Become an Expert in Microsoft Power BI Desktop

Explore the core concepts of Power BI, compare its features with Excel, and learn to download, install, tune settings, and navigate the Power BI graphical user interface and BI workflow.

Explore how Power BI Desktop connects over 70 data sources, transforms and models data with DAX, and delivers interactive reports and dashboards for self-service business analytics across organizations.

Download and install Power BI Desktop using the Microsoft Store for updates, or via the Microsoft site with a 64-bit exe. Power BI Desktop is free to install and use.

Configure Power BI settings to manually manage relationships by disabling update or delete relationships on refresh and auto detect, set locale to English United States, turn off auto date time.

Explore the Power BI interface and a four-stage workflow: query editor, model view, table view, and report view, covering ETL, data cleansing, data modeling, and visuals.

Discover the latest Power BI updates and a wealth of resources—training videos, templates, blogs, communities, and monthly summaries—then connect, transform, load, and shape your data model.

Connect to data sources in Power BI, shape and transform with Power Query, merge and append data, perform data quality checks, and build calendars for robust reports and dashboards.

Power BI desktop connects to data from many sources using Get Data, with file, database, Azure, and online service connectors, and transforms data in Power Query before loading.

Explore the Power Query Editor tools for extracting, transforming, and loading data, using the UI ribbons, query steps, M code generation, and tips for efficient data prep.

Master Power BI table transformations with the Power Query Editor, including removing or retaining columns, setting a fixed column count, promoting headers, and shaping data types.

Connect to Dim sales territory and Dim product sub category CSV files. Create an alternate key from the second dash in the product key and load into the data model.

Learn to transform tables in Power BI Desktop by adding dim product subcategory and dim sales territory, create an alternate key, replace nulls with na, and apply changes.

Explore how Power BI stores and connects data, focusing on import mode, Direct Query mode, and composite mode, plus live connections and their trade-offs.

Connect to a SQL Server data source in Power BI using Power Query, choose import mode, enter credentials, and apply optional advanced options before transforming tables.

Connect to a web page with Power BI desktop’s web connector to import URL data, preview tables in the navigator, transform in Power Query Editor, and load to the model.

Master data profiling in Power BI with column quality, distribution, and profile tools to identify errors and missing values, then apply query editor suggestions to clean data.

Explore numeric tools in Power Query Editor for Power BI Desktop, including statistics aggregations and row-level operations, then add a discounted price column and manage applied steps.

Apply Power BI desktop to validate statistics on products and customers by calculating the average list price, unique colors, distinct customers, and highest annual income, then restore data tables.

Extract high level statistics in Power BI Desktop, including average price, distinct colors, distinct customers, and maximum yearly income, and restore all tables to their original state.

Explore power BI's text tools to split, trim, clean, and format text, apply proper case, extract by delimiters, and merge columns to create a full name in Power Query.

Create and transform a new customer IDs column in the Power BI Desktop data model by duplicating the email column, stripping domain names, capitalizing IDs, and applying clean-up steps.

Use Power BI and Power Query to create a customer IDs column from email addresses by duplicating the email field, extracting text before @, then cleaning and capitalizing before applying.

Explore how to build and mark a date table in Power BI with Power Query, enabling time-based analyses using day name, start of week, month, quarter, and year.

Change locale to format dates in Power BI by transforming data in Power Query, converting UK formatted dates in Excel to USA format, and cleaning the query.

Create a dynamic rolling calendar in Power BI using a start date parameter and list.generate, then convert to a date table and add day name, year, and quarter on refresh.

Update the calendar table in Power BI Desktop by adding month number, month name, year, and start-of-year columns to enhance analytics of sales trends.

Learn to extend Power BI Desktop calendar table with additional date fields, including month, month name, year, and start of year, via Power Query to analyze sales trends over time.

Learn to add index and conditional columns in Power Query Editor for Power BI Desktop, including starting values and if-then-else logic for freight charges.

