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Trend Analysis in Power BI

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

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3 Hours9 Videos25 Exercises2,121 Learners1950 XPData Analyst Track

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Course Description

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.
  1. 1

    Exploring Time Series Data

    Free

    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.

    Play Chapter Now
    Starting to explore time series data
    50 xp
    Statements about time series analysis
    50 xp
    Exploring AirBnB time series
    50 xp
    Generating a new date variable
    100 xp
    Analyzing trends by day of week
    100 xp
    Calculating year-over-year change
    100 xp
  2. 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.

    Play Chapter Now
    Time series run chart
    50 xp
    Cyclical vs. Seasonal
    100 xp
    Analyzing Glassdoor reviews over time
    50 xp
    Building your first time series chart
    100 xp
    Calculating rolling averages
    100 xp
    Finding anomalies in time series data
    100 xp
  3. 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.

    Play Chapter Now
    Introduction to decomposition trees
    50 xp
    Statements about decomposition trees
    50 xp
    Using decomposition trees in Power BI
    50 xp
    Getting started with decomposition trees
    100 xp
    Diving deeper into decomposition trees
    100 xp
    Decomposing attrition rates
    100 xp
  4. 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.

    Play Chapter Now
    Introduction to key influencers
    50 xp
    Decomposition trees vs. key influencers
    100 xp
    Using key influencers in Power BI
    50 xp
    Key influencers for average listing price
    100 xp
    Segments from key influencers
    100 xp
    Key influencers for super hosts
    100 xp
    Congratulations!
    50 xp

In the following tracks

Data Analyst

Datasets

Exercises and DatasetsDataCamp vs. Local Experience

Collaborators

carlrosseel-73112126-9ed2-4866-942a-96fbf265b088
Carl Rosseel

Prerequisites

Exploratory Data Analysis in Power BI
Maarten Van den Broeck Headshot

Maarten Van den Broeck

Senior Content Developer at DataCamp

Maarten is an aquatic ecologist and teacher by training and a data scientist by profession. He is also a certified Power BI and Tableau data analyst. After his career as a PhD researcher at KU Leuven, he wished that he had discovered DataCamp sooner. He loves to combine education and data science to develop DataCamp courses. In his spare time, he runs a symphonic orchestra.
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Jacob Marquez Headshot

Jacob Marquez

Data Scientist at Microsoft

Jacob H. Marquez is an insatiable learner and lifelong builder. He is a data scientist by day, answering audacious questions to support customer experience and company goals. He is a serial hobbyist by day and night: being an educator, building a coffee recommendation app, drinking coffee, writing on Medium, and amateur cycling and muay thai. He has a bachelor's in psychology and a master's in computational analytics (2024).
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