Microsoft Power BI - Master Power BI in 90 Minutes!

Load sales data from an Excel workbook with two worksheets into Power BI, perform simple transformations, build the data model with correct relationships, and create your first visualization.

Explore getting data from Excel, linking sales data to salespeople, and using Power Query in Power BI to extract the year and add a new column with applied steps.

Load more data in Power BI by using the home menu to access get data or new source, in both the Power BI editor and the Power BI desktop window.

Load your data, extract the year from order date, and add these tables to the data model. Verify the relationships, including a many-to-one link between sales and salesperson.

Master Power BI by manually defining relationships between the sales and salesperson tables, establishing a many-to-one link, activating the relationship, and adding more connections in the data model.

Create dynamic Power BI visuals by building a clustered column chart of sales by first name and a year-based pie chart, highlighting interactivity across charts via solid data relationships.

Explore visualization customization in Power BI by configuring a column chart's axis and legend, adjusting the value measure, and applying filters to refine average sales by first name.

Plot sales over time with a line chart by order date, grouped by month to spot peak and low months, and explore area or line-and-clustered-column charts for product comparisons.

Format and customize Power BI visuals with the format and analytics tabs, adjusting axes, colors, labels, borders, and backgrounds; add average, minimum, maximum, or constant lines for analysis.

Use Power BI's ask a question feature to generate charts from natural language, acting as your virtual assistant, with bar or column charts for total or average sales.

Create a Power BI dashboard with tree charts for total sales by channel partners (alphabetical), by year and quarters, and by product for 2012–2014, using part B desktop.

Pull three NBA data sources from NBA.com and transform them in Power BI Desktop. Build a linked data model with relationships and craft visualizations to reveal insights.

Learn to pull data from web sources in Power BI, extract and clean tables, split location and team names, and load team stats, defense, and clutch into a data model.

Load and transform data, apply changes to the data model, and establish one-to-one relationships using location to connect team clutch, team defense, and team stats, enabling effective Power BI visualizations.

Build a Power BI report with multiple visualizations—column charts, cards, gauge, map, line and pie charts—linked by a data model for interactive insights.

Publish your Power BI report to Power BI service, replace the dataset, and assemble a dashboard by pinning visuals like a pie chart and map in your workspace for sharing.

Explore the Power BI website, navigate home, favorites, recent, and apps, and learn to use workspaces, quick insights, share and collaborate, and analyze in Excel.

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