Microsoft Power BI Desktop for Business Intelligence

Explore Power BI Desktop and what it's used for in business intelligence, including installation, settings, interface, and the business intelligence workflow for the course project.

Discover how Power BI Desktop enables self-service analytics by connecting, transforming, and loading data, building relational models with DAX, and delivering interactive reports and dashboards.

Configure Power BI desktop by enabling global preview features and setting English United States as the locale, while disabling auto relationships and time intelligence auto date time.

Explore practical resources and monthly updates for Power BI, including help options, blogs, videos, and user groups, and stay current with Power BI Desktop, Service, and Power Platform updates.

Power BI offers a robust connector library to access data from flat files, including CSV, databases, online services, and more, using the get data dialog box and the query editor.

Master Power Query Editor in Power BI to shape data with queries and applied steps; discover M code and the Home, Transform, and Add column tools for automated data cleansing.

Learn to apply basic table transformations in Power BI’s query editor, including keeping or removing columns and rows, promoting headers, and adjusting data types.

Create two Power BI queries to connect to product category and subcategory CSV files, promote headers, add SKU Type, replace zeros in Product Style with NA, and load data model.

Provide a solution walkthrough for Power BI table transformations: connect to product category and subcategory lookups, transform the product lookup, add a sku type, and load four tables.

Explore the four storage and connection modes in Power BI: import, direct query, composite models, and live connections. Understand when to use each to optimize performance and data freshness.

Connect to a database in Power BI with Power Query, enter server credentials, use advanced options, and load or keep tables in the query editor for QA.

Use the web connector to scrape tables from a web page, preview and import table into Power Query, adjust data types, rename to largest asset management firms, and disable load.

Explore data profiling tools in Power BI to assess column quality, distribution, and profile; identify and clean errors and empties, and review distinct counts, uniques, min, and max.

Learn to use Power BI text tools—split, format, trim, extract—in the Transform and Add Column tabs, then merge columns to create a full name in a customer table.

Create a domain name column from emails by duplicating the email column, extracting the domain, cleaning and capitalizing it, then saving and applying changes in Power BI Desktop.

Explore Power BI and Power Query to extract the domain from email addresses, remove the .com portion, replace hyphens with spaces, and capitalize words for clean domain names.

Explore number tools in the Power BI query editor, including statistics functions (count, min, max, median, average, standard deviation, count distinct) for exploration, and per-row math and rounding examples.

Learn to compute the average product cost, count colors, determine distinct customers, and identify the maximum annual customer income in Power BI, while restoring tables afterward.

Validate key metrics in Microsoft Power BI Desktop for business intelligence using the numerical tools walkthrough, calculating average product cost, distinct colors, distinct customers, and maximum income.

Learn to use date and time tools in Power BI query editor to build a calendar table from a date column, including start of week and start of month calculations.

Learn how to fix date import errors across locales by using 'using locale' in Power BI, setting date data type, and applying the correct English locale (UK) for accurate parsing.

Build a rolling calendar in Power BI using M code to generate a dynamic date table that updates with the current date.

Add date fields to the calendar table in Power BI to analyze sales trends over time, including month name, month number, start of year, and year.

Add calendar table columns in Power BI by selecting the date column in the query editor, then create month name, month number, start of year, and year columns.

Explore index and conditional columns in the Power BI query editor, create a Quantity Type from Order Quantity, and organize queries for a cleaner sales data model.

Add calculated columns as close to the original data source as possible to optimize Power BI performance, using the query editor when needed and front-end as a last option.

Group and aggregate data in Power BI Desktop using the Transform tab to roll up daily transactions. Group by product key and customer key to produce a total quantity summary.

Use dynamic data source parameters in Power BI to switch between development and production schemas. Create server and database parameters, configure values, and update queries in the M code.

Learn to manage refreshing in Power BI: use the home tab to refresh all queries, then deselect include in report refresh for lookups and rolling calendar, refreshing only sales data.

Import a full Excel data model into Power BI Desktop to preserve model details, including data source connections, queries, and DAX measures. Build in Excel and import for reporting.

Learn Power Query best practices for connecting and shaping data in Power BI Desktop. Organize table names and folder structures, optimize refresh for static sources, and load only needed data.

