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PowerBI Module 1 - Getting started with Microsoft Data Analytics with 100- correct answers
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PowerBI Module 1 - Gettingstarted with Microsoft Data
Analytics with 100% correct
answers (latest update)
What is Data Analytics and why is it important - answer With data and
information as the most strategic asset of a business, the underlying
challenge that organisations have today is understanding and using their
data to positively affect change within the business. Businesses continue
to struggle to use their data in a meaningful and productive way, which
impacts their ability to act.
Example of Data Analysis with a retail Company - answer daily/monthly
sale patterns. Common data segments that you might want to examine
include day-over-day, week-over-week, and month-over-month so that you
can compare how sales have been to where they were in the same week
last year, for example.
Why is understanding the data important - answer The key to unlocking
this data is being able to tell a story with it. In today's highly competitive
and fast-paced business world, crafting reports that tell that story is what
helps business leaders take action on the data.
What challenges do businesses face when understanding data - answer
The underlying challenge that businesses face today is understanding and
using their data in such a way that impacts their business and ultimately
their bottom line. You need to be able to look at the data and facilitate
trusted business decisions. Then, you need the ability to look at metrics
and clearly understand the meaning behind those metrics.
How is data conveyed to businesses and decision markers - answer While
telling the story is important, where that story is told is also crucial,
ensuring that the story is told to the right people. Also, make sure that
people can discover the story, that they know where to find it, and that it
is part of the regular interactions.
, Steps in Data Analysis - answer Before data can be used to tell a story, it
must be run through a process that makes it usable in the story. Data
analysis is the process of identifying, cleaning, transforming, and
modelling data to discover meaningful and useful information.
To analyse data, core components of analytics are divided into the
following categories - answer . DDPPC. Descriptive, Diagnostic,
Predictive ,Prescriptive, and Cognitive
Descriptive analytics - answer Descriptive analytics help answer
questions about what has happened based on historical data. Descriptive
analytics techniques summarise large datasets to describe outcomes to
stakeholders. Performance tracker like KPI, ROI, sales, financial data, etc.
Describes the what
Diagnostic analytics - answer Diagnostic analytics help answer questions
about why events happened. Diagnostic analytics techniques supplement
basic descriptive analytics, and they use the findings from descriptive
analytics to discover the cause of these events. Describes the way
Steps in Diagnostic Analytics - answer Identify anomalies in the data.
These anomalies might be unexpected changes in a metric or a particular
market. Collect data that's related to these anomalies.Use statistical
techniques to discover relationships and trends that explain these
anomalies.
Predictive Analytics - answer Predictive analytics help answer questions
about what will happen in the future. Predictive analytics techniques use
historical data to identify trends and determine if they're likely to recur.
Predictive analytical tools provide valuable insight into what might
happen in the future. What will be?
Prescriptive Analytics - answer Prescriptive analytics help answer
questions about which actions should be taken to achieve a goal or target.
By using insights from prescriptive analytics, organisations can make
data-driven decisions. This technique allows businesses to make informed
decisions in the face of uncertainty. What should be given xyz
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