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DL 101 – Introduction to Data Literacy

This course is designed to teach the foundations of data literacy, so that professionals in all fields can develop the basic capabilities for being data literate

Data Literacy: What It Is, What it is NOT, and How to Achieve It

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Description

This course is designed to teach the foundations of data literacy, so that professionals in all fields can develop the basic capabilities for being data literate. This interactive course provides a combination of lecture and small workshop exercises that allow the student to grasp and practice the concepts of data literacy for any enterprise. It blends the concepts of data literacy with the enterprise view of data collection, definition, management, and usage.

 

Objectives

  • Explain the foundational concepts of data literacy to professionals at all levels, including managers and executives
  • Identify the best practices for building and maintaining a data literate workforce
  • Develop a clear understanding of the value and benefits of adopting an enterprise view of data literacy for competitive advantage
  • Understand how data literacy (or data illiteracy) can affect the performance of an
  • organization

Seminar Content

  • Foundations of Data Literacy
    • Definitions of data literacy (what it is and what it is not)
    • Developing an enterprise approach to data literacy
    • Roles and personas for effective data literacy
  • Data Literacy Maturity Model
    • What is a maturity model?
    • Basics of a maturity model for data literacy
    • Data literacy assessment overview
    • Implementing a data literacy maturity model in an organization
    • Overview of 8 key data literacy dimensions
  • Data Literacy Roles and Personas
    • Understanding the various roles in a data literate environment
    • Determining the personas for data literacy in an organization
    • Value and benefits of identifying and using roles and personas to advance an organization’s data literacy
    • Data literacy stakeholders and their interactions
    • Data literacy return on investment (ROI)
  • Data Literacy Concepts and Principles
    • Foundational best practices of a data literate organization
    • Importance of using data literacy concepts and best practices to continually improve an organization’s data literacy
    • Implementing data literacy best practices for effective data management and usage
  • Challenges to Effective Data Literacy
    • Main obstacles to organizational data literacy
    • Political and organizational issues that affect data literacy
    • Keys to effective data literacy
    • 10 steps to data literacy improvement
    • Maintaining organizational data literacy
    • Addressing resistance to data literacy improvement
    • Issues and Challenges for Data Modeling and Data Analysis
  • Conclusion
    • Workshop Summary, Additional Exercises and Reference Materials

About the Course Designer

This training was designed by David Marco, PhD, an internationally recognized authority on data and AI governance, to help teams succeed in real organizational conditions. The curriculum equips participants with practical judgment, shared language, and decision clarity that hold under scale, risk, and executive accountability.

David Marco PHD EWSolutions

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