Course
Trend Analysis in Power BI
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Analyze Time-Series Data
In this course, you’ll learn how to analyze time series, visualize your data, and spot trends. You’ll build new date variables, discover run charts, and get into calculating rolling averages.Understand Influencing Variables
Finally, you’ll find out how to identify which variables exhibit the most influence on the target variable using Power BI's decomposition trees and key influencers.What you'll learn
- Identify the characteristics of a time series and recognize patterns including trends, seasonality, and cyclical variation in a dataset.
- Recognize the purpose of a rolling average and identify the appropriate window size for smoothing short-term noise in a time series visualization.
- Differentiate between period-over-period comparison methods and identify the DAX time intelligence functions, including SAMEPERIODLASTYEAR() and DATESBETWEEN(), used to implement them.
- Identify the use cases for Power BI's Decomposition Tree and Key Influencers visuals in root cause and trend analysis.
- Distinguish between structured trend analysis and ad hoc exploration and recognize when each approach is appropriate for a given analytical question.
Feels like what you want to learn?
Start Course for FreePrerequisites
Exploratory Data Analysis in Power BIExploring Time Series Data
Analyzing Time Series in Power BI
Decomposition Trees
Key Influencers
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FAQs
What prior Power BI skills do I need for this course?
You should already know how to create measures and columns using DAX, build common visuals like bar charts, and load data with Power Query. The prerequisite course is Exploratory Data Analysis in Power BI.
What datasets will I work with?
You will analyze a sample of 8,000 Airbnb listings from cities including New York, Paris, Rome, and Sydney, and a synthetic dataset of Glassdoor employee reviews covering ratings and professional history.
What can I do with time series data after completing this course?
You will be able to build run charts, calculate rolling averages, detect anomalies, and break down trends by categories using small multiples, all within Power BI Desktop.
What are the Key Influencers and Decomposition Tree visuals used for?
Key Influencers identifies which variables most strongly affect an outcome, while the Decomposition Tree lets you drill into a metric by multiple variables step by step. Both are native Power BI features that require no coding.
How is this course different from a statistics course?
The focus is on applying analytical concepts such as rolling averages, correlation, and anomaly detection visually inside Power BI, not on mathematical derivations. It is designed for practitioners who need actionable insights, not statistical theory.
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