Build a foundational relational model in Power BI by learning normalization, fact and dimension tables, and primary/foreign keys, then master cardinality, filter flow, and basic schemas like star and snowflake.

Discover how data modeling connects independent tables with relationships and primary and foreign keys to enable cross-table filtering and accurate aggregation in Power BI.

Learn database normalization: organize a relational model to reduce redundancy, preserve data integrity, and simplify queries by splitting into separate tables for transactions and products, linked by product IDs.

Learn how fact tables carry numerical metrics and dimension tables hold descriptive attributes to filter and group data, and how date and product ID keys connect them.

Explore the difference between relationships and merged tables in Power BI, avoid redundancy and a monster frankentable, and build efficient relational models with multiple small tables.

Configure your data model in Power BI Desktop by creating table relationships through drag and drop or the manage relationships dialog, linking primary and foreign keys to enable cross-table analysis.

Manage and edit relationships in the Power BI model view using the Manage relationships dialog, adjusting primary keys, cardinality, cross-filter direction, and active status, or delete and recreate links.

Understand the model schema by comparing star schemas with a single fact table and surrounding dimensions to snowflake schemas with sub-dimension relationships, including how sales data links to product categories.

Delete all table relationships, then build a star schema with sales, calendar, customer, product, and territories, then a snowflake schema linking product, subcategory, and category, and verify with a matrix.

Demonstrates cleaning and rebuilding table relationships to form a star schema across sales, calendar, customer, product and territory. Constructs snowflake schema for product lookups and validates filtering with matrix visual.

Learn to toggle active and inactive relationships in Power BI. Link either order date or stock date to the calendar date and switch with edit relationship or the properties pane.

Connect multiple fact tables through shared dimension lookups to enable cross-filtering of sales and returns, while noting missing customer keys limit breakdowns and introducing filter flow.

Explore how filter context and filter flow propagate through the territory lookup to sales and returns data in Power BI, using arrows to show upstream and downstream directions.

Explore bi-directional filtering in Power BI, where cross-filter direction can be set to Both, allowing filter context to flow between sales, territory lookup, and returns, with caution about ambiguity.

Hide fields from report view in Power BI Desktop to prevent filtering on invalid fields. Use hidden fields to enforce primary keys from dimension tables and reduce clutter.

Diagnose filter flow issues in a Power BI model by reproducing a matrix to uncover why product 338 shows no orders. Learn to prevent recurrence by hiding remaining foreign keys.

Build a Power BI matrix for product key with order quantity and return quantity, diagnose missing product 338, and apply a two-way then single cross-filter with hidden keys.

Create custom model layouts in Power BI Desktop to build focused sales and returns views, sync changes across views, and use related tables to keep diagrams organized without duplicating data.

Customize data formats and data categories in Power BI, using Data view and Model view, and learn how formats affect date, currency, and geospatial displays.

Create custom hierarchies in Power BI by grouping continent, country, and region into levels, then use drill up and down in visuals.

Create a date hierarchy from start of year field, adding start of month, start of week, and date, then apply it to the matrix visual for drilling up and down.

Create a date hierarchy with start of year, start of month, start of week, and date, add it to matrix visual, and drill up and down to time series levels.

Build a normalized data model with clear table roles and 1-to-many relationships. Place dimension tables above data tables, avoid complex relationships, and hide fields to enforce filtering by primary keys.

Learn core DAX topics in Power BI Desktop for business intelligence by creating calculated columns and measures, exploring row and filter context, and applying time intelligence.

Learn DAX, the data analysis expressions language that powers Power BI, enabling calculated columns for filtering and measures for aggregation in visuals, with examples from AdventureWorks.

Compare M code and DAX in Power BI, with M code used in the query editor for data shaping and DAX for front-end data analysis.

Explore DAX calculated columns in Power BI, learn how per-row values use row context, and why they suit fixed, filter-friendly columns but not aggregations, reserving measures for totals.

Discover how DAX measures generate calculated values using filter context and become visible only in visuals. Compare implicit and explicit measures and how drag-and-drop creates auto aggregation in Power BI.

Compare implicit and explicit measures in Power BI. Implicit measures auto-sum within a single visual, while explicit measures use DAX and are portable across the report for nested calculations.

