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 skill

Defining data literacy

The data literacy toolbox

Data literacy in action

From data to insights

DIKW pyramid as a process

What is insight?

The DIKW journey

Data-driven decision making

Becoming data-driven

Facts & myths about being data-driven

The data-driven process

Fitting the problem statement

Data Literacy Basics

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 us

Finding the right data

Finding the right data source

Options

Open data

Internal data

Open vs. internal data sources

Common data types

Importance of data types

Structured data

Unstructured data

Structured vs. unstructured data

Quantitative vs. qualitative data

Managing data

True

False

Using databases

Storage in the cloud

Data pipeline

Database

Dashboard

Which tool do you need?

Common data problems

Consequences of data problems

Find the data problems

Countering dirty data and data bias

Reading 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 analytics

Reasons (not) to use descriptive analytics

Exploring the data

Exploring connections

Diagnostic analytics

Finding causes

Root cause analysis steps

Descriptive vs. diagnostic analytics

Predictive analytics

Are we predicting yet?

Building a predictive model

Looking into the future

Prescriptive analytics

Characteristics of prescriptive analytics

Predictive vs. prescriptive analytics

Matching use cases to the type of analytics

Working with and Analyzing Data

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 visualizations

The purpose of visualizations

Providing context

Data storytelling

(Not) part of the story

Crafting a story

Three keys to communicating effectively

Focus on your central message

Getting your outline in order

The importance of form

From data to story: a case study

Formulating the central message

Setting up the narrative structure

Choosing visualizations

Best and bad practices

Wrap-up

Communicating Insights

Data Visualization Cheatsheet

Course Glossary

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.
 
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.
 
Time to start your journey to becoming data literate!

The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos.
The course glossary can be found on the right in the resources section.
To obtain CPE credits, you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.

<h2>Explore the Basics of Data Literacy</h2> 
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.
 
<h2>Get a Deeper Understanding of Data</h2> 
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.

Data is all around us, which makes data literacy an essential life skill. The ability to read, work with, analyze, and communicate insights with data.

Introduction to Data Literacy

Data is all around us, which makes data literacy an essential life skill. 

Data Literacy Professional

Data-vaardigheden voor bedrijven

Explainable AI can assist in mitigating bias.

Societal bias can be reflected in data bias.

Data cleaning is an essential preparation step before analysis can begin. 

Data bias is not a problem, because data analysis is objective and neutral. 

Data bias can always be removed through data cleaning.

Missing data have no effect on the results, they are just ignored in data analysis. 

Countering dirty data and data bias

Introduction to Data Literacy

Praktische interactieve oefening