Power BI is a popular and widely used business intelligence and data visualization tool developed by Microsoft. It empowers organizations to transform raw data into meaningful insights and interactive visualizations, enabling more informed decision-making. You'll begin this course by getting a big picture understanding of what Power BI has to offer, including three core features: data connectivity for easy data loading, transformation and modeling options, and visualizations. Next, you'll install Power BI desktop from the Microsoft Store, and explore its user interface. You'll see where you can build your reports, view your data and set up modeling relationships. Finally, you will access data from a file and learn how to transform and process that data so it can be used for data analysis and visualizations. You will work with Power Query to rename column headers and remove duplicates, learn to merge and split columns, and view data profile, quality, and distribution. When you have your data in the right format, you'll load the data into Power BI and set up a simple bar chart visualization in your report.

Power BI offers a seamless and efficient way to connect and retrieve data from databases. It supports a wide range of database systems including, but not limited to, SQL Server, Oracle, MySQL, and PostgreSQL. Users can establish connections to these databases by providing connection details such as server addresses, authentication credentials, and database names. You will start this course by loading files stored in SharePoint into Power BI. You will authenticate yourself to SharePoint from Power BI to access, process, and load data. Then, you'll visualize the data with pie and donut charts. Next, you'll load data from SQL Server into Power BI. You'll discover the difference between the Import mode and the DirectQuery mode. Lastly, you'll import data from a MySQL database, connect to MySQL using root credentials and user credentials, and learn to reset credentials and configure new ones.

Power BI offers robust capabilities to seamlessly retrieve data from various cloud storage services, facilitating efficient integration of cloud-based data into reports and visualizations. It supports connections to popular cloud platforms, including Microsoft Azure Blob Storage, Amazon S3, Google Cloud Storage. In this course, you will learn how to import data into Power BI from BigQuery on the Google Cloud Platform (GCP). You will create a service account with the permissions necessary to access and load data. Next, you will work with S3 buckets on Amazon Web Services (AWS) and create an Identify and Access Management (IAM) user with the credentials necessary to access and work with S3. You will write a Python script to connect to S3 and load and import data into Power BI. You will then access and retrieve data from Azure Blob Storage to load it into Power BI for analysis and use a connection string to authenticate and authorize Power BI to Azure storage. Finally, you will import data by making REST API calls and from embedded HTML in a web page using a Web connector and build visualizations such as pie charts, line charts, treemaps, and area charts in your Power BI report.

Power BI's data modeling capabilities empower users to craft sophisticated data relationships, calculations, and hierarchies. With the ability to establish meaningful connections between different data tables through relationships, users can seamlessly integrate disparate datasets and facilitate the creation of dynamic calculated columns and measures for in-depth analysis with Data Analysis Expressions (DAX). Hierarchies further enhance exploration by enabling intuitive drilldowns in your data. In this course, you will explore calculated tables and perform operations such as UNION, INTERSECT, and NATURALINNERJOIN to craft new tables. You will work with calculated columns and create and use calculated measures. Next, you'll learn how to create and model relationships between your tables, explore cardinality, and uncover the concept of cross-filter direction that influences the flow of filters across relationships. Finally, you'll explore hierarchies in Power BI, working with both default and custom hierarchies.

Power BI's advanced charting features, including gauges, funnels, radar charts, calendars, and Sankey diagrams, elevate data visualization by presenting insights in innovative formats. These specialized visuals in Power BI empower users to convey intricate information effectively, enhancing their ability to derive valuable insights from diverse datasets. You will start this course by creating gauge charts and funnel charts. Next you will visualize data using Sankey diagrams and learn how to work with Gantt charts to map project schedules. Finally, you will explore how to use radar charts to compare multiple variables across data points and implement heatmaps to highlight patterns and variations. You will also work with calendar layouts, which are similar to heatmaps but showcase values within a calendar framework.

Final Exam: From Data Loading to Stunning Visualization will test your knowledge and application of the topics presented throughout the From Data Loading to Stunning Visualization track.

In this Challenge Lab, you will implement a data model by using DirectQuery. First, you will create an Azure SQL database, and then you will create a data model. Next, you will create a chart-based report. Finally, you will publish the report, and then you will update the data to show the DirectQuery direct connection. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or exit and then return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

In this Challenge Lab, you will implement a data model by using Power Query. First, you will create a data model, and then you will transform data by using Power Query. Finally, you will create a report, and then you will publish the report. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or exit and then return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

In this Challenge Lab, you will create model calculations by using advanced DAX. First, you will create a data model, and then you will create advanced DAX calculations. Finally, you will create a report, and then you will publish the report. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or exit and then return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

Power Query is a powerful data transformation and preparation tool, seamlessly integrated into Microsoft Power BI and other Microsoft products such as Excel. It enables users to effortlessly extract, transform, and load data from various sources, ensuring data consistency and quality. Begin this course by exploring how to transform and clean data using Power Query. You will learn to delete, rename, and move columns, remove duplicates, and perform a host of other data cleaning and processing operations. Next, you will discover how to create query duplicates and references and how to perform basic and advanced filtering on your data. Then you will find out how to add columns with calculated and conditional values and how you can use merge queries to create a new column in your data. Finally, you will perform grouping and aggregation operations, create parameterized queries, and combine query data using the append operation. This course will provide you with a solid understanding of how Power Query can be used for data transformation.

