
Expires in:
Expires in:
Expires in:



Self-paced course
Self-paced course
Data Literacy Foundations
Data Literacy Foundations
Rating 4.3
318 reviews
318 reviews
318 reviews
Course Description
We live in a world that runs on data.
It’s how Amazon and Netflix know which movies and products to recommend, how Starbucks manages a global supply chain, how banks detect fraud, and how Uber connects drivers with passengers in real-time.
But data skills aren’t just for tech companies or professional analysts anymore.
Whether you’re a teacher using test scores to improve lesson plans, a sales manager tracking monthly quotas, or a marketer exploring customer trends, data can help you work smarter and make better, more impactful decisions.
In this course, we’ll set the stage by discussing what data literacy means, share frameworks to help you assess and benchmark your skills, and review the elements of a successful data ecosystem, including data democratization, strategy, architecture, and governance.
From there we’ll dig into each core component of the data literacy skill set – interpreting, managing, analyzing and communicating with data.
You’ll practice interpreting tabular datasets and charts, learn how to apply profiling and QA techniques, and review methods for accessing, storing, and transforming data for analysis.
Next we’ll introduce proven frameworks designed to help you think and problem-solve like a world-class data professional, and break down the differences between descriptive, diagnostic, predictive and prescriptive analytics.
We’ll also explore the power of data visualization and storytelling. We’ll review key principles and best practices for communicating with data, walk through common visualization mistakes and how to correct them, and show you how to craft clear, data-driven narratives.
Last but not least we’ll talk about what data literacy means in the age of AI. We’ll demo some incredible use cases for generative AI tools like ChatGPT and Gemini, share prompt engineering tips and best practices, and address common limitations and pitfalls to be aware of.
Whether you’re an individual looking to build confidence, a leader seeking to empower and upskill your team, or a data professional just trying to stay ahead of the curve, this is the course for you.
Course Description
We live in a world that runs on data.
It’s how Amazon and Netflix know which movies and products to recommend, how Starbucks manages a global supply chain, how banks detect fraud, and how Uber connects drivers with passengers in real-time.
But data skills aren’t just for tech companies or professional analysts anymore.
Whether you’re a teacher using test scores to improve lesson plans, a sales manager tracking monthly quotas, or a marketer exploring customer trends, data can help you work smarter and make better, more impactful decisions.
In this course, we’ll set the stage by discussing what data literacy means, share frameworks to help you assess and benchmark your skills, and review the elements of a successful data ecosystem, including data democratization, strategy, architecture, and governance.
From there we’ll dig into each core component of the data literacy skill set – interpreting, managing, analyzing and communicating with data.
You’ll practice interpreting tabular datasets and charts, learn how to apply profiling and QA techniques, and review methods for accessing, storing, and transforming data for analysis.
Next we’ll introduce proven frameworks designed to help you think and problem-solve like a world-class data professional, and break down the differences between descriptive, diagnostic, predictive and prescriptive analytics.
We’ll also explore the power of data visualization and storytelling. We’ll review key principles and best practices for communicating with data, walk through common visualization mistakes and how to correct them, and show you how to craft clear, data-driven narratives.
Last but not least we’ll talk about what data literacy means in the age of AI. We’ll demo some incredible use cases for generative AI tools like ChatGPT and Gemini, share prompt engineering tips and best practices, and address common limitations and pitfalls to be aware of.
Whether you’re an individual looking to build confidence, a leader seeking to empower and upskill your team, or a data professional just trying to stay ahead of the curve, this is the course for you.
Course Content
3.75 video hours
Skills you'll learn in this course
Read charts & statistics with confidence to spot truth vs noise
Ask the right business questions using the DATA framework
Choose appropriate data types & measures for any analysis
Communicate insights with simple, story‑driven visuals
Meet your instructors


Chris Dutton
Founder & CPO
Chris is an EdTech entrepreneur and best-selling Data Analytics instructor. As Founder and Chief Product Officer at Maven Analytics, his work has been featured by USA Today, Business Insider, Entrepreneur and the New York Times, reaching more than 1,000,000 students around the world.
Student reviews
Wonderful, got a lot more than I expected from the course...way more than expected. Sad I only came across Maven last week.
Matthew
I’m really grateful for the opportunity to take part in the Data Literacy Foundation course. It was such a valuable experience that helped me build a stronger understanding of how to work with data ,from identifying reliable sources to making sense of numbers in real-world contexts. The content was clear, practical, and beginner-friendly, yet still challenged me to think critically. I especially appreciated the focus on real-life applications and how data impacts decision-making across different fields
Moses Ogilo
Taking the Data Literacy and Foundation course was a fantastic decision! It provided me with a strong understanding of key data concepts, and I gained insights I hadn’t encountered before. I highly recommend this course to aspiring data analysts and anyone looking to deepen their knowledge of data
Racheal wilson
Included learning paths
Course credential
You’ll earn the course certification by completing this course and passing the assessment requirements

