Power BI 4-in-1 Bundle: Desktop, Service, Fabric & Copilot

Load sales data from an Excel workbook into Power BI Desktop and create a bar chart with city on the y axis and sales on the x axis.

Learn how to create a column chart in Power BI by plotting sales by segment, customizing axes, titles, and legends, and exploring region-based small multiples for insights.

Create and format pie and donut charts in Power BI by mapping sales to segments, adjusting titles, borders, and data labels, and applying readability guidelines for limited categories.

Create clustered column and bar charts in Power BI by adding category to axes, sales to measures, and segment to legends; customize colors, gridlines, and labels for clear data visualization.

Create and customize line and area charts in Power BI Desktop, visualizing profit by ship mode and quantity, with formatting, data labels, colors, and markers.

Master creating a ribbon chart in Power BI, ranking categories by sales across ship modes, and customizing axes, legends, and data labels with zoom and formatting options.

Explore creating and formatting Power BI line and stacked column charts as well as line and clustered column charts, with drill down, legends, and axis customization.

Create a line and clustered column chart in Power BI, map order date to the x axis, sales to the columns, and quantity to the line, with category colors.

Create and format a scatter plot in Power BI to show the relationship between sales and profit, assign sales to x and profit to y, and adjust borders and markers.

Create a bubble map visual in Power BI by assigning cities to the location bucket and sizing bubbles by total sales, then customize map style, labels, zoom, and title.

Learn how to create a table visual and a matrix visual in Power BI, drag fields such as country, region, city, sales, and profit, and compare their layouts and totals.

Create a funnel chart in Power BI to visualize sequential data across stages from prospects to converted leads, and customize titles, colors, and data labels.

Learn to build gauge charts and KPI visuals in Power BI using DAX measures for minimum, maximum, and target values, and format insights with trends by month.

Explore three AI visuals in Power BI—the key influencer visual, decomposition tree, and Q&A—to reveal profit insights by discount, category, and city while maximizing visual clarity.

Explore how to use Power Query Editor in Power BI to transform and clean data, load data from Excel, and ensure correct data types to support accurate data modeling.

Learn how data profiling in Power BI's Power Query editor uses column distribution, profile, and quality to understand data, identify primary keys, and ensure accurate reports and visuals.

Examine column distribution in Power BI by comparing distinct and unique counts in a single-column table via Power Query Editor, 11 records and values a–f to illustrate primary key concepts.

Append queries in the power query editor to combine two tables into a single dataset, creating a four-column result (id, name, phone number, address) with nulls where data is missing.

Learn how to perform an inner join in Power Query Editor by merging all student details with marks on the ID column, then expand to show subject and marks.

Practice left outer join by merging all student details with student marks in Power Query Editor. The left table drives the result, while unmatched right rows show nulls.

Apply right outer join in Power BI by merging two tables on ID to include all right-table records with matching left-table data, exposing nulls where no left match.

Explore left join and left anti join in Power BI, using the all student details (left) and student marks (right) tables, merging queries, and handling nulls in the final output.

Master full outer join in Power BI by merging two tables on the id column, capturing inner join results plus unmatched rows, with nulls in missing columns.

Explore the group by feature in Power Query Editor to aggregate transactions by bank and city, using basic or advanced options, and track applied steps.

Master transpose, pivot, and unpivot in the power query editor of power BI, learning how transpose swaps rows and columns, pivot aggregates sales by month, and unpivot reshapes data.

Explore the difference between add column and transform in power query editor by cleaning and splitting data from an excel sheet to create city, state, and pin code columns.

Explore how DAX, the data analysis expression language, creates measures, calculated columns, and tables in Power BI, using calendar and date functions to reveal insights for data driven decisions.

Master DAX functions in Power BI to create tables, columns, and measures, build date tables with calendar, format months and weekdays, and use concatenate, left, right, len, and mid.

Explore data modeling concepts in Power BI by comparing star and snowflake schemas, distinguishing fact and dimension tables, and understanding primary and foreign keys that relate tables.

Explore cardinality in Power BI by mastering one-to-one, one-to-many, and many-to-many relationships using primary keys and foreign keys across tables such as employees, customers, and orders, with practical DAX insights.

Learn how a DAX query is evaluated by the formula and storage engines, forming a query plan with logical and physical operations to retrieve data and produce final results.

