DA-100 Analyzing Data with Microsoft Power BI Test Bank LATEST UPDATES SOLUTIONS

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 sales manager trying to predict next month's numbers. You know that dozens, perhaps even hundreds of factors from the weather to a competitor's promotion to the rumor of a new and improved model can impact the number. Perhaps people in your organization even have a theory about what will have the biggest effect on sales. "Trust me. The more rain we have, the more we sell." "Six weeks after the competitor's promotion, sales jump." Regression analysis is a way of mathematically sorting out which of those variables does indeed have an impact. It answers the questions: Which factors matter most? Which can we ignore? How do those factors interact with each other? And, perhaps most importantly, how certain are we about all of these factors? What questions do prescriptive analytics help answer?Correct answer - which actions should be taken to achieve a goal or target. What is the benefit of prescriptive analytics?Correct answer - allows business to make informed decisions in the face of uncertainty. How do prescriptive analytics work?Correct answer - analyze past decisions and events, and estimate the likelihood of different outcomes Describe the self-learning feedback loop of cognitive analyticsCorrect answer - 1) draw inferences from existing data and patterns 2) derive conclusions based on existing knowledge bases 3) add these findings back into the knowledge base for future inferences What do cognitive analytics help you learn?Correct answer - what might happen if circumstances change and determine how you might handle these situations What are inference not?Correct answer - structured queries based on a rules database What are inferences?Correct answer - unstructured hypotheses that are gathered from several sources and expressed with varying degrees of confidence On what do effective cognitive analytics depend?Correct answer - machine learning algorithms How do cognitive services make sense of previously untapped data sources?Correct answer - using several natural language processing concepts Give an example of untapped data source to which natural language processing concepts can be applied to make sense of the data?Correct answer - call center conversation logs product reviews Give an example of several layers and types of data analytics that a retail company might perform.Correct answer - By enabling reporting and data visualizations, a retail business uses descriptive analytics to look at patterns of purchases from previous years to determine what products might be popular next year. The company might also look at supporting data to understand why a particular product was popular and if that trend is continuing, which will help them determine whether to continue stocking that product. A business might determine that a certain product was popular over a specific timeframe. Then, they can use this analysis to determine whether certain marketing efforts or online social activities contributed to the sales increase. How do data analysts build business trust in its data?Correct answer - As a practice, the data analysis process will capture data from trusted sources and shape it into something that is consumable, meaningful, and easily understood to help with the decision-making process. Data analysis enables businesses to fully understand their data through data-driven processes and decisions, allowing them to be confident in their decisions. What are the key responsibilities of the data analyst?Correct answer - A data analyst knows how to organize information and distill it into something relevant and comprehensible. A data analyst knows how to gather the right data and what to do with it, in other words, making sense of the data in your data overload. What are the main role in the data analytics process?Correct answer - Business Analyst Data Analyst Data Engineer Data Scientist Database Administrator What is the role of the Business Analyst?Correct answer - close to business specializes in interpreting the data that comes from the visualization Describe the role of the data analyst.Correct answer - enables businesses to maximize the value of their data assets through visualization and reporting tools such as MS Power BI. responsible for: - profiling - cleaning - transforming - design and build scalable and effective data models - enable and implement advanced analytics capabilities into reports for analysis - works with pertinent stakeholders to identify appropriate and necessary data and reporting requirements - turn data into relevant and meaningful insights also: - manage Power BI assets, including reports, dashboards, workspace, and the underlying datasets - implement and configure proper security procedures also: - work with data engineers to determine and locate appropriate data sources - ensure proper access to the needed data sources - identify new processes or improve existing processes for collecting data Describe the role of the Data Engineer.Correct answer - - provision and set up data platform technologies on-premises and in the cloud - manage and secure the flow of structured and unstructured data from multiple sources - ensure that data services securely and seamlessly integrate across data services also, they use on-premise and cloud data service and tools to: - ingest - egress - transform - validate - clean ...data from multiple sources collaborate with business stakeholders to identify and meet data requirements design and implement solutions does not include DBA responsibilities such as looking after a database and the server where it's hosted, and overall operational data management adds value by "wrangling" data works closely with the data analyst in: - ensuring access to the data - optimizing data models - providing connectivity to and maintenance of a modern data warehouse or data lake What are the main data platform types?Correct answer - relational databases nonrelational databases data streams file stores What roles can transition to a data engineer role?Correct answer - database administrators business intelligence professionals Describe the role of the Data Scientist.Correct answer - perform advanced analytics to extract value from data work can vary from descriptive analytics to predictive analytics What is the name of the process by which descriptive analytics evaluate data?Correct answer - Exploratory Data Analysis (EDA) What models are created in predictive analytics?Correct answer - forecast models What tool is used in predictive analytics to apply modeling techniques that can detect anomalies or patterns?Correct answer - machine learning What are some the aspects of a data scientist's work?Correct answer - descriptive analytics predictive analytics deep learning What is deep learning?Correct answer - performing iterative experiments to solve complex data problems by using customized algorithms Where is most of a data scientist's time spent?Correct answer - wrangling data feature engineering Who can help data scientist speed up the experimentation process?Correct answer - Data engineers can use their skills to wrangle data Describe the role of the Database Administrator.Correct answer - implements and manages the operational aspects of cloud-native and hybrid data platform solutions built on Azure services and SQL Server. responsible for the overall availability and consistent performance and optimizations of the database solutions. work with stakeholders to identify and implement the policies, tools, and processes for data backup and recovery plans monitors and manages the overall health of a database and the hardware it resides on manages security of the data - grants or restricts user access and privileges to the data Name the five key areas that data analysts engage in.Correct answer - Prepare Analyze Model Manage Visualize How do data analysts prepare data?Correct answer - profiling cleaning transforming take raw data and turn it into information that is trusted and understandable follow a series of steps and methods to prepare data for placement into a proper context and state that eliminates poor quality and allow it to be turned into valuable insights. ensure integrity of data: - correct wrong or inaccurate data - identify missing data - convert data from one structure to another, or from one type to another - make data more readable figure out how to get and connect to the data makes decisions to ensure that models and reports meet, and perform to, acknowledged requirements and expectations provide privacy and security assurances: - anonymizing data - prevent people from seeing personally identifiable information - removing data completely as needed In what two areas do data analysts divide most of their time?Correct answer - preparing modeling When can the data modeling process begin?Correct answer - when the data is in a proper state What is the process of data modeling?Correct answer - determine how your tables are related to each other define and create relationships between tables enhance the model by adding metrics and custom calculations to enrich the data What does effective data modeling do?Correct answer - makes reports more accurate