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Power BI によるトレンド分析
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更新日 2026/05
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前提条件
Exploratory Data Analysis in Power BI1
Exploring Time Series Data
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.
2
Analyzing Time Series in Power BI
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.
3
Decomposition Trees
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.
4
Key Influencers
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.
Power BI によるトレンド分析
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