Explore the Vertipaq storage engine and how columnar storage boosts Power BI performance. Compare import and direct query modes, and see how vertical scanning accelerates DAX calculations.

Explore encoding techniques used by the Vertipaq storage engine, including value encoding, hash encoding, and run length encoding, to compress data and boost Power BI report performance.

Compare calculated columns and measures in Power BI, noting their evaluation times—refresh for columns and query time for measures—and how they use storage and contexts (row vs filter) in visuals.

Explore expandable tables and filter propagation in a one-to-many data model, and learn how calculated columns and measures behave under default row context and calculate context transitions.

Explore how to create and use DAX aggregate functions in Power BI, including sum, min, max, average, count, and product with filters on date table and measures table.

Explore DAX concepts like row and filter context, the sum vs sumx distinction, and using calculate with all, allselected, and allexcept in Power BI.

Explore essential DAX functions by building measures in a measures table, including and, or, not, if, date diff, and switch, with practical examples using sales and cost price data.

Master DAX total MTD, total qtd, and total YTD in Power BI using a calendar table to build cumulative profits by month, quarter, and year.

Explore how to use the DAX same period last year function to compare totals across years, including total profit, total MTD, and total YTD, with a calendar table.

Create tooltips and drillthroughs in Power BI reports to reveal details on hover and drill-through pages. Configure tooltip pages, set sizes, define drillthrough fields, and add back navigation for exploration.

Discover how Power BI builds and manages table relationships, identifying primary keys, cardinality (many-to-many, one-to-many, one-to-one), and cross-filter directions using the relationship tab.

Explore how Power BI uses KPIs to compare actual values against targets with variance insights, including KPI charts and Power KPI visuals, and practical steps for building KPI visuals.

Explore how Power BI data flow centralizes 10 to 15 tables from Snowflake into a single data source, enabling one refresh to feed multiple reports.

Master row level security in Power BI by creating and managing rules that restrict data access by geography, testing with view as, and applying roles in desktop and service.

Learn dynamic row level security in Power BI using user principal name and access rules to replace static security across reports via the semantic model, groups, and service.

Apply top Power BI best practices: create a separate blank query for measures, limit visuals, use tooltips and drill-through, and filter data at source for performance.

Explore the Power BI service: navigate the cloud-based platform, create and manage workspaces, set access roles, and deploy reports and dashboards, with guidance from desktop to service.

Explore the Power BI service layout on app.powerbi.com, and learn to create and manage workspaces, reports, dashboards, and fabric capacity driven copilot workflows from development to production.

Learn how to create and manage Power BI workspaces, enable collaboration, and control access with admin, member, contributor, and viewer roles across Power BI and Fabric.

Power BI workspace roles (admin, member, contributor, viewer) define access: admin can do everything; members edit and delete reports and add contributors; contributors edit and view; viewers view only.

Set up a Microsoft Fabric capacity and attach it to a Power BI workspace, enabling unified data analytics with Fabric, Copilot integration, and semantic model storage.

Learn how to safely delete a fabric capacity and cancel its subscription to prevent ongoing billing, and understand the impact on workspace visibility and copilot access.

Explore how a Power BI deployment pipeline streamlines development, testing, and production with distinct stages, plus version control and collaboration.

Build a three-environment deployment pipeline in Azure MySQL for dev, testing, and production, publish a Power BI dashboard, and configure automatic data source synchronization across stages.

Learn to use a deployment pipeline for Azure MySQL to publish reports and a semantic model from development to testing and production, including managing credentials and deployment rules.

Define and troubleshoot deployment rules across dev, test, and prod stages in a Power BI deployment pipeline, covering data source rules, semantic models, and fabric capacity prerequisites.

Diagnose why data source rules fail in a Power BI deployment pipeline with Azure MySQL, probe semantic model constraints, and switch to Azure SQL as a supported alternative.

Set up a Power BI deployment pipeline across dev, test, and prod with Azure SQL DB, creating deployment rules to switch data sources from MySQL to SQL and publish reports.

Power BI distinguishes reports and dashboards: reports are multi-page, interactive data explorations, while dashboards are single-page, summarized tiles pinned from multiple reports in service.

Create reports directly in Power BI service from scratch—though not recommended—mirroring desktop capabilities with data sources, transforms, and visuals, and explore Copilot integration in Fabric.

