Mastering Microsoft Power BI: From Beginner to Advanced

Learn how to download and install Power BI Desktop from the Microsoft Store, set up your first reports, and explore data, model, and insert options for rich visualizations.

Explore Power BI’s front end and back end environments, connecting to data sources, transforming data, building reports and dashboards, and securely sharing insights with collaborators.

Power BI connectors provide databases, files, cloud services, and online sources with seamless data import and transformation. Enable real-time or scheduled refresh for consolidated dashboards.

Create basic Power BI reports by importing a CSV dataset, cleaning the sale price (remove the dollar sign and convert to number), and loading the data for visual exploration.

Power BI through a hands-on e-commerce sales data analysis project, cleaning raw CSV data, loading it, and exploring sales categories, trends, promotions, and delivery time.

Import and transform sales data by cleaning headers, removing top and blank rows, editing rows and columns, and converting data types in Power BI's Power Query editor.

Clean and transform data in Power BI by addressing date format errors, removing or duplicating columns, and replacing errors with zero or mean to enable accurate visualizations.

Create visuals to analyze sales data in Power BI, including sales by product and store, revenue by quarter, and promotions, with bar charts and formatting options.

Import data from web pages in Power BI using get data web to fetch tables from a URL, then load and transform columns like country and population for reporting.

Learn to import data from an Access database into Power BI by selecting related tables, loading them into a data model, and reviewing the relationships in the model view.

Import data from Excel into Power BI, load and transform it by using the first row as header, then create interactive visuals on the report canvas.

Learn to scrape website data into Power BI using get data from web, view web and table data, import product tables, and transform columns like product description, price, and tag.

Create a Power BI dashboard canvas, add a header and cards, and customize the background. Build measures to display total employees and attrition.

Create a custom conditional column in Power BI to compute attrition count by mapping yes to 1 and no to 0, then apply the changes.

Create new measures and cards in Power BI, calculating attrition rate as a percentage and showing current employees, average age, and average stay at the company.

Add a pie chart of employees by department, a clustered column chart of attrition rate by department and gender, and a donut chart of attrition rate by education, with slicers.

Create a stacked column chart of employee count by age group with gender legend, a stacked area chart of department job satisfaction, and a matrix of job satisfaction by role.

Add a marital status slicer to the Power BI dashboard to filter attrition insights across age groups and departments, using cards and donut charts for dynamic, styled analytics.

Analyze employee attrition by education field using a stacked bar chart and age-group donut charts by gender, with filters and a marital-status slicer in Power BI.

Explore an interactive Power BI attrition dashboard with slicers to analyze attrition rate by department, education, gender, and marital status, and publish for mobile viewing.

Create an interactive Power BI customer analytics dashboard from the provided Excel file, featuring top customers, sales by product and month, and customer status metrics for the class project.

Explore data analysis expressions (DAX) in Power BI, learning how to build measures, calculated columns, and calculated tables, and apply time intelligence and context concepts for advanced analytics.

Explore the difference between calculated columns and measures in Power BI, noting data loading versus on the fly computation, storage impact, and row vs filter context.

Learn to create calculated columns and measures in Power BI, differentiate their uses, and build a retail dashboard using the Right Style data with DAX-based profit calculations.

Learn to create a custom column in power bi by combining product name and category with a dash using a dax expression, and commit the new row-level column.

Understand how measures and calculated columns differ in Power BI with DAX, where measures compute on the fly in reports and calculated columns load into the data model.

Use calculated columns and measures to build Power BI reports. Combine a calculated column with a measure to show total sales and quantity by product category in charts.

Explore why measures, unlike calculated columns, avoid database storage and update from one dax expression when column names change, keeping total sales consistent across reports.

Explore calculated columns and measures in Power BI, compare per-row profit with total profit, and learn to analyze profit by category using charts.

Create a DAX measure to compare this year's and last year's sales by month, using sum of sales and sameperiodlastyear on the sale date.

