Explore the foundations of Power BI and tackle a real world business challenge to identify top regional earners for annual bonuses using a CSV dataset.

Connect to a CSV file in Power BI using Get Data, preview and transform data in the Power Query editor, adjust data types, and apply changes to load the dataset.

Explore Power BI navigation basics, from the home ribbon and data connectors to visuals, themes, and pane layouts; learn to switch visuals and refresh data.

Power BI helps you drill down from year to quarter, month, and day, and drill back up to get a granular view of sales data.

Explore advanced drilling in hierarchies in Power BI, mastering show next level and expand next level to navigate year, quarter, month, and day granularity while preserving or disregarding higher levels.

Learn to customize colors in Power BI visuals by assigning region to the legend, adjusting colors, transparency, and borders, while practicing hierarchical drill behaviors and aggregations.

Learn to add a new calculated column in Power BI to compute total sales by multiplying units by unit price, and use it in your visuals to show revenue.

Explore Power BI visual formatting to enhance clarity: adjust legends and data labels, set display units and decimals, format currency as dollars, and customize titles for clear, sharable reports.

Explore long-term unemployment statistics in the US by loading a time-series dataset designed for machines in Power BI, learn time-series aggregation, and prepare for stacked area chart visualizations.

Power BI hands-on course teaches visualizing US long-term unemployment from 2005–2015 as a time series, contrasting show next level (averages) with expand next level (monthly detail) to reveal trends.

Explore how aggregation and granularity shape Power BI visualizations, shaping level of detail from monthly figures to gender and age breakdowns, and how sums, averages, or medians influence charts.

Convert a line chart to a stacked area chart in Power BI by swapping age for gender, and highlight age groups with the color legend to show totals.

Explore filtering and slicers in Power BI by creating and configuring gender, age, and period slicers, and compare visual filters, page filters, and all-page filters to empower interactive analytics.

Create compelling maps and scatterplots by joining the order data and order breakdown in power BI, using relationships to combine tables and build interactive BI reports.

Explore inner, left, right, and full outer joins to combine two tables by matching keys, with unmatched rows becoming null and the left or right table as primary.

Explore how duplicates on the join column affect an inner join between two tables in Power BI, linking order status with items and sales.

Master joining on multiple fields in Power BI, such as a left join on store and order number, to avoid inflated results and ensure accurate customer sales totals.

Create a profit margin calculated measure in Power BI, apply gradient formatting to map bubbles, and let bubble size reflect sales.

Learn to build an interactive Power BI dashboard by combining charts with filters. Use slicers to filter across visuals and pages for dynamic analysis.

Load a UK bank customers CSV into Power BI, verify 4014 rows, and explore fields such as customer id, name, gender, age, region, job, join date, and balance.

Create a Power BI map by dragging region to the canvas and choosing a filled map, then add a card to show total customers and regional counts.

Visualize gender distribution in a Power BI dataset by creating a gender page, converting the gender field to a pie chart, showing percent with no decimals, and adjusting slice colors.

Create an age distribution in Power BI by binning age into five-year groups, counting customer IDs, and presenting the results as percentages with labeled data and clear formatting.

Power BI A-Z hands-on training: create balance bins and distributions by setting bin size in thousands, convert to percentage of total, and add data labels for a ready balance distribution.

Create an interactive Power BI customer segmentation dashboard by combining a map, gender pie, age and balance distributions, and a job classification treemap on one canvas.

Master Power BI reports by adjusting colors, exploring drill-down capabilities, and controlling visual interactions with edit interactions and filters to reveal regional and segment insights.

Explore how a bank's Power BI customer segmentation dashboard reveals gender and age trends, regional patterns, and balance insights to tailor offerings and drive strategic decisions.

Explore custom visuals in Power BI with the euro debt crisis data set (2011) showing creditor, debtor, amount in billions, and risk to build quick, insightful visualizations.

Master Power BI custom visuals by signing in with a work or school account and using a sample file or a workaround with Microsoft Advertising, featuring a chord diagram.

Build and read a chord chart in Power BI using a custom visual, mapping creditors to debtors by amount and exploring direction and formatting.

Learn how to enhance a chord chart in Power BI by adding a second layer of information, mapping country risk factors to data colors, and creating a debtors chart.

Add treemaps to Power BI visuals, enable data labels and shadows, and edit interactions so the creditor and debtor visuals filter each other for clearer analysis.

Explore power BI visualizations to analyze lending and borrowing across countries using chord diagrams and treemaps, revealing who lends to whom and which nations are most at risk.

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