Path overview
We designed this skill path for aspiring data professionals with little experience, and learners who use basic Excel in their daily jobs. You’ll learn how to manipulate data using complex formulas, commands, and tools, such as macros, pivot tables, and advanced graphs.
Best of all, you’ll learn by doing — you’ll write code and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.
Key skills
- Defining, Categorizing, and evaluating data
- Identifying data uses in everyday business
- Organizing data for data analysis
- Defining the key steps of the data analysis process
Path outline
Part 1: Introduction to Data Analysis with Excel [5 courses]
Introduction to Data Analysis in Excel 4h
Objectives- Define, categorize, and evaluate data
- Identify ways data is used in business and everyday life
- Organize data
- Describe key steps of the data analysis process
Preparing Data in Excel 6h
Objectives- Import data into an Excel spreadsheet from more than one data source
- Organize data into a spreadsheet using worksheets and tables
- Clean, manipulate, and modify the data
- Consolidate the data for analysis
Visualizing Data in Excel 6h
Objectives- Visualize data using pie, column, histogram, line, scatter, and combo charts
- Select the appropriate data visualization
- Create charts using design principles
- Design visualizations for your intended audience
Exploring Data in Excel 5h
Objectives- Define descriptive statistics
- Identify the different types of descriptive statistics
- Identify when to use each descriptive statistic
- Apply and compare different descriptive statistics to a single column, to multiple columns, and to groups of data
- Create visualizations to explore and analyze data
Analyzing Data in Excel 5h
Objectives- Analyze data and discover business insights using PivotTables
- Identify trends over time in time-series data
- Summarize and visualize relationships between categorical and quantitative variables
- Confirm a relationship between an independent and dependent variable using linear regression
- Estimate the sensitivity of an output to given inputs
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 your project portfolio
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.
Showcase your path certification
Impress employers by completing a capstone project and certifying it with an expert review.
Projects in this path
Guided Project: Preparing Data with Excel
In this guided project, you’ll import a dataset, organize it, clean it, and then consolidate it into a single table, preparing it for analysis.
Guided Project: Visualizing the Answer to Stock Questions Using Spreadsheet Charts
In this project, we will apply the knowledge and skills we developed in the preceding lessons to present stock data clearly and help answer important questions about the underlying data.
Guided Project: Identifying Customers Likely to Churn for a Telecommunications Provider
In this project, we’ll conduct an Exploratory Data Analysis (EDA) on data from a telecommunications provider to create profiles on customers that are at risk of churn.
Guided Project: Analyzing Retail Sales
Work with retail sales data to explore trends and relationships. Build basic models to confirm the statistical significance of your insights.
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