DA-100 Analyzing Data with Microsoft Power BI Test Bank(GRADED A+)

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