Microsoft Power BI Data Analyst Certification Guide: A comprehensive guide to becoming a confident and certified Power BI professional

Description

Gain the knowledge and skills needed to become a certified Microsoft Power BI data analyst and get the most out of Power BI Key FeaturesGet the skills you need to pass the PL-300 certification exam with confidenceCreate and maintain robust reports and dashboards to enable a data-driven enterpriseTest your new BI skills with the help of practice questionsBook Description Microsoft Power BI enables organizations to create a data-driven culture with business intelligence for all. This guide to achieving the Microsoft Power BI Data Analyst Associate certification will help you take control of your organization's data and pass the exam with confidence. From getting started with Power BI to connecting to data sources, including files, databases, cloud services, and SaaS providers, to using Power BI's built-in tools to build data models and produce visualizations, this book will walk you through everything from setup to preparing for the certification exam. Throughout the chapters, you'll get detailed explanations and learn how to analyze your data, prepare it for consumption by business users, and maintain an enterprise environment in a secure and efficient way. By the end of this book, you'll be able to create and maintain robust reports and dashboards, enabling you to manage a data-driven enterprise, and be ready to take the PL-300 exam with confidence. What you will learnConnect to and prepare data from a variety of sourcesClean, transform, and shape your data for analysisCreate data models that enable insight creationAnalyze data using Microsoft Power BI's capabilitiesCreate visualizations to make analysis easierDiscover how to deploy and manage Microsoft Power BI assetsWho this book is for This book is for data analysts and BI professionals who want to become more competent in Microsoft Power BI. Although the content in this book will help you pass the PL-300 exam, there are plenty of other practical applications beyond exam preparation in the chapters. No prior experience with Power BI is needed. Table of ContentsOverview of Power BI and the PL-300 ExamConnecting to Data SourcesProfiling the DataCleansing, Transforming, and Shaping DataDesigning a Data ModelUsing Data Model Advanced FeaturesCreating Measures Using DAXOptimizing Model PerformanceCreating ReportsCreating DashboardsEnhancing ReportsExposing Insights from DataPerforming Advanced AnalyticsManaging WorkspacesManaging DatasetsPractice Exams Cover Title Copyright and Credits Table of Contents Part 1 – Preparing the Data Chapter 1: Overview of Power BI and the PL-300 Exam A brief overview of Power BI Power BI for business intelligence Power BI as a solution Why get certified? PL-300 Analyzing Data with Microsoft Power BI Microsoft tests Timelines Strategies to get a passing grade Summary Questions Chapter 2: Connecting to Data Sources Technical requirements Identifying data sources Local data sources, files, and databases Cloud and SaaS data sources Connecting to data sources On-premises data gateway Exploring query types Power BI datasets Power BI dataflows Query performance tuning Reducing the data size DirectQuery optimization Composite model optimization Advanced options (what-if parameters, Power Query parameters, PBIDS files, and XMLA endpoints) What-if parameters Power Query parameters PBIDS files XMLA endpoints Summary Questions Chapter 3: Profiling the Data Technical requirements Identifying data anomalies Interrogating column properties Examining data structures Interrogating data statistics Column distribution Column profile Summary Questions Chapter 4: Cleansing, Transforming, and Shaping Data Technical requirements Accessing Power Query in Power BI Sorting and filtering Managing columns Using column transformations Transforming any data type columns Transforming text columns Transforming number columns Transforming date and time columns Adding columns Using row transformations Combining data Using merge queries Append queries Combine files Enriching data with AI Language detection Key phrase extraction Sentiment analysis Image tagging Azure ML Using advanced operations of Power Query Using the Advanced Editor Using the Query Dependencies tool R and Python scripts Summary Questions Part 2 – Modeling the Data Chapter 5: Designing a Data Model Technical requirements Define the tables Flatten out a parent-child hierarchy Star schema Defining relationships Cardinality Cross-filter direction Relationship test tips Define role-playing dimensions Date table as a role-playing dimension Configure table and column properties The General section The Formatting section The Advanced section Define quick measures Resolve many-to-many relationships Create a common date table Power BI date hierarchy tables Using your own date table Date math Model size Role-playing with our date table Define the appropriate level of data