Create calculated columns as close to the data source as possible—prefer SQL Server, then Power Query, then DAX—and place them in dimension tables to boost performance.

Explore data aggregation in Power BI by using group by in Power Query to compute sums and totals, grouping by product key and customer key for actionable insights.

Pivot and unpivot columns with Power Query in Power BI Desktop, turning columns into rows and rows into columns, using don't aggregate, unpivot other columns, and transpose for data reshaping.

Learn how to merge queries in Power BI Desktop by performing a left outer join on two tables using the customer key, and understand when to merge versus build relationships.

Learn to append queries in Power BI by stacking tables with identical column structures, then explore using the folder option to consolidate multiple files into a single all sales table.

Use the folder option in power query to merge multiple csv files with identical columns into one sales file table, then automatically append new files by refreshing.

Learn to manage and fix data connections in Power BI Desktop using data source settings, change source to update file paths for renamed or moved CSV files and folders.

Learn to dynamically switch data sources in Power BI Desktop by parameterizing the server and environment, enabling seamless transitions between Adventureworks 2022 and 2023 schemas across development and testing.

Refresh data sources in Power BI and selectively exclude unchanged dimension tables, then organize queries into groups like parameters and staging for a cleaner project.

Import an entire Excel data model into Power BI to preserve data source, connections, query steps, hierarchies, and calculated columns and measures, with a demo of the import process.

Master best practices for Power Query in Power BI by preparing data before loading, organizing files, loading only needed data, and using the query editor for cleansing and transformation.

Master the foundations of data modeling in Power BI, including normalization, dimension and fact tables, keys, and cardinality, and explore star and snowflake schemas, hierarchies, and filter flow.

Explore data modeling by connecting four tables via relationships and primary and foreign keys, enabling cross-table analysis and accurate totals in power bi without heavy joins.

Learn how normalization organizes data into separate product, customer, and transaction tables, uses unique IDs to reduce redundancy, guard data integrity, and enable efficient querying in Power BI data models.

Differentiate fact (data/transaction) tables from dimension (lookup) tables in data modeling. Connect facts to dimensions using shared key columns to filter and analyze sales by date, customer, and product.

Explore how primary keys and foreign keys define and connect fact and dimension tables in a Power BI data model, identifying keys in dim date and dim customers.

Explore why building proper table relationships in Power BI, using Power Query and DAX, beats merging fact tables, calendar dates, product details, and customer info into one table, boosting performance.

Explore Power BI's model view to create and manage table relationships, using drag-and-drop or the manage relationships tool to define many-to-one links.

Edit and manage relationships in your Power BI data model with the Manage relationships dialog, editing keys and cardinality, and creating, deleting, or adjusting cross filter direction.

the lecture explains star and snowflake schemas as multidimensional data warehousing models, detailing fact and dimension tables, sub dimension tables, and their relationships using a sales example.

Remove connections, build a Power BI star schema with sales date, customer, product, and territories, link product tables in a snowflake pattern, and verify order quantity via the matrix visual.

Delete and recreate all relationships in Power BI to reestablish a star schema, then map snowflake connections through product subcategory and product category keys, and verify visuals across dimensions.

Learn to manage active and inactive relationships between the date table and sales data, including order date and due date, noting that only one active relationship exists at a time.

Explore how cardinality defines unique values, and how one-to-many relationships, including 1-to-1 and many-to-many, shape Power BI model design with examples from sales and dim product.

Connect multiple fact tables to shared dimension tables in Power BI Desktop, linking damaged goods to dates, products, and territories to enable cross-table filtering and correct aggregations.

Understand how filter context flows from dimension to fact tables in a waterfall model, and how using the correct territory key yields accurate sales and damages totals in Power BI.

Master bidirectional cross filtering in Power BI Desktop, understanding how both directions flow filter context between fact and dimension tables and when to avoid it.

Hide fields in the report view using the eye icon to prevent incorrect filtering by foreign keys and encourage using primary keys in dimension tables in Power BI Desktop.

