Data & AI Accredited Education Partners

Data Literacy training description

Learn the power and pitfalls of data.

Clear insight into a data-driven world.

We are bombarded with data every day. One of the main challenges that organizations face in this time is a lack of data literacy. Do your employees have enough knowledge to read, interpret and transform data into valuable insights? This is crucial to make the right decisions. Only then will your organization be able to respond to the needs of your customers and opportunities in the market.

Are you curious enough?

Data literacy is the most important skill for people who work with data. It enables you to constantly look for new or existing data, question it and ask critical questions. It is therefore the skill that allows us to draw the right conclusions in today’s data-driven reality. This not only delivers faster decisions, but also a better result for your organization.

From manipulation to information

In this training you will learn not only the power, but also the pitfalls of data through practical examples and exercises. You will get an answer to the question how to read and interpret information correctly and what steps you need to take to analyze data thoroughly. After completing this Data Literacy training, you will have various tools to distinguish information from manipulation based on your curiosity.

TARGET GROUP This training is designed for anyone who wants to understand and analyze data faster and communicate it in an effective way.

Data Literacy Training Objectives

In this training you will learn:

how to get more value from your data; how to interpret data correctly; how to recognize the pitfalls of data; how to improve and maintain the quality of your data; the main steps to analyze data thoroughly; how to convince others with data-based arguments. More… TRAINING CONTENT Program

Block 1: Reading data

Reading data that is presented to us in the media, business reports, political claims and advertising messages How do you distinguish information from manipulation? How to prevent incorrect interpretation Practical assignment: applying the data checklist to a number of practical situations to improve our Data Literacy.

Block 2: Working with data

Improving the quality of your data How do you maintain this quality? Discussing the main data processing steps. Naming the consequences of data processing Practical assignment: estimating the consequences of the different processing steps on the results based on a number of cases.

Block 3: Analyzing data

What are the main steps to analyze data thoroughly? How do you prevent deception? What can we learn from the “scientific method” when it comes to data analysis? Practical assignment: performing the main analytical steps on a practical example.

Block 4: Arguing with and communicating data

Being right is one thing, but getting right is quite another.

Transition and difference from analysis to explanation of data How do you convince others with data-based arguments? What can we learn from storytelling to convey our data better?

The 7 essential principles for good data storytelling Practical assignment: Applying the 7 principles to a practical example