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.

Starting to explore time series data

Statements about time series analysis

Exploring AirBnB time series

Generating a new date variable

Analyzing trends by day of week

Calculating year-over-year change

Exploring Time Series Data

Time series run chart

Cyclical vs. Seasonal

Analyzing Glassdoor reviews over time

Building your first time series chart

Calculating rolling averages

Finding anomalies in time series data

Analyzing Time Series in Power BI

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. 

Introduction to decomposition trees

Statements about decomposition trees

Using decomposition trees in Power BI

Getting started with decomposition trees

Diving deeper into decomposition trees

Decomposing attrition rates

Decomposition Trees

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.

Introduction to key influencers

Options

Decomposition Tree

Key Influencer

Decomposition trees vs. key influencers

Using key influencers in Power BI

Key influencers for average listing price

Segments from key influencers

Key influencers for super hosts

Congratulations!

Key Influencers

Exercises and Datasets

DataCamp vs. Local Experience

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.

<h2>Analyze Time-Series Data</h2>
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. 
<br><br>
<h2>Understand Influencing Variables</h2>
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.


Exploratory Data Analysis in Power BI

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

Trend Analysis in Power BI

Data Analyst in Power BI

Allows the exploration of a target variable using different paths

Useful for directly comparing influence across variables

Dependent on enough observations to derive patterns

Explore the impact of a specific value on the change of a target variable

Decomposition trees vs. key influencers

Trend Analysis in Power BI

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