Create and manage custom model layouts in Power BI Desktop to highlight specific tables and relationships, with synchronized changes across layouts and related table additions.

Diagnose cause of filter flow issues in the Power BI model by replicating Harvey's matrix, uncover why sales data for products 321 and 323 are missing, and hide foreign keys.

Diagnose missing damages data for products 321 and 323. Replicate Harvey's model by adjusting product key relationships and cross-filter direction, and hide foreign keys to restore order and damages totals.

Format data and apply categorization in power bi desktop by adjusting date and currency formats in the table view and columns tool, and by marking fields as continent or country.

Create data hierarchies in Power BI by grouping related fields into levels, such as territory group, country, and region, enabling drill down and easier exploration.

Create a date hierarchy in Power BI Desktop to explore time series by year, month, week, and date, then apply it to a matrix visual and navigate levels.

Create a date hierarchy in Power BI by adding start of year, start of month, start of week, and date, then drill up and down to test.

Design a normalized data model, set primary and foreign keys, and include a date table; use a waterfall layout with dimension tables above data tables and simple one-to-many relationships.

Learn to use DAX data analysis expressions to create calculated columns and measures, apply row and filter context, and master calculate and other functions for time intelligence.

Explore Dax, the data analysis expressions language for Power BI Analysis Services and PowerPivot in Excel, with about 200 functions, including calculated columns and measures for data modeling and visuals.

Explore the differences between M-code and DAX in Power BI Desktop, with M handling ETL in the Power Query editor and DAX driving calculations and aggregations in the data model.

Create calculated columns to add per-row properties in a Power BI data model using row context, with values computed per row and stored in the model, separate from measures.

Explore DAX measures and how they compute values within a data model, adapting to filter context in visuals, with implicit aggregations like sum of order and damage quantity.

Explore implicit versus explicit measures in Power BI Desktop, learn to create explicit measures with DAX, understand nesting, and optimize visuals with precise calculations.

Explore how quick measures in Power BI Desktop create explicit measures via templates or natural language queries, covering 19 calculations across five categories, with guidance on verification.

Calculated columns work on row context, adding fixed values to a table and increasing file size, while measures use filter context to compute aggregates in visuals.

create and organize measures in power bi by using a dedicated measures table, built with enter data or dax table constructors, and group measures with folders in the data model.

Learn how filter context determines DAX measure calculations across visuals, slicers, and totals, using matrix, donut charts, and date filters to reveal context-specific results.

Explore how DAX measures calculate values by applying filter context, propagating through table relationships, and evaluating against the filtered fact table, illustrated with a black color example.

Master DAX syntax and operators to build measures and calculated columns, using sum on sales amount in the sales table with fully qualified column names and filter context.

Explore the major DAX function groups used in Power BI, including text, math and stats, iterator, logical, date and time, filter, table, and relationship functions.

Master DAX maths and statistics functions such as min, max, sum, average, and divide, and learn to create explicit measures in Power BI for dynamic visuals.

Explore DAX counting functions in Power BI, including count, counta, distinct count, countrows, and count blank. Learn build measures like total damages claims and total orders to suit business needs.

Create two Power BI measures: a distinct active customers count and a damages rate defined as damages claim divided by quantity sold, organized into folders to avoid clutter.

Create two measures in Power BI: a distinct count of active customers from sales data, and a damages rate ratio of claims to quantity sold, organized into folders.

Organize your measures in Power BI desktop by creating subfolders, sharing measures across folders, and placing frequently used measures at the top for easier access.

Master DAX logical functions including and, or, if, iferror, and switch, with per-row evaluation, then apply them in Adventure Works to build calculated columns like a parent flag.

Master the switch function in Power BI Desktop by mapping expressions to values using value and result pairs, else clauses, and true expression to create calculated columns.

Apply logical functions in Power BI to create calculated columns in the dim customer table: customer rank, income level, and education category mapped by priority, thresholds, and a switch function.

Create three calculated columns in the dim customers table using dax to define customer rank, income level, and education category with nested ifs and a switch.