Explore Power BI quick measures: calculations with templates for weighted averages, variance, time intelligence, and running totals, plus natural language suggestions to create explicit measures, then validate results.

Contrast calculated columns and measures: calculated columns store static values per row (row context) and enlarge the model; measures use filter context and recalc with report filters in visuals.

Create a dedicated measure table to store explicit measures, organize them in folders, and choose between using enter data or DAX table constructors to add it to the model.

Explore how filter context governs DAX measures in Power BI, including row and total calculations, and how page level filters and drill-down interactions shape each measure.

Discover how Power BI evaluates measures via a three-step filter context: detect and apply, propagate to related tables, then sum filtered order quantities for black color.

Master the DAX core syntax, from measure references and function names to naked column references vs aggregations, and using fully qualified columns; cover common operators and calculated fields for AdventureWorks.

Learn to build DAX measures in Power BI using sum, average, max, min, and divide, compare implicit vs explicit measures, and explore data by category and subcategory in visuals.

Explore counting functions in Power BI, including count, counta, distinctcount, and countrows, and learn to apply them to columns and tables for totals like total returns and total orders.

Create two measures in Power BI: total customers to count distinct customers with transactions, and return rate as quantity returned divided by quantity sold.

Explore conditional and logical functions in Power BI, including if, iferror, switch, and, or, with a hands on example of creating a parent calculated column from TotalChildren using row context.

Explore the switch function in DAX, evaluating an expression against values to return corresponding results, including the switch true pattern for efficient else logic and common pitfalls.

Create calculated columns in the customer lookup table to support customer segmentation in Power BI Desktop: define Customer Priority, Income Level, and Education Category with conditional logic and SWITCH.

Create calculated columns in the customer lookup table for customer priority, income level, and education category in Power BI, using if statements and switch to categorize education.

Explore text functions in Power BI, including length, concatenate, left, mid, right, substitute, and search, and learn practical techniques for building calculated columns with ampersand for flexible concatenation.

Explore text functions in Power BI Desktop by capitalizing the month short column with upper and extracting SKU category from product SKU using left and search for the first hyphen.

Learn basic date and time functions in Power BI, including today, now, day, month, year, hour, minute, second, weekday, week number, end of month, and DateDiff with practical DAX examples.

Extract date parts in Power BI with the year function to derive birth year from birthdate. Learn how year, quarter, month, and day support calculations in a customer lookup table.

Learn to use the related function to pull values from a linked table into a calculated column and compute revenue by multiplying retail price by quantity across a one-to-many relationship.

Learn how the dax calculate function modifies filter context to evaluate expressions under simple boolean filters, override existing context, and enable flexible measures like weekend orders.

Discover how DAX totals in a matrix use filter context and distinct count, revealing why total orders differ from the sum of category rows.

Create measures for bike returns and bike sales in Power BI, build a matrix by start of month, and calculate the bike return rate to analyze trends.

Create Power BI measures for bike returns, bike sales, and bike return rate using CALCULATE with category name equals bikes; visualize by start of month to assess trends.

Master the all function in Power BI, using calculate to remove filters from a table or column, create unfiltered totals, percent of all orders, and overall averages.

Create two measures in Power BI: all returns and percent of all returns, then build a matrix by product category to show return shares.

demonstrates building two measures in Power BI—all returns and percent of all returns—using calculate and divide to ignore filters, then builds a matrix of percent by category.

Explore DAX iterator functions (X functions) like SUMX to loop over table rows, apply row-level expressions, and aggregate results, replacing columns with measures for efficiency.

Create a total cost measure multiplying order quantity by product cost and summing it; then calculate total profit as revenue minus cost and display profit by year, including 2022 AdventureWorks.

Develop a Power BI iterators workflow by creating a total cost measure with sumx, a total profit measure from revenue minus cost, and a yearly profit matrix.

Explore time intelligence patterns in DAX, including ytd, mtd, and qtd totals, previous period, and running totals, using CALCULATE, DATEADD, and DATESINPERIOD with a calendar table.

Apply time intelligence functions to add six measures: previous month returns, orders, and profit; 10% targets; and a 90-day rolling profit to the data model for month-over-month and year-over-year insights.

Master time intelligence in Power BI by building previous month returns, orders, and profit, plus a 90‑day rolling profit and target measures using a calendar date table.