granularity Design the data model to meet performance requirements Summary Questions Chapter 6: Using Data Model Advanced Features Technical requirements Using sensitivity labels Implementing row-level security Setting up row-level security Managing row-level security Applying natural-language Q&A capability Using Q&A in reports and dashboards Q&A linguistic models Optimizing Q&A in data models Summary Questions Chapter 7: Creating Measures Using DAX Technical requirements Building complex measures with DAX Quick measures Creating your own measure Measures versus calculated columns Default summarization Context is everything! Using CALCULATE to manipulate filters Simple filtering The FILTER function The ALL function Implementing time intelligence using DAX Date tables Role-playing dimensions Replacing numeric calculated columns with measures The X functions When to use calculated columns When to use measures Using basic statistical functions to enhance data Changing the default summarization Binning and grouping histograms Implementing top N analysis Ranking function Top N functions Creating semi-additive measures Additive measures Non-additive measures Semi-additive measures Summary Questions Chapter 8: Optimizing Model Performance Technical requirements Optimizing data in the model Removing unnecessary rows and columns Splitting numeric and text column data Optimizing measures, relationships, and visuals Optimizing relationships Optimizing visuals Optimizing with aggregations Query diagnostics Session diagnostics Step diagnostics Understanding query diagnostics Summary Questions Part 3 – Visualizing the Data Chapter 9: Creating Reports Technical requirements Understanding the capabilities of Power BI Adding visualization items to reports Choosing an appropriate visualization type Table and matrix visualizations Bar and column charts Line and area charts Pie chart, donut chart, and treemaps Combination charts Card visualization Funnel visualization Gauge chart Waterfall chart Scatter chart Map visuals Q&A visualization Formatting and configuring visualizations Formatting options for a visualization Importing a custom visual Configuring conditional formatting Configuring small multiples Applying slicing and filtering Adding an R or Python visual Adding a smart narrative visual Configuring the report page Designing and configuring for accessibility Report accessibility checklist Configuring automatic page refresh Creating a paginated report Using Power BI datasets in Excel PivotTables Summary Questions Chapter 10: Creating Dashboards Technical requirements Introducing Power BI dashboards Creating a dashboard Setting a dashboard theme Using a dashboard Pinning tiles Optimizing dashboards Configuring views of a dashboard Optimizing the performance of a dashboard Summary Questions Chapter 11: Enhancing Reports Technical requirements Using bookmarks Using the selection pane Creating custom tooltips Interactions between visuals Configuring navigation for a report Applying sorting Sync slicers Using drillthrough and cross-filter Drilling down into data using interactive visuals Exporting report data Designing reports for mobile devices Summary Questions Part 4 – Analyzing the Data Chapter 12: Exposing Insights from Data Technical requirements Exploring slicers and filters The Analytics pane Summary Questions Chapter 13: Performing Advanced Analysis Technical requirements Identifying outliers Using anomaly detection Conducting time series analysis Grouping and binning Grouping Binning Key influencers Decomposition tree visual Applying AI insights Summary Questions Part 5 – Deploying and Maintaining Deliverables Chapter 14: Managing Workspaces Technical requirements Using workspaces Using workspace roles Workspace licensing Distributing reports and dashboards Creating a Power BI app Using deployment pipelines Creating a deployment pipeline Unassigning a workspace to a deployment pipeline stage Automating deployment pipelines Monitoring workspace usage Using usage reports Summary Questions Chapter 15: Managing Datasets Technical requirements Configuring a dataset scheduled refresh Identifying when a gateway is required Configuring row-level security group membership Providing access to datasets Summary Questions Part 6 – Practice Exams Chapter 16: Practice Exams Practice test 1 Practice Test 2 Answer keys Practice Test 1 Practice Test 2 Appendix: Practice Question Answers Chapter 1, Overview of Power BI and the PL-300 Exam Chapter 2, Connecting to Data Sources Chapter 3, Profiling the Data Chapter 4, Cleansing, Transforming, and Shaping Data Chapter 5, Designing a Data Model Chapter 6, Using Data Model Advanced Features Chapter 7, Creating Measures Using DAX Chapter 8, Optimizing Model Performance Chapter 9, Creating Reports Chapter 10, Creating Dashboards Chapter 11, Enhancing Reports Chapter 12, Exposing Insights from Data Chapter 13, Performing Advanced Analytics Chapter 14, Managing Workspaces Chapter 15, Managing Datasets Index