Explore text functions in DAX within Power BI, including len, upper, lower, concatenate, left, right, mid, substitute, and search, with hands-on examples creating new name and month short columns.

Solve the text functions assignment by capitalizing the first three letters of the month and creating a unit key from the product alternate key after the first hyphen.

Explore Power BI text functions to uppercase month abbreviations and build a unit key from the product alternate key using left and search to extract four characters after the hyphen.

Explore DAX date and time functions in Power BI, including today, now, weekday, calendar, and date difference, and apply them to dim dates to create day-of-week and start-of-week indicators.

Learn to apply date functions in Power BI by adding a birth year column that extracts the year from birth dates in the customer table, enabling age-based insights for segmentation.

In the Power BI solution, convert birth date fields to short date format, then create a birth year column using the year function.

Learn to use the related function to pull values from dimension tables into a sales file, building calculated columns within one-to-many relationships.

Explore the DAX calculate function in Power BI, learning how it modifies filter context, handles expressions and filters, and creates flexible measures like sizable orders and weekend orders.

Explain why matrix totals misalign with the final row in Power BI, driven by filter context and a distinct count total orders measure in the AdventureWorks dataset.

Use the calculate function to create measures like big damages and bike damage rate. Build a month-by-month matrix for bike damages and analyze bike sales to inform an escalation plan.

Develop bike-related insight by building calculate-based measures for bike damages, bike sales, and bike damage rate in Power BI, using Adventureworks data to explore trends.

Master the DAX all function in Power BI, which returns all rows or values while ignoring filters, enabling context-free calculations and percent of all orders.

Develop two Power BI measures using calculate and all to count all damages claims regardless of filters. Display a matrix showing the percentage distribution of damages claims by product category.

Create two DAX measures in Power BI Desktop to compute all damages claims and the percent of all damages claims, then display results in a matrix by category name.

Learn how the DAX filter function returns a table subset by a boolean expression per row, enabling context transition and dynamic, measure-based filtering with calculate.

Learn how DAX iterator functions, or X functions, iterate over table rows to compute aggregates with a table argument and a scalar expression, using SUMX and related.

Create a total cost measure by multiplying order quantity by the standard cost and summing. Then define total profit as revenue minus cost and display yearly profits in a matrix.

Follow a Power BI desktop walkthrough to create total cost and total profit measures using sumx and related, format as currency, and build a year-wise profit visual.

Explore time intelligence in DAX with ytd, qtd, and mtd, and running totals using calculate over a date table to analyze period-based performance in Power BI Desktop.

Implement time intelligence in Power BI Desktop by integrating previous month damages claims, orders, and profit, and add 5% targets plus a 100-day rolling profit for month-over-month and year-over-year comparisons.

Generate time intelligence in Power BI by calculating previous month damages claims, orders, and profit. Use date add and max or last date function for a 100 day rolling profit.

Master dax practices in power bi desktop using calculated columns for filtering and measures for aggregation. Create explicit measures for flexibility while understanding filter and row context to optimize calculations.

Master advanced DAX techniques, tidy code, and error handling; leverage variables, testing, and the calculate function with modifiers, plus concatenateX and time intelligence for real-world visuals.

Learn essential dax keyboard shortcuts in power bi desktop to write and debug measures faster, including intellisense, line editing, indentation, and quick navigation.

Format DAX code to reveal each function, variable, and value clearly. Learn a sales year-on-year growth measure using calculate, parallelperiod, dates in period, and lastdate, with indentation in Power BI.

Learn how to add single-line and multi-line comments in DAX, place them in measures like the 100 day rolling profit, and improve readability in Power BI.

Learn how to use DAX error handling in Power BI, including iferror, isblank, and divide, and apply defensive data quality strategies via Power Query to keep reports accurate.

Learn DAX variables, declare them in a declaration expression, and return with the return expression; improve readability and performance by evaluating once and reducing redundancy in measures like orders from females.

