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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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 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.

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 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 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.

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.

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.

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

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.

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.

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.

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

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

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.

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.

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.

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.

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.

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 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.