Explore row and filter context in Power BI to master when to use calculated columns versus measures, and how context shapes calculations and visuals in DAX-powered reports.

Create a Power BI dashboard showing total sales and profit with cards, a product category bar chart, and location-year matrix, using slicers for location and order type to analyze trends.

Explore the difference between sum and sumx in Power BI: sum as an aggregator over a column and sumx as an iterator for row-by-row calculations, with context awareness.

Explore internal filters in Power BI using the calculate function to fix totals for locations like Lucknow, while external filters from slicers remain dynamic.

Learn to compare total sales by location across product categories with the main branch and calculate each location's percentage of overall sales using Power BI measures.

Learn to use the calculate function in Power BI to compute location-specific sales totals by filtering for Mumbai or Lucknow, and compare with all location totals.

Explore the SUMX function and row-wise calculations in Power BI to compute sale amount per bill (quantity × unit price) and correctly aggregate totals.

Create an age bracket column in Power BI using DAX, importing customer data from Excel, cleaning with Power Query, and classifying ages into 18–24, 25–34, 35–44, 45–54, 55+.

Create a calculated column in Power BI to extract month and year from the sale date with the DAX format function, enabling flexible display like January 2020 or Jan 2020.

Learn to use the switch function in DAX to assign a region volume label (low, medium, high) based on total sales by territory, via a calculated column.

Learn to import and load Excel financial data into Power BI, build relationships among calendar, GL, and territory tables, map date fields, and prepare profit, loss, and sales analyses.

Select matrix visual, place amount in values, and add subclass as rows with year as columns to calculate sales in Power BI; filter to sales for years 18, 19, 20.

Format the sales matrix in Power BI by resizing the visual, turning off subtotals, adjusting font sizes and colors for values and headers, and adding a centered heading.

Analyze sales with drill up and drill down in Power BI, moving from year to quarter and month using the date hierarchy in a matrix.

Learn to create and customize sales visualizations in Power BI by duplicating matrices, building line charts, drilling down by year and quarter, and applying date hierarchies and color formatting.

Use a country slicer in Power BI to analyze sales revenue by country from the territory table, updating all visuals when a country is selected.

Build and analyze a profit and loss matrix in Power BI, calculating gross, operating, and net profit with country and region slicers for targeted financial insights.

Learn to calculate gross profit, operating profit, profit before interest and tax, and net profit in Power BI using a GL-based matrix, filters by class, and region slicers.

Learn to use the cards visual in Power BI to display total sales revenue by filtering subclass sales in charts of account and summing amount.

Master KPI visuals in Power BI by configuring value and trend with a date hierarchy, filtering for sales, and understanding how trend lines and colors reflect target and period.

Create and customize line charts for sales revenue, gross profit, and net profit on a Power BI dashboard, with x axis, date hierarchy, legends, filters, and focus mode.

Add a year slicer linked to the calendar table to filter financial data by year, enabling per-year views of sales revenue, gross profit, and net profit.

Create a country-specific Power BI dashboard to analyze sales revenue, gross profit, and net profit by country with year and quarter context, identifying country performance trends and dips.

Create a DAX measure to calculate total sales in Power BI using sum on the amount column and apply it to the GL table for flexible analysis beyond default totals.

Establish a Power BI data model by linking orders, customers, and cookies type tables to analyze total units sold, revenue, cost, and profit.

Discover how to fill null values in Power BI by applying fill down and fill up, preserving state names (Karnataka and Maharashtra) while transforming data.

Explore power BI's AI capabilities with narrative summaries and the decomposition tree to analyze data across multiple dimensions, drill down by city and state, and uncover root causes.

Master Power BI visuals with a Kaggle sales dataset, then use narrative AI to quickly summarize highest and lowest sales by city, percentage of total, and sales range.

Learn when to use sum versus sumx in Power BI. Distinguish simple column totals from row-level calculations and custom expressions, such as tax and revenue.