Master the evaluation order for variables in DAX, why a variable is fixed once defined, and how calculate inside a variable yields correct filtering for orders from females.

Discover how to debug DAX by breaking a complex measure into variables, test each part, and return any variable to pinpoint issues and fix problems in Power BI DAX.

Explore modifiers for the calculate function in Power BI Desktop to adjust filter context, switch filter flow with cross filter, and use inactive relationships with use relationship and all.

Apply the remove filters modifier in Power BI to clear filters from specified tables or columns, create a grand total of orders, and compute the percent of total orders.

Use the key filters modifier to keep existing filters while calculating, creating a new filter context that behaves like an inner join, illustrated with Canada orders.

Learn to build a Power BI matrix displaying product categories by country (USA, Canada, United Kingdom), create country-specific measures, and compute a consolidated percentage of country orders using remove filters.

Create three country-specific measures for United States, Canada, and United Kingdom orders and a percent of country orders measure to break down product categories by country in Power BI.

Explore advanced uses of the calculate function to build cumulative totals for sold quantity and percent of total revenue using modified filter contexts in a Power BI Adventureworks dashboard.

Explore table and filter functions in Power BI, learning to generate columns and tables, filter data, add or summarize columns, and create data across calculated, filtering, manipulating, and generating tables.

Explore how Dax functions with table arguments can operate on real tables like sales files or dim products or on calculated virtual tables created with filter and distinct.

Master the distinct function in Power BI to extract unique values or combinations from a column, table, or table expression, and create lookup or dimension tables for accurate measures.

Discover how the values function in Power BI returns duplicates for table name, or unique values for a column name, and build a styles dimension to slice totals by style.

Master physical and virtual relationships in Power BI Desktop, including one-to-many links, active and inactive connections, and DAX expressions to connect tables with different granularities.

Explore how the uniqueness of column values drives iterator cardinality and affects dax performance, contrasting physical and virtual relationships and their impact on nested iterators.

Explore the concatenate x function in Power BI to combine English product name and model name, using a delimiter and optional order by expression with ascending sorting.

Create dynamic labels in Power BI reports by using the concatenate x function to capture slicer selections and display them on a card or matrix, reflecting filter context.

Create a date table that covers dates, includes a date or date time column with unique values, splits date and time when needed, and marks date table for time intelligence.

Learn to build a calendar table in Power BI using the calendar function and DAX with start and end dates, producing a single date column and a customizable date range.

Learn how to create a reusable date table in Power BI Desktop using calendar auto and add columns, including defining fiscal year ends and custom date columns.

Explore time intelligence functions in Power BI to perform YTD, MTD, and QTD calculations, compare periods, and compute running totals using a date table.

Learn how to use the parallel period function in Power BI to shift dates by month, quarter, or year, build a last quarter sales measure, and verify quarterly totals.

Explore the previous quarter DAX function in Power BI, comparing it to parallel period and building a calculate-based measure for last quarter sales across months.

Learn how the same period last year function in Power BI pulls prior year sales from a chosen dates column and a date slicer, enabling year-to-date and last-year comparisons.

Apply time intelligence in Power BI to compute new customers within a period by building life to date and prior counts, using dates between and measure logic.

Master advanced dax techniques by using variables in measures, mastering iteration functions, time intelligence, branching, pre-written measures, and robust error handling to deepen analysis.

Learn to design dynamic, interactive dashboards in Power BI Desktop by applying data visualization best practices, using bookmarks, parameters, tooltips, navigation tools, and row level security.

Master data visualization best practices by identifying data types, choosing the right visuals for distributions, comparisons, compositions, and relationships, and tailoring dashboards to analysts, managers, and executives.

Explore how analytics dashboards turn raw data into actionable insights by integrating real-time data from multiple sources, KPIs, and AI-assisted data preparation to support data-driven decisions.

Design a multi-page Adventureworks dashboard focused on KPIs, regional trends, product details, and high-value customers using time series data and geospatial maps. Arrange KPI cards and charts for executive insights.