Create reports in Power BI service with AI Copilot, attach Fabric capacity to a workspace, and build KPI pages with AI visuals on service or desktop.

Begin an end-to-end Power BI project for Electro Hub to analyze sales, profit, and quantity by category, and answer top and bottom products, time trends, and discounts by category.

Load data to Power BI Desktop from an Excel workbook, then use Get Data, Power Query Editor, and applied steps to clean and transform four tables into a report-ready model.

Master data profiling and transformations in Power BI, check column distribution and quality, and profile columns to prepare clean data for reporting.

Merge the fact table with dimension tables via left outer joins to bring price per unit, then compute total sales, discount value, and net sales for reporting.

Explore how a primary key uniquely identifies records with not null values, illustrated by an id column, and how foreign keys relate tables to form a Power BI data model.

Explore how foreign keys reference primary keys, enforce subset values, and identify one-to-one, one-to-many, and many-to-many relationships in data models for Power BI.

Explore the star schema concept in Power BI, organizing data into fact and dimension tables to reduce redundancy, shrink the model, and boost report performance.

Master Power BI data modeling with a star schema linking a fact table to dimension tables via one-to-many relationships. Validate data types and manage active relationships with Power Query.

Discover the three filter types in Power BI desktop's filters pane—visual level, page level, and all pages—and how they shape a net sales bar chart.

Create and format Power BI visuals to show top and bottom five products by sales, profit, and quantity, using Power Query to add a profit column and top N filters.

Explore how to visualize sales trends over time in Power BI using a line chart, drill up and drill down across daily to yearly levels, with custom formatting.

Create and format key Power BI visuals to analyze sales, profit, and discounts, including a scatter plot, a bar chart, a map, and a card for orders.

Explore how Power BI fulfills requirement four by comparing sales, profit, and quantity sold between two user-selected dates using two date tables, slicers, and DAX measures.

Learn how to fulfill requirement four with Power BI by using edit interactions between two date filters and three bar charts for sales, profit, and quantity, avoiding larger models.

Power BI 4-in-1 bundle lesson shows building a report page with a fact table and slicers from product, date, customer, and promotion dimensions, plus formatting and unidirectional filter behavior.

Learn to create dynamic slicer interactions across dimension and fact tables in Power BI, using a unidirectional relationship and a simple measure to show non-blank results.

Download and install Microsoft SQL Server Developer Edition, set up SQL Server Management Studio, and connect to Power BI using Windows authentication and a new query.

Create a new database in Microsoft SQL Server, import a flat file, and prepare data for Power BI reporting using SQL Server Management Studio.

Load insurance data from a Microsoft SQL Server into Power BI Desktop, using import mode, transform with Power Query Editor, and publish to Power BI service.

Learn to load insurance data from SQL Server into Power BI, inspect data with table view, and perform column profiling and data type checks in Power Query Editor.

Add and arrange slicers for policy number, customer ID, and claim number, switch to a drop-down style, apply a dark theme, and insert a Prism Insurance Private Limited text box.

Format slicers on the page and add new card visuals in Power BI to display total premium, total coverage, and total claim amount, with customized fonts and rounded card shapes.

Add and format a multi-row card and a ribbon chart in Power BI to display gender counts and claim status, with customized fonts, borders, and data labels for clear visuals.

Learn to add and format a bar chart and a line chart in Power BI, representing premium amounts by policy type and by age group using Power Query Editor.

Create a Power BI page with a donut chart and a matrix visual, add an active/inactive column in Power Query, and format visuals to show policy types and claim statuses.

Publish your Power BI desktop report to the Power BI service and select a workspace and account. Share the published report and manage viewing or editing permissions for collaborators.

Publish the Power BI report to a workspace, install a personal gateway, and configure data source credentials to enable a scheduled daily refresh with a chosen time zone.

Master drill through filters in Power BI to display table details on a second page, filtered by policy type via an interactive bar chart.

Publish the updated report from Power BI Desktop to the service, then test scheduled refresh and review refresh history to ensure new pages or drill through changes reflect.

Create and test row-level security roles in Power BI Desktop to restrict data by policy type (travel and health), then publish to Power BI service and validate roles there.

Test and implement row level security in Power BI service by testing as health and travel roles, applying email-based access, and ensuring data is filtered per role.