In Power BI, you can establish data relationships and use Power Query to perform joins to merge multiple data tables into a cohesive dataset. By defining these relationships and using functions like merge queries, you can seamlessly combine data from different sources based on common keys, enhancing data integration and enabling in-depth analysis. In this course, you will discover how to create relationships between tables that will allow you to perform more complex inter-table operations. Next, you will learn how to perform SQL-style joins on two tables. Power BI offers numerous types of joins, including inner, outer, left, right, left anti, and right anti joins. You will implement all of these join techniques to define the differences between them and describe their use cases. You will also learn how to pivot and aggregate data in Power Query. Finally, you will explore fuzzy merging to perform joins for inexact matches. This course will provide you with a foundation for how to perform exact and fuzzy joins in Power BI.

In this Challenge Lab, you will create a multi-page slicer report by using Microsoft Power BI. First, you will prepare data, and then you will get data from data sources. Finally, you will create a multi-page slicer report, and then you will publish the report. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or exit and then return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

Power BI service is a Microsoft cloud-based platform designed for sharing, collaborating, and publishing Power BI reports and dashboards. Begin this course by exploring dataflows and datasets in order to create, use, and refresh dataflows and datasets in the Power BI service. Next, you will create and use auto-generated reports and manually create reports and dashboards in the Power BI service. You will also learn how to use the dashboard Q&A feature to ask natural language questions to Power BI. Then you will examine a variety of features of reports and dashboards and find out how to connect to a dataflow from Power BI Desktop to create a report using that data. Finally, you will focus on publishing reports from the desktop to the Power BI service, creating a dashboard with charts from multiple reports, using slicers to filter the data in your visuals, and exporting and embedding Power BI reports in SharePoint sites. Upon course completion, you will be able to confidently use Power BI service to create and collaborate on reports and dashboards.

In this Challenge Lab, you will set up the Power BI service environment. First, you will deploy a Microsoft 365 tenant, and then you will create a Power BI service account. Next, you will create a Power BI workspace, and then you will create a Power BI dataset. Finally, you will create Power BI reports. This lab is a prerequisite for all related Power BI Challenge Labs. You must complete this lab, and then save the trial account credentials before beginning any related Power BI Challenge Labs. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

In Power BI, a scorecard is a useful visual tool for presenting and tracking essential key performance indicators (KPIs), offering a quick and concise overview of critical data points. On the other hand, paginated reports are structured documents designed for generating formal, print-ready reports. Power BI's deployment pipelines play a pivotal role in streamlining the development and deployment of BI solutions and automating processes. In this course, you will discover how to use scorecards and metrics to track KPIs. Then you will learn how to pin visuals as live tiles and update them by refreshing data. Next, you will find out how to add slicers to filter visualizations and explore how to create and embed paginated reports in your dashboard. Finally, you will examine Power BI applications and deployment pipelines, create Power BI apps to package your reports and dashboards, and use deployment pipelines to manage the life cycle of your content in the Power BI workspace. Upon course completion, you will be able to effectively work with scorecards, dashboards, and other important features of Power BI.

In this Challenge Lab, you will create a report by using a custom theme. First, you will prepare data, and then you will create a custom theme. Finally, you will create a report, and then you will publish the report. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or exit and then return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

Power BI Mobile is a dedicated app that allows users to access their Power BI reports and dashboards from smartphones and tablets. It offers a responsive and user-friendly interface, enabling mobile data exploration, sharing, and collaboration. Begin this course with an exploration of the Power BI Mobile application on an Android device, learning how to create a mobile layout for a report and add visual-level and report-level data. Next, you will examine the features of the Power BI Mobile application to see what functionality is available to you on the go. Then you will learn how to configure a shortcut to open a report from your phone's home screen and how to create and use QR codes to easily share a report. Finally, you will discover how to share dashboards with other team members and how to use annotations to mark important visuals in a dashboard. After completing this course, you will be able to confidently use the Power BI Mobile application to view and analyze reports and dashboards on your mobile device.

In this Challenge Lab, you will create an alert for a report by using Microsoft Power BI. First, you will prepare data, and then you will get data from a data source. Next, you will create a report, and then you will publish the report. Finally, you will create an alert for a dashboard tile. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or exit and then return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

In this Challenge Lab, you will create an incremental refresh policy by Using Microsoft Power BI. First, you will create an Azure SQL database, and then you will create a data model. Next, you will create a report. Finally, you will publish the report, and then you will update the data to verify the incremental refresh policy. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or exit and then return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

Final Exam: Mastering Power BI Service and Power Query will test your knowledge and application of the topics presented throughout the Mastering Power BI Service and Power Query track.