Choose between calculated columns and measures, and create explicit measures for simple calculations. Use fully qualified references, move calculations upstream, and minimize iterator functions to improve performance.

Master visualizing data with Power BI by building dynamic interactive reports and dashboards. Apply best practices and use bookmarks, drillthrough, filters, parameters, tooltips, and row-level security for mobile layouts.

Identify the three key questions—data type, communication goal, and audience—to choose effective visuals in Power BI, from geospatial and time series data to histograms and scatter plots.

Apply a six-step dashboard design framework; define purpose and audience, choose metrics, present clearly with layout that reduces clutter, and craft a data-driven story.

Create a Power BI report by adding pages: executive dashboard, map, product detail, and customer detail, inserting images and shapes, and using format and view options to align.

Use the selection pane to rename and group report objects, like the left nav background and AW logo, for clearer pages. Group the KPI background cards to keep dashboards organized.

Create KPI cards with the card visual, populate total revenue and other measures, customize formatting (Segoe UI, 38, 20e2d7, 1 decimal), then copy, swap measures, and group into KPIs.

Create two Power BI card visuals on the customer detail report to show total customers and revenue per customer, duplicate to add a second card, and apply matching background shape.

Insert and build a line chart in power bi, set x-axis to start of week and y-axis to total revenue, then apply formatting and tooltip customization.

Add a trend line and forecast to Power BI line charts, customize with transparency, forecast units or points, ignore last periods, and adjust the confidence interval for clearer visuals.

Discover how KPI cards provide context by using trend axes and targets in Power BI, comparing current and previous periods for revenue, orders, and returns.

Learn to compare product categories with bar and donut charts, using legend and values to show total orders by category on an exec dashboard.

Learn how to apply visual, page, and report level filters in Power BI to control visuals and dashboards, including cross-filtering, top N, and advanced conditional options.

Explore building and formatting two Power BI donut charts that show total orders by income level and by occupation, with detail labels, legend off, and visual level filtering.

Explore conditional formatting in Power BI to enhance matrix visuals with data bars and colors. Apply subtle colorblind-friendly rules to orders and return rate using the format pane and fx.

Apply a top N filter to the matrix visual to show the top 10 products by total orders.

Create a Power BI desktop table visual for the customer detail report, showing customer key, name, orders, and revenue; apply top 100 by orders, add a chart title, and sort.

Apply top N filters to text cards in Power BI to show the most ordered and most returned subcategories, with clear titles and formatting.

Create top N text cards showing the top customer by revenue with full name; copy for orders and revenue, adjust the top N filter for accuracy, and format titles.

Practice top N text cards in Power BI by building three cards for the top revenue customer, filtering by customer key to ensure unique results, and formatting with styled callouts.

Learn to use Power BI slicers as visual filters that update maps and other visuals, with options like lists, tiles, dropdowns, and date or numeric range settings.

Add a year slicer to the customer report to enable filtering by year or multiple years, and apply a visual-level filter to exclude blank years above the customer cards.

Add a slicer on the customer detail page to filter by year from the calendar table, using the between style to select single or multiple years.

Discover how the DAX function HASONEVALUE drives robust top customer detail cards in Power BI, returning the single value or a dash when multiple customers exist to avoid confusing totals.

Create gauge charts to compare current month against targets based on previous month plus 10% for orders, revenue, and profit, using a product slicer and N filter for latest month.

Create target gap measures and use fx conditional formatting in Power BI to color call-out values red when below target, otherwise gray, across orders, revenue, and profit.

Master drill up and drill down in Power BI visuals by using a date hierarchy and visual header icons to switch granularity from weekly to monthly to daily.

Update the customer detail report to use a date hierarchy on the X-axis, drill up and down for daily to annual trends, with weekly default and drill mode.

Practice drilling up and down a date hierarchy in a weekly customer line chart, from year to day. Enable and disable drill mode to filter points and observe partial weeks.

Learn to customize report interactions in Power BI Desktop by editing how filters on one visual affect others, using cross filter options like filter, highlight, and none.

Configure report interactions in the customer detail report: filter line chart and donut charts from selections, keep the table from filtering visuals, and use the year slicer to filter visuals.

