost of operation
Through a careful analysis of data, it is
possible to reduce financial risk.
Predict future trends
By using analytical tools for predictive
analysis, companies can create future-oriented
products and services.
Monitor product performance
Data analytics can be used for monitoring the
behavior of customers toward products or
services. It is used to discover the reasons for
low sales as well as what products customers
purchase and why they purchase them, and how much
they spend on these items.
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Importance of Data Analytics
Improved business performance
Analyzing and collecting data on the supply chain
will help to identify the causes of delays in
production, as well as bottlenecks and potential
problems. When it comes to stock levels and data
analytics, it can aid in determining the optimal
supply of all products of an organization.
Better Targeting
Utilizing Data Analytics, organizations can
decide which types of advertisements can
effectively reach their clients and impact them.
Data Analytics allows organizations to know which
advertising methods for their products will have
the most impact on their target people and on
what scale the company could implement this type
of marketing.
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Conclusion
Data is essential for every business and aids
them in understanding their customers, increasing
their marketing campaigns, and increasing their
bottom lines. Tools and methods for data
analytics are essential as there are many
benefits of data. However, with no tools, you
will not be able to enjoy these benefits. Raw
data is a wealth of potential, but it is
essential to use data analytics in order to
unlock the doors to grow your business. We can
conclude that data analytics are important for
the growth of any business since data analytics
aids the business in maximizing its performance.
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Thank you!
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