Master creating multi-page reports in Power BI Desktop by using report view to add, rename, and arrange pages and visuals, apply themes, and integrate shapes and images.

Master format and selection panes in Power BI Desktop to customize visuals, adjust data fields, control z index, and rename and group objects for clean, organized reports.

Design and format KPI cards in Power BI Desktop using the card visuals to display revenue, profit, orders, and damages rate with precise sizing and styling.

Develop and configure KPI cards on the customer detail report in Power BI to display total unique customers and revenue per customer, mirroring the executive dashboard format.

Implement KPI cards on the customer detail page in Power BI, display number of customers and revenue per customer via APIs, and adjust callout fonts and visuals.

Master on-object formatting in Power BI to edit chart elements directly on visuals, using drag-and-drop fields, contextual menus, and the format pane for bar, line, pie, and more.

Add and customize line charts in Power BI Desktop, setting x and y axes with start of month and revenue, then profit, with tooltips, colors, and zoom options.

Explore how to add trend lines and forecasts in Power BI visuals, customize their style and transparency, and adjust forecast horizon, confidence intervals, and granularity to sharpen data insights.

Integrate a monthly customer count line chart into the customer detail report, displaying monthly totals with a trend line and a zoom slider for the x axis. Activate tooltips and format them to match the line chart on the executive dashboard.

Demonstrate building a monthly line chart in Power BI Desktop to visualize customer base trends, align tooltips with the executive dashboard, and apply precise styling and a zoom slider.

Explore how kpi visuals in Power BI transform dashboards by adding trend axes and targets with callouts, turning revenue and orders data into actionable insights.

Break down orders by product category with a donut chart, then switch to a bar chart for clearer comparisons among accessories, bikes, and clothing. Apply legend, values, and data labels.

Explore how to use the filters pane in Power BI Desktop to control cross-filtering across visuals, and apply visual, page, or all-pages filters.

Create a donut chart of total orders by occupation and a treemap by income level, with a chart title, data labels category and value, font size eight, and top-three filter.

Explore a Power BI solution that builds a donut chart and a treemap to visualize total orders by occupation and by income level, with top-n filtering and formatting.

Master Power BI visuals by choosing between tables and matrices; use tables for flat 2D data, and matrices for multi-dimensional drill down with rows, columns, and values.

Master conditional formatting in Power BI Desktop to color and enhance matrix visuals with data bars, icons, and background colors, based on numeric values.

Apply a top N filter in a Power BI visual to show the top 25 products by a chosen measure. Sort and refine the results for meaningful insights.

Update the products header and create Power BI tables—one with customer keys, full names, orders, revenue; the other with LTT and new customers—applying conditional formatting and a top-100 orders filter.

Format two Power BI tables on the AdventureWorks dashboard: a top 100 customers table with keys, full names, orders and sales, and a monthly life-to-date vs new customers table.

Learn to create a top-ranked text card in Power BI using DAX, with CALCULATE, the selected value function, and the top end function to show the product by total orders.

Integrate a top n card into Power BI desktop report to display revenue customers' names, revenue, and orders; duplicate the card for orders and revenue; add text boxes for titles.

Demonstrates building top N cards in Power BI to display the top customer by revenue and orders, using advanced filters to ensure not blank names and precise sorting.

Explore the new card visual in Power BI Desktop, learn to add multiple fields to a single card, and customize styling, tooltips, drill through, and reference labels to enhance dashboards.

Learn to format Power BI card visuals by adding icons and images, adjusting image size and layout, and using reference labels and conditional formatting to show revenue, targets, and gaps.

Create an advanced formatting for the new card visual in Power BI by using a revenue gap measure with unichar up and down arrows and currency formatting.

Learn to create measures for the orders and damages card visuals in Power BI Desktop, show previous month and target statistics, and format them for the executive dashboard.

Build a Power BI solution for the new card visual by creating measures for previous month orders, order gap, damages gap, and applying conditional formatting and arrow indicators.

