Power BI Intermediate Course: Beyond the Basics

Import and transform a folder of sales data files in Power BI, using Power Query to clean, filter by file type, and prepare a single combined dataset for analysis.

Combine multiple sales files into one large data set in Power Query, then remove unnecessary columns and tidy data for faster, clearer analysis.

Verify data types in Power BI with auto detect, rename the query to sales prep, and apply fixed decimals to unit cost, unit price, total cost, and total price.

Import Excel and text files into Power Query, fix headers and data types, rename queries to countries and products, and load to Power BI with auto-detected relationships from column headings.

See how the sales prep table acts as fact table and links to country and product lookups to speed Power BI queries, and learn duplicate vs reference in Power Query.

Create a lookup table for the location and country code columns. Use a reference table to remove duplicates and create a unique location list with a distinct index.

Add index columns to create unique identifiers for locations, products, and countries, rename as location id, product id, and country id, and merge lookups into the sales prep table.

Load only the final sales table and needed lookup tables (locations, products, countries) and disable the sales prep table to speed up refreshes, then analyze with DEX functions and visualizations.

Explore the advanced editor in Power Query to view and modify the M language code, track applied steps, and safely backtrack when renaming or reordering columns.

Organize Power BI queries by creating fact and dimension folders in the queries pane to clearly separate the transactional fact table from lookup dimension tables.

Explore how to troubleshoot and fix Power BI table relationships in data modeling by mapping fields, resolving inactive relationships, and eliminating conflicting lookups to keep the fact table central.

Master cross filter direction in Power BI by understanding single versus both directions and how filters flow between related tables in visuals.

Explore the difference between measures and calculated columns in Power BI using DAX, with examples of creating calculated columns and measures and using them in visuals.

Create a dynamic date table with DAX using calendar from the dataset’s min and max dates, including day name and month name, to enable time intelligence in Power BI.

Add calculated columns in Power BI using DAX to extract year, month number, month name, day number, weekday number, and weekday name from the dates table.

Create a conditional column in Power BI using an if statement to classify dates as weekend or weekday based on weekday number, applied to the dates table.

Mark the dates table as the date table to enable time intelligence, then create a many-to-one relationship with the sales table via the date column so visuals aggregate by year.

In Power BI, create a quarter column in the dates table by using the round up function on the month from the date column, dividing by three to assign quarters.

Learn how quick measures in Power BI replace implicit measures with explicit ones, using time intelligence to produce year-to-date totals for your visuals.

Create a blank key measures table from the home data menu, move measures like total sales quantity and total profit YTD into it, and delete the extra column.

Discover how to create measures with aggregation functions—average, max, count—and apply them to visuals like maps and cards in Power BI, using the key measures table.

Learn to use sumx to evaluate an expression for each row in a table, compare it with sum and calculated columns, and create a measure for price including tax.

Explore how the all function with calculate clears filter context to reveal totals by country and compute percentage contributions, with practical examples of total cost and grand total.

Learn to build and format visualizations in Power BI to present data clearly. Identify which charts best show metrics like total profit by country and align visuals with audience needs.

Master Power BI's formatting options, from general sizing and grid settings to style presets, header formatting, step layout, subtitles, and field formatting for precise visuals.

Master matrix table formatting in Power BI by turning on titles, styling text and backgrounds, adjusting borders, aspect ratio, and visual headers, and toggling icons to customize the look.

Apply conditional formatting in Power BI to highlight matrix data with color scales, data bars, and icons; customize min, max, and diverging rules in advanced controls while handling blanks.

Learn how to swap a matrix to column and bar charts in Power BI, customize axes, legend, colors, data labels, tooltips, and integrate line charts for multiple series.

Learn to create and format Power BI card visualizations to display key metrics at a dashboard glance, using measures like total costs, profit, and sales, with consistent sizing and formatting.

Explore Power BI map charts, and compare standard maps with field map charts, then plot countries, size bubbles by profit, and customize tooltips, colors, and map styles for clarity.

Add interactive slicers and filters in Power BI to drive responsive visuals, using product, category, location, and date fields with dropdowns, search, and multi-select, plus formatting.

Learn to apply universal design elements in Power BI, using themes for quick formatting, add pages and visuals, and use grouping, text boxes, and navigation buttons to elevate report design.

Publish reports from Power BI desktop to the Power BI service, then publish them to a shared workspace to enable access and dashboard collaboration.

Explore the difference between reports and dashboards in Power BI, learn how to pin visuals from multiple reports to a single dashboard, and use drill through to inspect underlying data.

Pin visuals from reports to dashboards in the Power BI service, build and customize a sales analysis dashboard, resize and arrange visuals, and use drill through filters to explore data.

Build a sales dashboard in the Power BI intermediate course from scratch by importing data, cleaning it, creating measures, building reports, publishing to Power BI, and pinning visuals with bookmarks.

Define report requirements and metrics for a five-page Power BI dashboard covering 2017–2020. Add charts and measures for gender, orders, revenue by region, age, and status with year filters.

Import the Excel workbook in Power BI by selecting the order log worksheet, then use Power Query to rename it to order prep and tidy the data.

Check data types in Power Query, convert total revenue and total cost to fixed decimals, and create a location lookup table from town, city, state, and region while removing duplicates.

Create and rename lookup tables for town/city, state/region, order type, and payment type, using references, removing duplicates, adding index keys, and merge into the order prep table.

Merge lookup tables into the orders table using merge queries, create keys, and remove unused columns to optimize Power BI reports.

Design a polished Power BI report with a clear title, year-specific pages, and visual styling using shapes, icons, and text, grouped for consistency.

Explore line charts to display time-based metrics, comparing male and female customers over years and months; customize axes, colors, and legends to reveal trends and support business decisions.

Add a 100 percent stacked column chart to display total revenue by region, using the total revenue measure and region as the legend, with themed colors and data labels.

Learn to build a funnel chart in the Power BI intermediate course to visualize age distribution, grouping customers by age years into 10-year bins and identifying the largest target groups.