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DA-100 Analyzing Data with Microsoft Power BI Full Updated Testbank
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DA-100 Analyzing Data with Microsoft Power BI Full Updated Testbank
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DA-100 Analyzing Data with Microsoft II II II IIPower BI Full Updated Testbank
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In the learning path "Get started with Microsoft data analytics," what do you learn about?
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the life and journey of a data analyst:
skills
tasks
processes
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...they go through in order to tell a story with data so trusted business decision can be
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made
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- how the suite of Power BI tools and services are used by a data analyst to tell a
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compelling story through reports and dashboards, and the need for true BI in the
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enterprise II II II II II II II II II II II II
What types of data that are being generated each day in an organization?
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- transactional data in a traditional database
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- telemetry data from services that you use
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- signals that you get from different areas like social media II II II II II II II II II
Describe that data the a retail business collects and stores.
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in-store browsing behavior
sales
purchases II II II II
pages visited on their site
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the aisles in which purchases were made II
spending habits II II
...and much more
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Retail analytics focuses on providing insights related to sales, inventory, customers, and
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other important aspects crucial for merchants' decision-making process.
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The discipline encompasses several granular fields to create a broad picture of a retail
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business' health, and sales alongside overall areas for improvement and reinforcement.
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Essentially, retail analytics is used to help make better choices, run businesses more
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efficiently, and deliver improved customer service.
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The field of retail analysis goes beyond superficial data analysis, using techniques like
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data mining and data discovery to sanitize datasets to produce actionable BI insights that
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can be applied in the short-term.
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Moreover, companies use these analytics to create better snapshots of their target
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demographics. By harnessing sales data analysis, retailers can identify their ideal
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customers according to diverse categories such as:
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- ageII
- preferences
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- buying patterns
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- location
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- and more II II II II II II II II II II II II
What is the challenge that organizations have today regarding their data and information? II II II II II II II II II II II
understanding and using their data to positively effect change within the business.
We have an expert-written solution to this problem!
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A retail business should be able to use their data in such a way that impacts the business,
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including what?
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- tracking inventory
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- identifying customer purchase habits
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- detecting user trends and patterns
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- recommending purchases
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- determining price optimizations
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- identifying and stopping fraud
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- identifying daily/monthly sales patterns
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- performing trend analysis
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- performing period over period analysis
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What is the key to unlocking business data?
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being able to tell a story with it II II II II II II II II
What does crafting reports that tell a story do?
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It helps business leaders take action on the data. II II II II II II II II II II
Business decision makers depend on what to drive better business decisions?
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an accurate story II II II II II II II II II II II
What is the benefit to a business of making fast, precise decisions?
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The business will be more competitive, with a better advantage
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What do businesses need to be able to do with their data?
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act on the data to effect change within the business
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What types of change might occur when acting on the data?
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- reallocating resources within the business to accommodate a need
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- identifying a failing campaign and knowing when to change course
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- adjusting...prices, inventory, purchasing, assortment
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What comes first in using data to drive business decisions? II II II II II II II II II II II
business leaders partnering with data professional within your organization, such as data
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engineers and data scientists
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What do data professionals within your organization do?
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help get the data that you need to tell the story that allows business decision makers to act
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What are aspects of building a data culture?
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- telling the data story
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- where the story is told
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- who the story is told to
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- making sure people can find the story and have appropriate access
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- making sure data stories are part of regular interactions
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What is data analysis?
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The process of reducing, organizing, and giving meaning to the data that has been
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collected
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the process of...
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- identifying
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- cleaning
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- transforming
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- modeling II II II II II II
...data to discover meaningful and useful information.
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What happens to data after it has been analyzed?
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The data is then crafted into a story through reports for analysis to support the critical
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decision-making process.II II II II II II II II II II II
What is a vital component and aspect of large and small businesses? II II II
storytelling through data analysis II II II II II II
Data-driven business make decisions based on what?
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the story that their data tells
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What is a challenge that most businesses face in today's data-driven world?
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data is not being used to its full potential
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What types of critical business insights does data analysis provide?II II
evaluating customer sentiment II II
performing market research II II II II
identifying trends across the business
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What are the core categories of data analytics? II II II II
Planning: What is our plan?
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Descriptive: What happened?
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Diagnostic: Why did it happen?
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Predictive: What will happen next?
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Prescriptive: What should be done about it?
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Cognitive - mimic the human brain by drawing inferences from existing data and patterns,
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drawing conclusions based on existing knowledge bases, and inserting this back into the
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knowledge base for future inferences - a self-learning feedback loop.
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What questions does descriptive analytics help answer?
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What has happened based on historical data?
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What do descriptive analytics techniques do with large data sets?
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They summarizes them to describe outcomes to stakeholders.
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What is used to to help track the success or failure of key objectives?
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Key Performance Indicators (KPI) II II II II II II II II II
What is a common descriptive metric used in many industries? II II II
Return On Investment (ROI)
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a ratio between net profit (over a period) and cost of investment (resulting from an
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investment of some resources at a point in time). A high ROI means the investment's
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gains compare favourably to its cost.
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As a performance measure, ROI is used to evaluate the efficiency of an investment or to
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compare the efficiencies of several different investments. In economic terms, it is one way
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of relating profits to capital invested. II II II II II II
What is an example of descriptive analytics? II II II II II II II II II II II II
generating reports to provide a view of an organization's sales and financial data
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Which data analytics category helps answer questions about why events happened? II
diagnostic analytics II II II II II II II II II II II
What do diagnostic analytics techniques use to discover the cause of events?
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the findings of descriptive analytics
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In diagnostic analytics, what is further investigated to discover why events improved or
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worsened outcomes?
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What is the diagnostic analytics process?
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1. Identify anomalies in the data. These anomalies might be unexpected changes in a
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metric or a particular market.
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2. Collect data that's related to these anomalies
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3. Use statistical techniques to discover relationships and trends that explain these
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anomalies II II II II II II II II II II II II
What data analytics category helps answer questions about what will happen in the
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future? II
predictive analytics II II II II II II II II II II II
What data does predictive analytics use, and how does it use it?
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it uses historical data to identify trends and determine if they are likely to recur.
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What tools and techniques are used to provide insights into what might happen in the
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future?
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a variety of statistical and machine learning techniques such as:
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neural networks - Neural nets are a means of doing machine learning, in which a
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computer learns to perform some task by analyzing training examples. Usually, the
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examples have been hand-labeled in advance. An object recognition system, for
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instance, might be fed thousands of labeled images of cars, houses, coffee cups, and so
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