After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
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.Feels like what you want to learn?
Start Course for FreeWhat 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.
Prerequisites
Curriculum
Course outline
1
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.
Trend Analysis in Power BI
Course
Complete
