课程
Power BI 趋势分析
中级技能水平
更新时间 2026年5月
Power BIData Manipulation3小时9 视频25 道练习1,950 XP38,837成就证明
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企业版试用课程描述
分析时间序列数据
在本课程中，你将学习如何分析时间序列、可视化数据并识别趋势。 你将构建新的日期变量，了解运行图，并开始计算滚动平均值。了解影响变量
最后，你将了解如何利用 Power BI 的分解树和关键影响因素来识别哪些变量对目标变量影响最大。先决条件
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 趋势分析
课程完成 加入超过19百万学习者，今天就开始Power BI 趋势分析！
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