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In this chapter, you’ll get more familiar with time-based variables and the multiple ways to extract further variables using EDA for analysis—like day of week and time difference. You’ll get hands-on with Power BI as you build line charts to calculate new metrics and uncover trends hiding in your data—including period-over-period change and rolling averages.
One of the most powerful functions of EDA in Power BI is being able to identify which variables have the most influence on your target outcome. A native Power BI visualization tool enabling that is Decomposition Trees. You'll learn about Decomposition Trees, how to construct, then interpret in order to explain a target outcome by other variables.
In this chapter you'll build another native Power BI tool, Key Influencers visual. It helps you to understand how much a target outcome changes based on specific variables and segments of observations.
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