Self-paced course
Self-paced course
Data Literacy Foundations
Data Literacy Foundations
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 course hours
1 assignments & solutions
5 quizzes
Who should take this course
Anyone looking to work smarter, earn more, and make more impactful data-driven decisions
Leaders seeking to upskill or empower teams with critical data skills
Data professionals who want to sharpen their data visualization and storytelling skills
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.
Featured review
"Completing the Data Literacy Foundations course has been an incredible experience. Coming from a project management background, I wanted to strengthen my data skills, and this course delivered exactly that! I’ve learned different tools, methods, and techniques to effectively interpret, manage, analyze, and communicate data, all of which directly support smarter decision-making and project outcomes. This course has given me a strong foundation to continue growing in data analysis, and I would highly recommend it to anyone looking to boost their confidence with data."
Cecilia W.
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
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
Completing the Data Literacy Foundations course has been an incredible experience. Coming from a project management background, I wanted to strengthen my data skills, and this course delivered exactly that! I’ve learned different tools, methods, and techniques to effectively interpret, manage, analyze, and communicate data, all of which directly support smarter decision-making and project outcomes. This course has given me a strong foundation to continue growing in data analysis, and I would highly recommend it to anyone looking to boost their confidence with data.
Cecilia W.
I recently completed the Data Literacy Foundation course from Maven Analytics and found it to be highly valuable. The course content was well-structured and provided a comprehensive understanding of data fundamentals. The practical examples and exercises helped reinforce the concepts effectively. Overall, it has significantly enhanced my data literacy skills and I would highly recommend it to anyone looking to build a strong foundation in data analytics.
Syed Muhammad Saqib
The Maven Analytics Data Literacy Foundation offers a comprehensive curriculum that equips learners with essential skills in data literacy, covering topics ranging from the fundamental importance of data literacy to advanced concepts like data analysis and integration with artificial intelligence (AI). The course begins by elucidating why data literacy is crucial in today's data-driven world, emphasizing its impact on decision-making, problem-solving, and overall organizational effectiveness. Through lessons like Data Literacy 101, participants gain a solid understanding of key data concepts, terminology, and best practices, laying a strong foundation for their data journey. As learners progress through the program, they delve into interpreting and managing data, learning techniques to transform raw data into meaningful insights. The course also focuses on honing analytical skills, empowering participants to extract valuable insights, identify trends, and make data-driven decisions. A pivotal aspect of the curriculum is the emphasis on effective data communication, enabling individuals to convey insights clearly and persuasively, bridging the gap between data analysis and actionable outcomes. Furthermore, the integration of AI into data literacy expands participants' horizons, showcasing the potential of leveraging AI tools and techniques in data analysis and interpretation. Upon completing the Maven Analytics Data Literacy Foundation course, I am profoundly grateful for the wealth of knowledge gained. The course has not only enhanced my understanding of data but has also equipped me with practical skills that I am eager to apply in my work as an aspiring data analyst. I express my deepest gratitude to Maven Analytics for providing such a comprehensive and impactful learning experience, one that has undoubtedly accelerated my journey towards becoming a proficient data professional. #DataLiteracy #DataAnalytics #DataDrivenDecisions #AIIntegration #Gratitude
ERIC ROLLAN AUNZO
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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