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Data Analysis in Excel

Learn how to analyze data in Excel.

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4 Hours12 Videos48 Exercises114,327 Learners2600 XP

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Course Description

Excel is the world’s most popular data analysis tool. Companies and institutions worldwide use it to transform mountains of raw data into clear insights. Strong Excel skills can open new career paths, make you more employable in various industries, and save hours in your daily tasks.

In this course, you’ll develop employable data analyst skills, starting with the Excel basics, what it can do, and the data analysis steps you should follow.

The chapters begin by exploring data; navigate your worksheet and trim and classify your data types. You’ll even work with real-world Kickstarter data to use your new-found Excel skills to analyze what makes a successful project.

Later chapters in this course will teach you how to prepare your data by extracting text, preparing date data, and which Excel formulas can help. You’ll learn to use ‘the most important function in Excel’, VLOOKUP, to combine data from different sources before testing your understanding in hands-on exercises.

These Excel skills, functions, and time-saving shortcuts can be applied to any industry, whether you’re looking to move to a career in data analysis, or looking to improve your skills in marketing, finance, HR, logistics, and more.
  1. 1

    Exploring Data

    Free

    In the first chapter, you’ll learn about the data analysis process, a framework that will help you transform raw data into information that is useful for decision-making. You will use Excel to start exploring the Kickstarter dataset.

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    Welcome to the wonderful world of Excel!
    50 xp
    What can Excel do?
    50 xp
    Data analysis steps
    100 xp
    Setting up your environment
    50 xp
    Navigating the worksheet
    50 xp
    Exploring data in Excel
    50 xp
    Looking for exact matches
    50 xp
    Trimming your data
    50 xp
    Sorting the table
    50 xp
    Nesting functions
    50 xp
    Understanding data types in Excel
    50 xp
    Classifying data types
    100 xp
    Changing to text
    50 xp
    Rounding values
    50 xp
  2. 2

    Preparing Data

    In this chapter, you’ll move on to data cleaning and learn about a variety of functions that help you prepare text and date fields. Additionally, you’ll use VLOOKUP, one of Excel’s most essential functions, to add data into your dataset from another table.

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    Cleaning text data
    50 xp
    Joining text strings
    50 xp
    Capitalizing words
    50 xp
    Using upper and lower case
    50 xp
    Extracting text from cells
    50 xp
    Counting characters
    50 xp
    Extracting text
    50 xp
    Replacing characters
    50 xp
    Preparing date data
    50 xp
    Using the system date
    50 xp
    Working with dates
    50 xp
    Finding the day of the week
    50 xp
    Figuring out the month
    50 xp
    The most important function in Excel
    50 xp
    Finding the matching column
    50 xp
    Working with range_lookup
    50 xp
    Using VLOOKUP
    50 xp
  3. 3

    Analyzing Data

    For the final chapter, you’ll get down to business and use an assortment of functions to analyze the Kickstarter data and better understand what features successful projects have in common.

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    But who's COUNTing?
    50 xp
    Choosing the right count function
    100 xp
    Learning to count
    50 xp
    Counting blank cells
    50 xp
    Excel the great calculator
    50 xp
    Math functions in Excel
    50 xp
    Finding the minimum
    50 xp
    Aggregating data
    50 xp
    Logic functions
    50 xp
    The arguments of the IF() function
    100 xp
    Performing a logical test
    50 xp
    Taking IF() to the next level
    50 xp
    Conditional aggregations
    50 xp
    Finding unique values
    50 xp
    Counting projects
    50 xp
    Determining the average
    50 xp
    Wrap-up
    50 xp

Datasets

Solution WorkbookRaw Data

Collaborators

sara-billen
Sara Billen
Jen Bricker Headshot

Jen Bricker

Head of Career Services, DataCamp

Jen leads the Career Services team mentoring learners during their job search. Previously, she led the Instructor Success team hiring hundreds of data scientists, working with them to build DataCamp content. Prior to DataCamp, she worked in non-profit management as well as data analytics adult education. Her career has always centered around her two main passions - people and data!
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