Loved by learners at thousands of companies
Explore the Basics of Data LiteracyData 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 DataNext, 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.
Data Literacy BasicsFree
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.Why data literacy is an essential skill50 xpDefining data literacy50 xpReasons to become data literate100 xpThe data literacy toolbox100 xpFrom data to insights50 xpDIKW pyramid as a process100 xpWhat is insight?50 xpInformation or knowledge?50 xpData-driven decision making50 xpBecoming data-driven50 xpFacts & myths about being data-driven100 xpData-driven process100 xpFitting the problem statement50 xp
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.Data is all around us50 xpFinding the right data50 xpFinding the right data source50 xpOpen vs. internal data sources100 xpCommon data types50 xpImportance of data types50 xpStructured vs. unstructured data100 xpQuantitative vs. qualitative data50 xpManaging data50 xpUsing databases100 xpStorage in the cloud50 xpWhich tool do you need?100 xpCommon data problems50 xpConsequences of data problems50 xpFind the data problems50 xpCountering dirty data and data bias100 xp
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.Descriptive analytics50 xpReasons (not) to use descriptive analytics50 xpExploring the data50 xpExploring connections50 xpDiagnostic analytics50 xpFinding causes50 xpRoot cause analysis steps100 xpDescriptive vs. diagnostic analytics100 xpPredictive analytics50 xpAre we predicting yet?50 xpBuilding a predictive model100 xpLooking into the future50 xpPrescriptive analytics50 xpCharacteristics of prescriptive analytics50 xpPredictive vs. prescriptive analytics100 xpMatching use cases to the type of analytics100 xp
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.Data visualizations50 xpThe purpose of visualizations50 xpProviding context100 xpData storytelling50 xp(Not) part of the story50 xpCrafting a story100 xpThree keys to communicating effectively50 xpFocus on your central message100 xpGetting your outline in order100 xpThe importance of form50 xpFrom data to story: a case study50 xpFormulating the central message50 xpSetting up the narrative structure100 xpChoosing visualizations50 xpBest and bad practices100 xpWrap-up50 xp
Jess AhmetSee More
Content Developer at DataCamp
Jess is a Content Developer at DataCamp. Prior to joining DataCamp, she worked in various analyst roles within healthcare and most recently online gambling. She has a passion for education, data, and business which she has been able to combine in her role at DataCamp. Outside of work, you can often find her in front of a TV watching Soccer and Formula 1.
Carl RosseelSee More
Head of BI Curriculum at DataCamp
Carl, a Tableau certified data analyst, is the head of the BI Curriculum at DataCamp, where he focuses on democratizing data skills through Business Intelligence tools. He holds a double master's degree in Business Engineering and worked in various analyst roles at an e-commerce company before joining DataCamp. He likes to use data to make the complex simple and tell data stories. Outside work, you can often find him enjoying a game of soccer, both on and off the pitch.