Learn to add a spark line chart to a Power BI card using an SVG template, create an area spark line measure, and update visuals to reflect total revenue.

Explore Power BI map visuals, including basic map, field map, ArcGIS maps, shape map, and Azure maps, using geospatial data and bubble sizes based on total orders, with controls.

Explore slicers in Power BI to filter reports with visual controls, from date and numeric slicers to tiles, with options like show select all and reset buttons.

Learn to add a slicer visual to the executive dashboard, and a date slicer to the customer report, enabling year and date filtering and eliminating blank years.

learn to implement a slicer visual in Power BI Desktop, setting up an executive year slicer and a customer date slicer, with copy-paste steps, basic filtering, and formatting.

Power BI's new button slicer offers flexible, single-field filtering with customizable button shapes, rows and columns, overflow styles, and image backgrounds, plus hover, click, and select states.

The DAX HASONEVALUE checks if one distinct value remains after filtering. It cannot be used in direct query mode for calculated columns or row-level security in Power BI measures.

Master radial gauge charts in Power BI to visualize progress toward KPI targets using gate charts for orders, revenue, and profit, driven by product and date slicers.

Learn to format advanced gauge charts in Power BI by creating measures for target gaps in orders, revenue, and profit, and applying dynamic color rules using the format pane.

Master area charts in Power BI to visualize time-series data, compare total profit and damages claims with layered visuals, secondary axis, and flexible formatting.

Learn how to drill up and drill down in Power BI, using date hierarchy to switch between weekly, monthly, and daily granularity with drill mode and visual icons.

Update the customer detail line chart to include a date hierarchy and enable interactive drill up/down from the header, then test drill mode and default to monthly data.

Demonstrate a Power BI drill up and down solution, enabling day and annual overview from Gloria Watkins' request, by adjusting date hierarchy and managing incomplete data on the Adventureworks dashboard.

Enable cross report drillthrough in Power BI to navigate between related reports, passing matching fields and drillthrough filters from the source to a target page.

Explore editing report interactions in Power BI Desktop to control cross filtering and highlighting across visuals, tailoring how a map, matrix, bar, and line charts update.

Fix report interactions in Power BI by ensuring line chart, donut, and treemap filter with customer selections, table does not, and the date slicer filters all visuals.

Learn Power BI desktop report interactions by enabling edit interactions, converting highlights to filters on line, donut, and treemap visuals, and syncing a date slicer.

Create and use bookmarks in Power BI desktop to capture a report page state, including filters, slicers, and visuals, and return users to a default view for seamless navigation.

Explore customer data by adjusting filters in Power BI Desktop, then create bookmarks to highlight insights and clear all filters, linking an information button to the Customer Insight bookmark.

Highlight noteworthy insights or emerging trends in the report by creating bookmarks that draw attention to key stories and add a 'clear filters' bookmark tied to a button.

Create custom navigation buttons in Power BI to link four pages, executive dashboard, map, product detail, and customer detail, with hover and press icon changes and tooltips.

Create a compact slicer panel in Power BI Desktop by assembling a button, panel, and slicer, then use bookmarks and actions to show or hide it without disturbing other filters.

Create numeric range and field parameters in Power BI desktop, bind them with slicers to drive measures and visuals, and explore scenarios via a percent adjustment parameter and adjusted profit.

Power BI field parameters let users adjust reports and visuals by selecting options, enabling input controls for filtering, sorting, grouping, or aggregating data across charts, tables, and graphs.

Introduce a fields parameter named customer metric with total customers and average revenue per customer, add it as a slicer in the customer detail report, and format for tile style.

Implement a field parameter slicer in Power BI to switch metrics like active customers and revenue per customer, binding it to visuals with a dynamic title.

Create and customize Power BI tooltip pages linked to visuals to show additional data on hover, using dedicated tooltip pages, canvas sizing, and field and measure triggers.

Learn to create a customized tooltip in Power BI Desktop, featuring a treemap, a donut chart of orders by occupation, and a customer perspective matrix, harmonized to the dashboard theme.