Data Literacy Foundations

Data Literacy Foundations
CPE Accreditation

CPE Credits:
0
Field of Study:
Information Technology
Delivery Method:
QAS Self Study
Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.
For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.
*Last Updated: May 25, 2023
Course Description
We live in a world that runs on data.
It’s how Amazon and Netflix know which movies and products to recommend, how Starbucks manages a global supply chain, how banks detect fraud, and how Uber connects drivers with passengers in real-time.
But data skills aren’t just for tech companies or professional analysts anymore.
Whether you’re a teacher using test scores to improve lesson plans, a sales manager tracking monthly quotas, or a marketer exploring customer trends, data can help you work smarter and make better, more impactful decisions.
In this course, we’ll set the stage by discussing what data literacy means, share frameworks to help you assess and benchmark your skills, and review the elements of a successful data ecosystem, including data democratization, strategy, architecture, and governance.
From there we’ll dig into each core component of the data literacy skill set – interpreting, managing, analyzing and communicating with data.
You’ll practice interpreting tabular datasets and charts, learn how to apply profiling and QA techniques, and review methods for accessing, storing, and transforming data for analysis.
Next we’ll introduce proven frameworks designed to help you think and problem-solve like a world-class data professional, and break down the differences between descriptive, diagnostic, predictive and prescriptive analytics.
We’ll also explore the power of data visualization and storytelling. We’ll review key principles and best practices for communicating with data, walk through common visualization mistakes and how to correct them, and show you how to craft clear, data-driven narratives.
Last but not least we’ll talk about what data literacy means in the age of AI. We’ll demo some incredible use cases for generative AI tools like ChatGPT and Gemini, share prompt engineering tips and best practices, and address common limitations and pitfalls to be aware of.
Whether you’re an individual looking to build confidence, a leader seeking to empower and upskill your team, or a data professional just trying to stay ahead of the curve, this is the course for you.
Course Description
We live in a world that runs on data.
It’s how Amazon and Netflix know which movies and products to recommend, how Starbucks manages a global supply chain, how banks detect fraud, and how Uber connects drivers with passengers in real-time.
But data skills aren’t just for tech companies or professional analysts anymore.
Whether you’re a teacher using test scores to improve lesson plans, a sales manager tracking monthly quotas, or a marketer exploring customer trends, data can help you work smarter and make better, more impactful decisions.
In this course, we’ll set the stage by discussing what data literacy means, share frameworks to help you assess and benchmark your skills, and review the elements of a successful data ecosystem, including data democratization, strategy, architecture, and governance.
From there we’ll dig into each core component of the data literacy skill set – interpreting, managing, analyzing and communicating with data.
You’ll practice interpreting tabular datasets and charts, learn how to apply profiling and QA techniques, and review methods for accessing, storing, and transforming data for analysis.
Next we’ll introduce proven frameworks designed to help you think and problem-solve like a world-class data professional, and break down the differences between descriptive, diagnostic, predictive and prescriptive analytics.
We’ll also explore the power of data visualization and storytelling. We’ll review key principles and best practices for communicating with data, walk through common visualization mistakes and how to correct them, and show you how to craft clear, data-driven narratives.
Last but not least we’ll talk about what data literacy means in the age of AI. We’ll demo some incredible use cases for generative AI tools like ChatGPT and Gemini, share prompt engineering tips and best practices, and address common limitations and pitfalls to be aware of.
Whether you’re an individual looking to build confidence, a leader seeking to empower and upskill your team, or a data professional just trying to stay ahead of the curve, this is the course for you.
Curriculum
1
Getting Started
1
Getting Started
1
Getting Started
2
Why Data Literacy?
2
Why Data Literacy?
2
Why Data Literacy?
3
Data Literacy 101
3
Data Literacy 101
3
Data Literacy 101
4
Interpreting & Managing Data
6 MIN
6 MIN
6 MIN
4
Interpreting & Managing Data
6 MIN
6 MIN
6 MIN
4
Interpreting & Managing Data
6 MIN
6 MIN
6 MIN
5
Analyzing Data
5
Analyzing Data
5
Analyzing Data
6
Communicating with Data
6 MIN
6 MIN
6 MIN
6 MIN
6
Communicating with Data
6 MIN
6 MIN
6 MIN
6 MIN
6
Communicating with Data
6 MIN
6 MIN
6 MIN
6 MIN
7
Data Literacy + AI
6 MIN
6 MIN
6 MIN
7
Data Literacy + AI
6 MIN
6 MIN
6 MIN
7
Data Literacy + AI
6 MIN
6 MIN
6 MIN
8
Key Takeaways
6 MIN
6 MIN
8
Key Takeaways
6 MIN
6 MIN
8
Key Takeaways
6 MIN
6 MIN
9
Course Feedback & Next Steps
9
Course Feedback & Next Steps
9
Course Feedback & Next Steps
Meet your instructors

Chris Dutton
Founder & CPO
Chris is an EdTech entrepreneur and best-selling Data Analytics instructor. As Founder and Chief Product Officer at Maven Analytics, his work has been featured by USA Today, Business Insider, Entrepreneur and the New York Times, reaching more than 1,000,000 students around the world.
Student reviews
Wonderful, got a lot more than I expected from the course...way more than expected. Sad I only came across Maven last week.

Matthew
I’m really grateful for the opportunity to take part in the Data Literacy Foundation course. It was such a valuable experience that helped me build a stronger understanding of how to work with data ,from identifying reliable sources to making sense of numbers in real-world contexts. The content was clear, practical, and beginner-friendly, yet still challenged me to think critically. I especially appreciated the focus on real-life applications and how data impacts decision-making across different fields

Moses Ogilo
Taking the Data Literacy and Foundation course was a fantastic decision! It provided me with a strong understanding of key data concepts, and I gained insights I hadn’t encountered before. I highly recommend this course to aspiring data analysts and anyone looking to deepen their knowledge of data

Racheal wilson
Included learning paths
Course credential
You’ll earn the course certification by completing this course and passing the assessment requirements

Data Literacy Foundations

Data Literacy Foundations
CPE Accreditation

CPE Credits:
0
Field of Study:
Information Technology
Delivery Method:
QAS Self Study
Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.
For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.
*Last Updated: May 25, 2023
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