Understanding data fluency

Data Fluency

Konstantinos Kattidis

Data Analytics Lead

The journey of learning a new language

1. Basic language level: Ability to understand the vocabulary, grammar, and basic sentence structure
2. Language fluency: Ability to express clearly, engage in meaningful conversations, and convey thoughts and ideas effectively to others
3. Language expertise: A high level of proficiency which is required by people that use language as a profession

The journey of learning the language of data

• Level 1: Data literacy
  • The ability to read, understand, and interpret data in a meaningful way
  • Being familiar with basic data concepts and data analysis techniques
  • Understanding data visualizations, charts, and reports
  • Asking relevant questions about data and make informed decisions based on data insights

Moving beyond data literacy

• Level 2: Data fluency
  • Effectively working with data
  • Analyzing, manipulating, and drawing meaningful insights
  • Seeking data-driven solutions to business problems and effectively communicating data insights
  • Data fluency takes data literacy to a more advanced level

Surpassing data fluency

• Level 3: Data expertise
  • A high level of proficiency required by data professionals
  • For example, data scientists, data analysts, or engineers
  • Having a deep understanding of advanced data analysis techniques, data infrastructure development, and predictive analytics

About the course

• Chapter 1 - Learn about the importance of data fluency and discover a framework for achieving data fluency
• Chapter 2 - Learn how data-fluent individuals behave in different scenarios by covering best practices and techniques
• Chapter 3 - Learn what a data fluent organization looks like by covering the elements of data culture, and data ecosystem

Let's practice!

Data Fluency