Create a custom tooltip in Power BI Desktop that shows the customer perspective with a donut chart of orders by occupation and measures like active customers and revenue per customer.

Learn to augment Power BI desktop visuals by importing custom visuals from Appsource. Build a dynamic dashboard using measures like total orders, revenue, and profit.

Configure and view row-level security rules in Power BI Desktop to restrict data access by role. View data through territories like Europe, North America, and Pacific.

Create mobile-optimized report pages in Power BI by switching to the mobile layout view, dragging visuals onto the mobile canvas, and adjusting font sizes for the Power BI mobile app.

Publish Power BI desktop reports to the cloud Power BI service, a SaaS platform for dashboards, sharing, and data analysis, with interactive cross-page viewing.

Master best practices for data visualizations in Power BI Desktop by simplifying visuals, choosing the right charts, ensuring consistent design, enabling interactivity, and optimizing performance and accessibility.

Explore Power BI's artificial intelligence capabilities, including anomaly detection, smart narratives, Q and A visuals, decomposition trees, and key influencer visuals to enhance data insights and decision making.

Power BI's anomaly detection for line charts automatically flags deviations in time series data using statistics and machine learning, with adjustable sensitivity and window for explanations in Power BI service.

Discover how smart narrative summaries in Power BI generate dynamic text insights from visuals, highlighting trends in revenue, orders, and profits with cross filtering.

Explain how the Q&A visual uses natural language to generate visuals from questions, and how to train it with synonyms and tuning for accurate results in Power BI.

Explore how the decomposition tree in Power BI Desktop automatically analyzes data, drills down by category, and uses AI splits to identify highest and lowest values for root cause analysis.

Explore how the key influencers visual in Power BI identifies factors affecting a metric, using linear and logistic regression and decision trees to rank impact and compare segments.

Explore Power BI optimization tools, including the optimize ribbon, pause and unpause visuals, optimization presets, clear all slicers button, Performance Analyzer, and tools for semantic modeling, data analysis, and accessibility.

Explore how the optimize ribbon helps Power BI report authors configure reports, especially for direct query data sources, with parsing queries, optimization presets, the performance analyzer, and slicer actions.

Pause visuals in the Power BI Desktop optimized ribbon to halt visual queries and keep visuals paused while refreshing individual visuals. Resume visual queries to update all visuals.

Explore optimization presets in Power BI desktop that quickly apply query reduction or interactivity, with customize options to fine tune settings and apply slicer changes.

Apply all slicers and clear all slicers buttons streamline Power BI reports by applying or clearing selections with one click, reducing unnecessary visual queries.

Use the Performance Analyzer in Power BI Desktop to record visuals and DAX queries, analyze milliseconds for query load and visual render, and identify optimization opportunities.

Explore external tools in Power BI Desktop, including Dex Studio, Tabular Editor, and Bravo, to enhance data modeling, analysis, and model optimization with third-party applications.

Discover the DAX query view in Power BI Desktop, a preview tool for crafting and running DAX queries (evaluate, define, order by, sumx) against semantic models, returning tabular results.

Explore how to define and evaluate DAX measures in Power BI, use summarize columns and group by, and view results in the DAX query view with Performance Analyzer.

Discover how the model explorer enhances semantic models and how calculation groups consolidate explicit measures, enabling dynamic time intelligence, currency conversion, and daily averages with simple DAX items.

Create calculation groups in Power BI to compute daily and monthly averages from the date table, consolidating measures and enabling dynamic matrix visuals with a metric selector.

Explore time intelligence in Power BI by building calculation groups, applying DAX time functions (MTD, QTD, YoY), and formatting measures for dynamic, reusable analytics.

Create DAX-like expressions directly on a visual with a grid-like, Excel-style interface. Reference only the data visible on the visual, offering simpler, faster calculations.

Learn to create and format visual calculations in Power BI using matrix visuals, including running sums, moving averages, and percent of parent or grand total.