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Install Anaconda and create a dedicated conda environment for Power BI with Python 3.8, then activate it and configure Power BI to use this environment on Windows.
Explore how to create Python visuals in Power BI, build a linear model plot of sales versus amount with color by category, customize legends, and apply slicers for interactive filtering.
Explore a Python-based data science case study in Power BI context, loading a customer churn dataset, performing preprocessing, training a classifier, and visualizing predictions and correlations.
Learn to build dynamic Power BI visuals using disconnected tables and DAX switches, enabling a single chart to toggle between new and lost customers with a slicer.
Learn to build a balance sheet in Power BI finance, detailing current assets, long-term assets, liabilities, and equity. Import data in a flat structure and apply grouping for case study.
Create a balance sheet in Power BI by converting to a matrix, adding subgroup and balance sheet groups to drill down assets, liabilities, and equity.
learn to highlight min and max values in small multiples line charts in Power BI, using a min-max measure and a bar chart workaround for conditional formatting.
Learn a fast Power Query copy-paste technique to move multiple queries between Power BI reports, and explore Get Data feature that brings Power Query to Mac users in the service.
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