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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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.

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 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.

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.

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 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.