Beginner Power BI

In this Beginner Power BI course module, Allison Gonzalez, a Microsoft certified trainer, introduces students to the fundamentals of Power BI, guiding them through the entire process from importing raw data to creating and sharing interactive reports. Allison emphasizes a hands-on learning approach with bite-sized lessons designed for flexible progress, while encouraging active participation and use of available support channels. Students will also learn how to organize their work with provided class files and resources, setting a strong foundation for their Power BI journey.

In this module, Allison, introduces the Power BI Desktop as the essential tool for the course, emphasizing its role in the initial data discovery phase of the Power BI lifecycle. They explain how Power BI evolved from Excel components like Power Query and Power Pivot, making it accessible for Excel users to transition smoothly. The module also guides students through the process of downloading and installing Power BI Desktop, highlighting the benefits of using the Microsoft Store for automatic updates and addressing common organizational constraints.

In this module, Allison introduces the initial phase of the Power BI lifecycle: data discovery and connection. Allison explains how to locate and import data from various sources into Power BI, emphasizing the importance of choosing between entire sheets or specific tables to streamline data preparation. Students will also learn how to preview and transform data in the Power Query Editor before loading it for analysis, setting a strong foundation for effective data modeling.

In this module, Allisonr introduces key data transformation techniques within the Power Query Editor, emphasizing how filtering and sorting can optimize report performance by limiting unnecessary data. Students will learn how to use intuitive UI features to apply transformations without writing code, including the powerful "Column from Examples" AI tool that generates custom columns based on user-provided samples. This foundational knowledge prepares learners to confidently manipulate data and streamline their workflows in both Power BI and Excel’s Power Query Editor.

In this module, Allison introduces the M language used within the Power Query Editor, explaining its role in making structural changes to data such as adding, removing, or transforming columns. She breaks down the organization of M code, highlighting key components like the let expression, named steps, and the chain reaction nature of the code that links each step sequentially. This foundational understanding prepares students to confidently explore and modify M code in the advanced editor, setting the stage for practical application in upcoming lessons.

In this module,Allison introduces the fundamentals of data modeling within the Power BI development lifecycle, emphasizing the transition from data preparation to organizing data relationships. She explains key concepts such as fact and dimension tables, star and snowflake schemas, and the importance of creating efficient one-to-many relationships to enable accurate and performant reporting. Students will gain a clear understanding of how to connect and relate multiple data tables in Power BI without altering the original data sources, setting the foundation for effective data analysis.

In this module,Allison introduces DAX (Data Analysis Expressions) as the primary formula language used in Power BI for creating calculations, columns, and tables directly within the report environment. Students will learn the key differences between DAX and the M language used in Power Query, focusing on how DAX enables dynamic analytics and efficient data modeling through calculated columns and measures. The module also highlights essential resources like DAX.Guide and Microsoft’s official documentation to support learners in mastering DAX functions and syntax.

In this module, Allison explains the fundamental differences between columns and measures in DAX, emphasizing that measures are stored calculations dynamically evaluated based on the context of visuals. Students will learn about implicit measures automatically created by Power BI and the advantages of writing explicit measures to define custom, reusable logic with greater precision. The module also introduces common DAX functions, including the specialized A and X variants, preparing learners to create and apply measures effectively within their Power BI reports.

In this module, Allison introduces the visualization phase of the data preparation lifecycle, focusing on designing effective reports using Power BI Desktop. Students will explore various visual types, learn the importance of planning report layouts, and understand how to create clear, user-focused designs that avoid clutter. Emphasizing practical tips like sketching report pages and applying minimalist design principles, Palasin prepares learners to craft insightful and visually appealing data presentations.

In this module, Allison introduces foundational data visualization techniques using bar charts, column charts, and line charts, emphasizing their best use cases for comparing categories and displaying trends over time. Students will learn how to effectively add data to these visuals, customize their appearance, and understand the practical differences between chart types based on layout and data needs. Additionally, the module covers the use of filters at the visual, page, and report levels to refine data views and create tailored, dynamic reports.

In this module, Allison explains the difference between the filter pane and slicers in Power BI, highlighting how the filter pane is primarily for report creators to set default filters, while slicers provide an interactive way for end users to filter data on the report. She introduces various slicer styles, including standard, cascading, and hierarchical slicers, demonstrating how they enhance user experience by allowing dynamic data exploration. The module concludes with a practical session applying these slicers in Power BI to help students understand their functionality and customization options.

In this module, Allison explores the three primary types of tabular visuals in Power BI: tables, matrix visuals, and card visuals, highlighting their best use cases for displaying numerical data. He emphasizes the importance of designing reports with high-level summaries on main pages using cards, while reserving tables and matrices for detailed, drill-down pages. Students will also learn how to format each visual type effectively to create clear and insightful reports.

In this module, Allison introduces categorical data visualization techniques, focusing on tree maps, column and bar charts, as well as pie and donut charts. They explain how tree maps display hierarchical categories with proportional sizing, while highlighting the importance of limiting the number of categories to avoid clutter. Additionally, the module compares different chart types to help students understand when each visualization is most effective for representing categorical data clearly.

