Course
Introduction to Data Literacy
BasicSkill Level
Updated 03/2026Start Course for Free
Included withPremium or Teams
TheoryData Literacy2 hr16 videos61 Exercises4,000 XP130K+Statement of Accomplishment
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Explore the Basics of Data Literacy
Data is all around us, which makes data literacy an essential life skill. It is a skill that empowers you to ask the right questions about data and choose the right tools to read, interpret and communicate data. This non-technical course will equip you with the necessary knowledge and skill to feel confident around data and understand how data can be used to gain actionable insights and drive change.Through hands-on exercises, you’ll learn how to get from data to insights, how data drives decision-making, how to collect and manage data, the four types of analytics and how to use storytelling and visualization to improve your data communication, and more.
You’ll start with the basics, understanding why data literacy is important and why you should take steps to become data literate. You’ll also learn how to use data to your advantage, from gaining insights to making decisions.
Get a Deeper Understanding of Data
Next, you’ll discover how to identify data sources, looking at some of the most common types, how to manage them, and what to do when you run into problems with your data.In the second half of this data literacy course, you’ll focus on how you can gain insights by using data analytics. As well as exploring the different types of analysis and when to perform them, you’ll also learn about presenting your findings with impact using data visualizations and storytelling.
By the time you’re finished, you’ll have a strong understanding of why data literacy is so essential in the modern world, as well as some of the fundamentals of identifying the right types of data for you to use.
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Start Course for FreeWhat you'll learn
- Assess typical data quality issues—including errors, missing values, and bias—and Evaluate appropriate cleaning or mitigation strategies
- Define data literacy and its four core abilities of reading, working with, analyzing, and communicating data
- Differentiate descriptive, diagnostic, predictive, and prescriptive analytics to determine the most suitable method for a given problem
- Identify common data sources, data types, and storage options such as relational databases, document stores, data warehouses, and data lakes
- Recognize effective techniques for communicating insights, including selecting suitable visualizations, applying narrative structure, and focusing messages for stakeholders
Prerequisites
There are no prerequisites for this course1
Data Literacy Basics
Why should you become data-literate? To answer this question, you'll learn why data literacy is an essential skill, how to get from data to insights, and how data can help with decision-making.
2
Reading Data
Data is everywhere nowadays, but how do you find the right data for your problem? In this chapter, you'll learn about data sources, common types of data, how to manage data, and what to do about common data problems.
3
Working with and Analyzing Data
In this chapter, we dive deeper into how to analyze your data to get the insights you need. You'll learn how and when to use the four types of analytics: descriptive, diagnostic, predictive, and prescriptive analytics.
4
Communicating Insights
In the final chapter, we'll cover communicating the insights you gained from your data. You'll learn how to use visualizations and storytelling to craft an engaging data story and learn about the three keys to communicating effectively.
Introduction to Data Literacy
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