Create Power BI reports in desktop and publish to service, then assemble dashboards in service by pinning visuals from reports for at-a-glance insights.

Learn to perform sentiment analysis in Power BI using text analytics in Power Query Editor, import Excel feedback, and create a sentiment score with categories excellent, good, and needs improvement.

Add visuals for sentiment analysis in Power BI, including a word cloud, a bar chart, and a table, and publish the report to Power BI service.

Load and transform the UPI transactions data in Power BI desktop from an Excel source, using Power Query and data type adjustments, then load the model for profiling and reporting.

Explore data profiling in Power BI using the Power Query editor to inspect column profiling, distribution, and quality, identify nulls and errors, and assess 20,000 records for clean reporting.

Learn to resize and align slicers and visuals on a Power BI report page by applying a consistent sizing and spacing scheme across rows for precise, professional layouts.

Master Power BI report formatting by resizing and aligning visuals, configuring canvas settings and background, and arranging five slicers in a single row with consistent size, position, and borders.

Add a new DAX column age groups to categorize customers by age, and configure slicers across two pages, including city, device type, gender, age groups, and transaction type.

Add and customize a line chart in Power BI to show transaction amounts over time, using date on the x axis, 2024 data, and currency filters across all pages.

Add and customize a matrix visual in Power BI, place months in rows and cities and currencies in columns, format values, enable grid lines, and apply slicer filters across pages.

Learn how to sync slicers across Power BI report pages so selections on one page reflect on others, and apply conditional formatting to matrix visuals to color-code amounts.

Learn to create and manage bookmarks in Power BI to switch between a line chart and a column chart, using overlapping visuals, the selection pane, and a bookmark navigator.

Create and manage bookmarks to toggle remaining balance visuals, including line and column balance by month charts, update bookmark states, and align titles for a seamless Power BI report navigation.

Publish your report to Power BI service after signing in, selecting a workspace, and publishing, then switch bookmarks with a single click in service.

Explore Microsoft Fabric as an end-to-end analytics platform unifying data movement, processing, ingestion, and reporting, with lakehouse, governance, and Power BI integration.

Explore ethical, cost-effective ways to access Microsoft Fabric by using a work email or a domain-based organization email, since personal addresses won't work, with a 60-day trial.

Create a Fabric workspace, manage access with admin, members, contributors, and viewers, mirroring Power BI service, and learn to connect Power BI desktop to Fabric and create a lakehouse.

Explore how a lakehouse blends data lake and data warehouse benefits to handle structured, semi-structured, and unstructured data. Clarify governance, cost, and data quality trade-offs for BI and analytics.

Explore a typical fabric lakehouse architecture from diverse data sources through ingestion, transformation, and store, to consume data via Power BI or SQL endpoints.

Connect and load data to a Lakehouse using Fabric, create a Lakehouse and tables, and explore import versus direct query in Power BI while noting encoding issues and access controls.

Learn to create a SQL database in a Fabric lake house, load data, and connect the SQL database to Power BI for visualization.

Explore fabric data flows to centralize data preparation and transformations in lakehouse sources using the Power Query platform, enabling reusable, transformed data with scheduled refresh for Power BI.

Explore kql, the kusto query language, for fabric data with readability, data exploration, time series analysis, and pipe operator workflows, plus custom functions and Power BI integration.

Learn how to write KQL (Kusto query language) queries for read-only telemetry data analysis in Azure Data Explorer, and how Power BI and Fabric integrate with KQL.

Explore practical KQL basics by translating SQL to KQL, using explain to preview queries, and building select, where, top, order by, and between timestamp queries.

Learn practical KQL basics: wildcard like operations, group by and having clauses, and nested queries, with SQL parallels, plus sorting and summarizing results.

Master nested queries in kql by translating sql with the hyphen explain command, demonstrated on an employees table and username conditions; generate kql queries via grok when needed.

In kql practicals four, we demonstrate join operations with an inner join between authentication events and employees on username, and compare kql with sql for select, where, and nested queries.

Explore practical KQL techniques from SQL basics to advanced visualizations, including hourly time-binning, failed vs successful logins, and rendering charts for authentication events with anomaly detection.

Learn to connect Azure Data Explorer KQL databases to Power BI, distinguishing KQL query sets in Fabric from actual KQL databases in ADX, and wire the connection via cluster URI.