In this module, Allison guides students through understanding data trends by exploring various line chart variations and their applications over time. Students will compare different visual options, including ribbon and waterfall charts, to determine the most effective ways to present time-based data. Emphasis is placed on selecting visuals that not only represent data accurately but also cater to the end user's ability to interpret and make informed decisions from the reports.

In this module Allison explores how to effectively combine categorical data with trend analysis using advanced visualizations. Students will learn to create combo charts that layer line charts over stacked or clustered columns to compare metrics like profit and profit margin with dual axes. Additionally, the course covers scatter charts with dynamic clustering and customizable axes, enabling learners to visualize multiple metrics simultaneously and track data changes over time for deeper insights.

In this module, Allison introduces the fundamentals of mapping location data in Power BI, emphasizing the importance of correctly identifying location fields to ensure accurate visualization. They explain the transition from traditional map types like the standard and filled maps to the newer Azure map, encouraging learners to adopt the latest mapping options for better functionality. Additionally, the course previews advanced mapping tools such as Shape map and ArcGIS, providing students with opportunities to explore and choose the best fit for their data visualization needs.

In this module, Allison explores how to visualize progress toward specific goals using gauge and KPI visuals in Power BI Desktop. Students will learn how to set targets, track key metrics, and interpret these visuals to monitor their performance effectively. This foundational skill will enable learners to create clear, goal-oriented dashboards for better data-driven decision-making.

In this module, Allison introduces the concept of custom visuals in Power BI, explaining how users can enhance their reports by importing additional visuals from AppSource, including those created by Microsoft and third-party developers. She highlights the importance of understanding organizational policies regarding the use of custom visuals, as some companies restrict or certify which visuals can be used. Allison also demonstrates the process of accessing, downloading, and integrating these custom visuals into Power BI to expand the range of data presentation options.

In this module, Allison guides students through the process of publishing reports from Power BI Desktop to the Power BI service, highlighting the transition from a free desktop application to a subscription-based online platform. She explains key concepts such as Workspaces, which organize and control access to reports, and Apps, which allow users to share selected content in a streamlined way. Additionally, Allison touches on alternative deployment options like the on-premises Power BI Report Server, noting its differences and directing learners to further resources for deeper exploration.

In this module, Allison explains how to effectively set up and manage workspaces within the Power BI service, emphasizing the organizational controls and access levels available. Students will learn about the roles of admins, members, contributors, and viewers, as well as how workspace apps help streamline content delivery by grouping reports, dashboards, and semantic models. The course also highlights the impact of organizational size and licensing on workspace permissions and structure, preparing learners to navigate and optimize workspace management in real-world scenarios.

In this module, Allison explains the concept and functionality of dashboards within the Power BI service, highlighting their role as single-page, high-level overviews that consolidate key visuals from multiple reports. They emphasize how dashboards differ from interactive reports by offering static visuals without filtering capabilities, allowing users to quickly monitor important metrics across various data sets. Additionally, the module covers best practices for organizing dashboards in a shared workspace and demonstrates the process of creating and managing dashboards through different import and publishing methods.

In this module, Allison explores the Power BI Q&A visual, demonstrating how users can ask natural language questions to quickly generate different types of data visualizations. The lesson covers practical tips for effectively phrasing queries and explains the process of transitioning a Q&A visual into a regular visual within Power BI Desktop to avoid issues when publishing reports. Students will learn how to leverage Q&A for rapid data insights and understand best practices for integrating these visuals into their reports.

In this module,Allison explains the concept of data refresh in Power BI, detailing how the service updates reports by retrieving new data from various sources and processing it through the established query steps. The lesson covers different refresh types, including scheduled refreshes for imported data and live connections or direct queries that update in real time, as well as the role of gateways for accessing on-premises data. Students will also learn how to configure refresh schedules, monitor refresh status, and troubleshoot common issues to ensure their reports always reflect the latest information.

In this module, Allison explains the importance of creating mobile-friendly reports by making them responsive to different screen sizes, similar to modern websites. They highlight how Power BI allows you to design distinct mobile layouts that automatically display on mobile devices, while still giving users the option to switch to the web version if desired. Students will learn how to effectively design and manage these mobile views both on the desktop and within the Power BI service to enhance user experience across devices.

In this module, Allison, introduces the Power BI mobile app as a convenient solution for accessing reports and real-time data on the go. Students will learn how the app enhances user experience across various devices, including iPhone and Android, by offering features like interactive maps, Q&A texting, and barcode scanning for inventory management. This session emphasizes practical mobile use cases, enabling learners to stay connected and make data-driven decisions anytime, anywhere.

In this course module, Allison guides students from Power BI beginners to gaining a solid foundational understanding of the platform, including its lifecycle, key concepts like semantic models, and the differences between reports, dashboards, columns, and measures. The focus is on building confidence to independently explore and create Power BI reports while acknowledging that mastery comes with continued learning. Students are encouraged to continue their journey with the intermediate course to deepen their knowledge and expand their skills further.