• Entry level

Data Essentials Certificate (eDEC)

  • 2 Half days

  • Instructor-led on-site training

Data Essentials image

Overview

This is a foundational certification program designed to equip new workforce entrants and those who work with data as part of their role (not limited to IT roles) with baseline competency in data management principles. Based on internationally recognized ISO standards, the course provides the fundamental knowledge that employers expect from professionals who will work with data in any capacity.

Like a driver’s license proves you know the rules of the road, this Certification proves you know the rules of data.

Employers can require this Certificate as proof that professionals demonstrate an understanding of the fundamentals of safe data management based on ISO international standards.

Key Learning Outcomes

On completing this certification, participants will be able to:

  • Explain the difference between data and information, and why the distinction matters

  • Recognize common data quality issues and understand their impact on business decisions and AI/ML applications

  • Apply ISO 8601 date/time formatting and data standards in everyday work

  • Describe core concepts of ISO 8000, ISO 22745, and ISO 25500 standards

  • Identify how poor data quality affects business decisions and AI/ML accuracy

  • Follow best practices for file naming, version control, and metadata management

  • Interpret data requirements derived from policies, rules, and regulations

  • Arrange your team training – Inquire now

Who should attend?

This certification is designed for:

  • New entrants to the workforce in any industry sector and any discipline
  • Professionals who will work with data as part of their role (not limited to IT roles)
  • Employees transitioning to data-related responsibilities
  • Anyone seeking to demonstrate baseline data management competency

Important: This course is not limited to IT or technical roles. It provides the foundational knowledge that employers expect from all professionals, regardless of their academic background. Whether you studied business, healthcare, engineering, law, sciences, humanities, or any other field, you will work with data in today’s workplace.

There are no formal prerequisites for this course. Participants should have basic computer literacy and familiarity with common office applications (spreadsheets, databases). No prior knowledge of ISO standards or formal data management training is required.

Course Agenda

The program is structured as two half-day training sessions.

Certification Exam

Upon course completion, participants can take the ECCMA Data Essentials Certificate exam. This online, multiple-choice test requires 80% passing grade. Successful candidates will receive an electronic certificate.

ECCMA Data Essentials Certificate (eDEC)

Registration Process

Access to course materials and the certification exam requires registration through the ECCMA website. Organizations wishing to include their company name on the certificate must validate it via an ISO 25500 International Business Identifier (IBID).

Please note

Recording of training sessions is not permitted under the terms of ECCMA Training and Certification. You are not licensed or permitted to record, reproduce or disseminate ECCMA Online training sessions or training resources.

Day 1

  1. Introduction to data management
  • Welcome and course objectives
  • Why data fundamentals matter in an AI-driven world
  • The concept of baseline competency in data management
  • Data is everywhere: why this course matters for all professionals
    • Whether entering finance, healthcare, manufacturing, engineering, marketing, or any other field
    • You don’t need to be “technical” to understand and apply data quality principles
    • Cross-industry examples and applications
  • Overview of ISO standards covered (8000, 22745, 25500, 8601)
  • How AI systems amplify both good and bad data practices
  1. Data Fundamentals
  • Understanding the difference between data and information
  • Key principles of information quality
  • Types of organizational data:
    • Master data
    • Transactional data
    • Reference data
  • What is metadata and why it matters
  • Why using correct terminology is important
  • Why data standards matter
  • Data portability: ensuring data can move between systems
  • Data as the foundation for AI applications
  1. Data Quality Principles
  • What makes data “quality” data
  • The relationship between data quality and information quality
  • Dimensions used to assess data quality
  • Recognizing common data problems
  • How data quality impacts business decisions
  • Understanding data requirements
  • Data quality and AI/ML
  1. ISO 8000 – Data Quality & Portability
  • Introduction to ISO 8000
  • The concept of quality as meeting requirements
  • Portable data and avoiding data lock-in
  • Date and time formatting standards (ISO 8601)
  • How standards compliance supports AI-ready data

Day 2

  1. ISO 22745 – Open Technical Dictionaries
  • Purpose of technical dictionaries
  • Working with metadata and reference data
  • Standardized terminology in practice:
  • The role of consistent definitions in AI training data
  1. ISO 25500 – Data Validation
  • Principles of supply chain data interoperability
  • Overview of the Industrial Internet
  • Data validation concepts and techniques
  • Validation as a quality gate for AI systems
  • Practical approaches to checking data before use
  1. Practical Skills & Exercises
  • Best practices for file naming and version control
  • Introduction to data profiling techniques
  • Understanding data relationships
  • Working with ECCMA tools and applications
  • Exercise: Evaluating data for AI/ML readiness
  • Introduction to data visualization
  • Conclusion 
  • Course summary and key takeaways
  • Introduction to data governance
  • Understanding data stewardship and your role
  • Basic awareness of roles and responsibilities in data management
  • Your contribution to data quality from day one
  • Next steps: post-course online assessment
  • Resources for continued learning
  • Q&A