YoVDO

Trend Analysis in Power BI

Offered By: DataCamp

Tags

Data Visualization Courses Exploratory Data Analysis Courses Trend Analysis Courses

Course Description

Overview

Enhance your reports with trend analysis techniques such as time series, decomposition trees, and key influencers.

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. 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.

Syllabus

  • 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.
  • 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.
  • 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.
  • 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.

Taught by

Maarten Van den Broeck and Jacob Marquez

Related Courses

Intro to Statistics
Stanford University via Udacity
Introduction to Data Science
University of Washington via Coursera
Passion Driven Statistics
Wesleyan University via Coursera
Information Visualization
Indiana University via Independent
DCO042 - Python For Informatics
University of Michigan via Independent