The Power BI Fabric administrator is a role dedicated to managing the Power BI service for an organization. Fabric admins have the authority to control workspace settings, access permissions, and data policies, ensuring secure and efficient data governance within the Power BI environment. In this course, you will learn about the administrative roles in Power BI. You'll see that the Fabric administrator role is the main administrative role and has full access to management tasks, usage auditing, and performance monitoring. You will work in the Admin Portal, which is the primary workplace of Fabric administrators, where all administration settings, audit logs, and performance metrics are visible. Next, you will learn how to use Power BI as a Fabric administrator. You discover how to allow or block specific operations for all users in an organization or for specific security groups. Finally, you will explore a number of administrative settings and how you can configure them.

Power BI's real-time streaming capabilities enable users to visualize and analyze data as it's generated or updated. By connecting to various streaming data sources, such as Internet of Things (IoT) devices or social media feeds, Power BI allows for immediate insights and dynamic dashboard updates, enhancing situational awareness and enabling proactive decision-making based on the most current information. In this course, you will learn how to connect to on-premises data sources using a data gateway. You will explore the two types of data gateways: standard mode and personal mode. Next, you will learn about the three main types of Power BI datasets: streaming, PubNub, and push datasets. You will discover how to create and use streaming dashboards, create dashboards with streaming tiles and different visuals, and configure live dashboard tiles. Finally, you will explore how to create hybrid datasets, which are both streaming and push, and how to create reports using this data. You will also learn about other advanced features useful for data streaming, such as dashboard alerts, scheduled refresh of data, and query caching.

Final Exam: Advanced Strategies for Administration, Security, and Performance will test your knowledge and application of the topics presented throughout the Advanced Strategies for Administration, Security, and Performance track.

In this Challenge Lab, you will implement row level security by using Microsoft Power BI. First, you will create a test user, and then you will prepare the data. Next, you will create a role, and then you will create a report. Finally, you will publish a report. Note: Once you begin the Challenge Lab, you will not be able to pause, save, or exit and then return to your Challenge Lab. Please ensure that you have set aside enough time to complete the Challenge Lab before you start.

Power BI's artificial intelligence (AI) capabilities offer a remarkable blend of data analytics and artificial intelligence. Power BI empowers users to unlock hidden patterns, generate predictive forecasts, and gain a deeper understanding of their data without requiring extensive data science expertise. You will start this course by generating insights on data and reports. You will explore how to generate these insights on datasets, reports, and even dashboard tiles. You'll also learn how to harness AI to explain fluctuations in your data. Next, you will learn how to perform text analytics in Power BI. You will explore how to use the Text APIs for language recognition, key phrase extraction, and sentiment analysis. Finally, you will use image analytics in Power BI by loading a dataset of images and generating tags for each set.

Machine learning (ML) in Power BI provides a dynamic and transformative dimension to data analysis. This feature enables users to create predictive models, discover patterns, and make data-driven decisions while requiring no programming or machine learning expertise. You will start this course by creating a binary classification model that will be used to predict categorical variables. You will load in data and perform exploratory data analysis, including visualizing the data and extracting insights. Then, you will create and train a binary classification model and use it for predictions. After training the model, you will view the training report that will allow you to evaluate your model's performance. Next, you will build a regression model to predict the value of a continuous variable. You will load in the data and perform preprocessing steps to clean your data. You will also perform exploratory data analysis and visualize your data to extract insights about patterns and trends in your data. Then, you will create and train your regression model and learn how to interpret the training report generated by Power BI. Finally, you will perform multi-class classification.

Power BI includes power features that offer valuable insights into your data. The Key Influencer visual helps identify the factors or attributes that have the most significant impact on a chosen outcome. On the other hand, the Decomposition Tree provides an intuitive way to break down complex data into understandable components, allowing users to explore data hierarchies and identify key contributors to a specific metric. You will start this course by learning how Power BI will leverage artificial intelligence (AI) for detecting anomalies in time series data. Next, you will use decomposition tree visualizations to drill-down into measures. You will also make use of AI splits, which are AI-generated drill-downs into high value and low value categories. Finally, you will use Key Influencer visualizations to help you identify factors in your data that drive specific outcomes.

Smart narratives and the Q&A feature in Power BI enhance data storytelling and interactivity for reports and dashboards. Smart narratives automate the creation of textual descriptions and insights from data. The Q&A feature, on the other hand, allows users to ask natural language questions about their data and receive immediate responses and insights. You will start this course by using smart narratives in Power BI to generate natural language summaries of visualizations, dashboards, and reports. You will configure dynamic variables in your narratives that update with your data. Next, you will use the Q&A feature to ask natural language questions about visualizations that will be answered with numbers, charts, or tables. You will also learn to use the Teach Q&A feature to teach the Q&A widget to work with organization-specific terminology. Finally, you will learn how to use Power BI Copilot. You will explore how to calculate measures using natural language queries to generate DAX commands and add those measures to your reports.

Final Exam: Unleashing AI in Power BI will test your knowledge and application of the topics presented throughout the Unleashing AI in Power BI track.