“Dataquest not only teaches you the fundamentals, but also teaches you how to keep learning…so you’re never stuck.”

## Course overview

This course is part of the “Introduction to Data Analysis with Excel” skill path, which we designed for those seeking the practical skills in Excel to perform data analysis and visualization — and ultimately help organizations make better-informed decisions. We designed it for aspiring data professionals with little experience and learners who use basic Excel in their daily jobs and want to enhance their skills.

In this course, you’ll learn how to develop business insights using PivotTables, how to identify trends using time-series analysis, and how to create data visualizations to tell meaningful stories. You’ll also learn how to summarize and visualize relationships between categorical and quantitative variables.

Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser.

## Key skills

• Using PivotTables to analyze data and discover business insights
• Working with time-series data to identify trends over time
• Confirming a relationship between an independent and dependent variable using linear regression
• Estimating the sensitivity of an output to given inputs

## Course outline

### Variance Analysis in Excel 1h

Lesson Objectives
• Roll up and drill down on a dataset using PivotTables
• Identify differences to budget or previous period
• Create custom groupings within a defined hierarchy

### Trend Analysis in Excel 1h

Lesson Objectives
• Resample time series data using PivotTables
• Visualize trends
• Perform basic forecasting

### Exploratory Data Analysis in Excel 1h

Lesson Objectives
• Summarize data with proportion tables and descriptive statistics
• Visualize the distributions of two or more categories
• Explore the relationship of two continuous variables with correlations

### Confirmatory Data Analysis in Excel 1h

Lesson Objectives
• Compare the difference in means between two groups for statistical significance
• Build a basic linear regression model
• Visualize important statistics concepts using Excel

### Business and Financial Modeling in Excel 1h

Lesson Objectives
• Estimate the sensitivity of an output to given inputs
• Build a scenario manager to anticipate possible outcomes
• Perform what-if analysis to estimate a project’s breakeven point

### Guided Project: Analyzing Retail Sales 1h

Lesson Objectives
• Combine and profile data sources
• Analyze and visualize trends in sales over time
• Analyze changes over time at varying levels of a hierarchy
• Model future business scenarios for impact on profitability

## Projects in this course

### Guided Project: Analyzing Retail Sales

For this project, we’ll take on the role of an analyst for a chain of retail stores to explore sales performance across categories and over time using Excel.

## The Dataquest guarantee

Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.

We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.

## Master skills faster with Dataquest

### Go from zero to job-ready

Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.

Build confidence with our in-depth projects, and show off your data skills.

### Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

Impress employers by completing a capstone project and certifying it with an expert review.

98%
of learners recommend
4.85
Dataquest rating
SwitchUp Best Bootcamps
\$30k
Average salary boost
for learners who complete a path

### Aaron Melton

“Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.”

### Jessica Ko

#### Machine Learning Engineer at Twitter

“I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.”

### Victoria E. Guzik

#### Associate Data Scientist at Callisto Media

“I really love learning on Dataquest. I looked into a couple of other options and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method. The projects on Dataquest were key to getting my job. I doubled my income!”

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