M365 Power BI Desktop - Beginner

Explore self-service BI with Power BI Desktop, learning to pull data from diverse sources, model it, and publish dashboards for stakeholders and end users.

Connect to data from over 80 options, including local files, CSV, Excel, databases, and online services such as Amazon Redshift, Facebook, and LinkedIn, and transform it for reporting.

Compare data imports and live connections in Power BI Desktop, noting performance differences, network considerations, and emphasize importing Excel data to start building reports.

Import the Shiping Excel workbook into Power BI Desktop, select the invoices data, and load clean transactional data to prepare for visuals like a funnel chart.

Save your work by naming the workbook and choosing a file type, then consider saving as a template to preserve the data model, data connections, and corporate branding.

Utilize the transform data feature to clean and shape datasets with column edits, replacements, and type conversions for meaningful visuals.

Classify data as structured, semi-structured, or unstructured to set realistic preparation timelines for Power BI analytics. Recognize how databases, CSVs, and word processor data affect data shaping.

Learn how to clean and transform data in Power BI Desktop by removing header and footer information, handling legacy formats, and reshaping data through pivoting, formatting, and adding calculated columns.

Shape and transform data in Power BI Desktop, learn how formatting differs, and apply currency formatting to unit price, subtotal, and profit in the data view.

Explore what makes a good visual using Anscombe's quartet to show how visuals reveal data insights hidden from numbers, and assess every chart type to tell the data's story.

Build visuals in Power BI desktop by selecting fields, choosing visuals, and dragging fields into the correct buckets, then refine with format and analytics settings.

Select the country data category to enable geographic maps in Power BI Desktop, and learn how latitude, longitude, and tooltips use field roles for improved map granularity.

Explore nine data types and four data categories in Power BI desktop, with emphasis on geocoding to generate geo coordinates and enable maps from public data.

Create a table and a matrix in Power BI Desktop to visualize sales data, comparing row and column summaries, and enable data bars and basic formatting for quick insights.

Learn to create text based visuals in Power BI, using single value cards and multi-row cards, with formatting, borders, shadows, and mindful scrolling for dashboards.

Create a clustered column chart in Power BI with salesperson on the axis and subtotal in values, then add profit tooltips and prepare a line chart on the same page.

Build a line chart in Power BI by dragging month from the order date hierarchy to axis, region to legend, and subtotal to values, then configure tooltips and formatting.

Explore how multiple visuals on a single Power BI Desktop page interact, enabling cross-filtering between a column chart and a line chart, with responsive legends and dynamic axis scales.

Learn to build and interpret a waterfall chart in Power BI, compare it with a funnel chart, and use region and subtotal values with tooltip for clarity.

Learn why a funnel chart matters: it's a process view, not just a column chart turned sideways, reducing a top number through stages from prospects to payment to optimize outcomes.

Create a scatter plot to compare subtotals on the x axis with quantity on the y axis, highlighting outliers and regional patterns using interactive tooltips.

Learn how to add motion to a scatter plot in Power BI Desktop by using a play axis with a time interval and ensure X and Y are summarized.

Create and compare standard and stacked area charts to manage overlapping data and occlusion, using month on the axis, region and shipper as legends, and interactive legends for insight.

Create KPI indicators and gauges in Power BI to compare actual values against monthly targets, and build dashboards that clearly display target versus actual performance.

build and customize a gauge visualization in Power BI Desktop, setting min, max, and target values, and fine-tuning formatting and colors for KPI-like insights.