Update report interactions by changing line chart and demographic donuts to filter mode, disable cross filtering between table and line chart, and verify the year slicer filters all visuals.

Learn to use bookmarks in Power BI to capture a report page state and return via report actions, clear filters, and navigate views with buttons.

Explore report bookmarks to highlight customer insights in Power BI, create a customer insight bookmark with a button, and add a reset bookmark to clear all filters.

Apply bookmarks in Power BI to capture a specific report state, filter to 2022 skilled manual roles, highlight Ruben Suarez's $4,683 revenue, and connect the bookmark to an info button.

Create a custom slicer panel in Power BI Desktop to filter by year and continent without cluttering the page, using a left nav trigger, a panel rectangle, slicers, and bookmarks.

Explore numeric range parameters in Power BI to drive scenario testing and what-if analysis, using slicers to adjust a price adjustment parameter and generate adjusted price, revenue, and profit measures.

Learn to use fields parameters in Power BI to create a slicer-driven metric switcher with a DAX measure, enabling dynamic visuals for total orders, revenue, profit, returns, and return rate.

Add a field parameter named customer metric selection with total customers and average revenue per customer, use it as a single-select tile slicer, and bind chart y-axis to this parameter.

Create a fields parameter named customer metric selection in Power BI to switch a line chart’s Y axis between total customers and revenue per customer using a tile style slicer.

Design and implement completely custom tooltips in Power BI by creating a dedicated tooltip page, displaying multiple visuals and KPIs without cluttering your main reports.

Learn to create and test row-level security roles in Power BI Desktop, filter data model by continent, and view reports as assigned roles before applying them in Power BI service.

Design mobile-specific report layouts in Power BI by dragging and dropping existing visuals into the Mobile Layout view, then resize for easy viewing on the Power BI mobile app.

Preview the publish button as the gateway to Power BI Service, the cloud counterpart to Power BI Desktop, enabling publishing to shared workspaces and collaboration.

Apply data viz best practices by clarifying what data you visualize, what you communicate, and your end user, while using bookmarks, drillthroughs, tooltips, and mobile-optimized layouts for Power BI reports.

Explore anomaly detection in Power BI, a time-series based feature that flags anomalies on line charts, provides AI-generated explanations, and supports root-cause analysis via explain-by fields like subcategory and country.

Discover smart narratives in Power BI that generate AI summaries responsive to filter context and visuals. Learn to create, edit, and customize report- and visual-level narratives with dynamic values.

Explore Power BI's Q&A visuals with natural language prompts, train the model with synonyms and review questions, teach Q&A, publish to service, and convert to standard visuals.

Explore decomposition trees in Power BI to analyze return rates by category, subcategory, and product name, enabling ad hoc data exploration and AI-driven root-cause analysis across dimensions.

Explore Power BI's performance optimization tools for large data models. Use the Optimize ribbon, pause visuals, presets, slicers, and the Performance Analyzer, plus external tools for optimization.

Explore optimization presets in Power BI to manage queries and interactivity. Switch from interactivity mode to query reduction or customize query reduction for slicers, cross filtering, and cross highlighting.

Add an apply all slicers button to a report page to apply or clear all slicers with a single click, reducing visual queries and boosting performance.

Explore the Power BI Performance Analyzer to record report actions—from DAX queries to visual rendering and other tasks—export results as JSON and apply optimization tips.

Use external tools in Power BI Desktop to access third-party apps installed on your computer via the External tools menu. Examples include DAX Studio, Tabular Editor, and Bravo.

Learn how calculation groups in Power BI simplify measure management by grouping time intelligence calculations into a single calculation group, using calculation items and explicit measures to drive dynamic visuals.

Explore the new DAX query view in Power BI, enabling table-based DAX queries to explore data, define measures, and view results without building visuals.

Discover the new button slicer in Power BI Desktop (November 2023 update), featuring customizable layouts, rounded corners, image support, overflow paging, and interactive hover and selection effects.

Document a Power BI data model with INFO.VIEW DAX functions to generate a dynamic data dictionary. Expose this information to end users via a report page.

Learn to document Power BI semantic models using the new TMDL view and AI, generating descriptive DAX measures and data dictionaries from code, with portable scripts and AI-assisted descriptions.