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Data Management for Beginners - Main Principles
Rating: 4.4 out of 5(66 ratings)
241 students

Data Management for Beginners - Main Principles

Understand data governance, ownership, quality, security, and the human factors behind a data-driven organization.
Created byArtemakis Artemiou
Last updated 5/2026
English
English [Auto],

What you'll learn

  • Distinguish data management from data governance.
  • Explain the responsibilities of data owners, stewards, and custodians.
  • Describe the roles of data policy, metadata, quality, security, and auditing.
  • Explain how people and organizational culture affect data practices.
  • Outline the main considerations in a transition toward data-driven decision-making.
  • Recognize how database, security, and introductory AI topics relate to data management.

Course content

10 sections • 59 lectures • 2h 37m total length

  • Welcome to the Course! What Will you Learn?3:02

    This is the introduction to the course. We will talk about what you will be learning throughout the course.

  • What is Data Management?1:31

    In this lecture, we will be discussing about Data Management; what it is and how it is used.

  • Real-World Applications of Data Management (New)2:03

    In this lecture, we’ll be exploring real-world scenarios where data management plays a critical role in driving decisions, improving efficiency, and ensuring compliance. By the end of the lecture, you’ll see the tangible value of learning these principles.

  • Data Management vs. Data Governance1:56

    In this lecture, we will be comparing Data Management with Data Governance and we will identify their main similarities and differences.

  • Section Recap0:41

    This lecture, is a recap of what you have learned in this section.

  • Introduction

Requirements

  • No previous data-management experience is required.
  • Basic familiarity with how an organization uses information is helpful.
  • The course is conceptual; no database installation or programming environment is required for the core material.

Description

Learn the essential principles behind effective data management and understand how organizations can make their data more trusted, secure, organized, and useful.

This beginner-friendly course introduces the core concepts of data management and data governance and explains the roles, processes, responsibilities, and organizational practices that shape how data is managed throughout its life cycle.

If you work with data, technology, analytics, business systems, or digital transformation and want to understand the bigger picture behind effective data practices, this course provides a clear foundation.


Understand the Foundations of Data Management

Organizations generate and collect enormous amounts of data, but having more data does not automatically lead to better decisions.

Data needs to be understood, managed, protected, maintained, and governed.

You will explore key data-management concepts including:

  • Data management principles.

  • Data governance.

  • Data ownership and accountability.

  • Data quality.

  • Metadata.

  • Data security.

  • Data policies.

  • Data auditing.

  • Data life-cycle considerations.

  • Data roles and responsibilities.

These concepts provide the foundation for understanding how organizations can improve the way they manage and use their information.


Understand Data Governance and Accountability

Effective data governance requires clear responsibilities.

You will learn about important roles such as:

  • Data owners.

  • Data stewards.

  • Data custodians.

You will explore how these roles contribute to decisions about data quality, access, protection, accountability, and appropriate use.

Understanding these responsibilities helps explain why successful data management is not simply a technical responsibility belonging to database administrators or IT departments.

It is an organizational capability.


Explore Data Quality, Metadata, Security, and Policy

Data needs to be trustworthy before it can support reliable reporting, analytics, automation, or decision-making.

The course introduces important areas such as data quality, metadata management, security, policy, and auditing.

You will learn why these disciplines matter and how they contribute to a more controlled and reliable data environment.

This foundation is especially useful for understanding the challenges organizations face when data is duplicated, inconsistent, poorly documented, insecure, or difficult to locate.


Understand the Human Side of Data Management

Technology alone does not create good data management.

People, responsibilities, processes, and organizational culture play an equally important role.

A dedicated section explores the importance of data-management culture and why employees across business and technology teams need to understand their responsibilities toward data.

You will see how collaboration between technical teams, business users, governance functions, and leadership influences the success of data initiatives.


Understand What It Means to Become Data-Driven

Many organizations aim to become more data-driven, but this involves more than introducing dashboards or analytics platforms.

You will explore how data management supports better decision-making and why governance, quality, accountability, and organizational change are essential components of a data-driven organization.

This gives you a broader framework for understanding conversations around:

  • Data strategy.

  • Analytics.

  • Business intelligence.

  • Digital transformation.

  • Artificial intelligence.

  • Enterprise data platforms.


Build a Broader Data Foundation

The course also introduces additional topics that help connect data-management principles with the wider technology environment.

These include:

  • Relational database concepts.

  • Data security.

  • Modern data-management practices.

  • Artificial intelligence and its relationship with data.

These topics help you understand where data management fits within modern enterprise technology and why strong data foundations become increasingly important as organizations adopt analytics and AI.


Who Is This Course For?

This course is suitable for:

  • Complete beginners in data management.

  • Professionals moving into data-related roles.

  • Business analysts.

  • Data analysts.

  • Database and IT professionals.

  • Project managers and technology professionals.

  • Professionals involved in governance, compliance, or digital transformation.

  • Managers who want to better understand organizational data responsibilities.

  • Anyone interested in how organizations manage and govern their data.

No previous data-management experience is required.

The course focuses on fundamental principles and organizational concepts rather than implementation within a specific technology platform.


Build Your Data Management Foundation

By the end of the course, you will understand the main principles of data management and governance, recognize important data roles and responsibilities, and explain why data quality, metadata, security, policy, and organizational culture matter.

You will also have a stronger understanding of how good data-management practices support analytics, decision-making, digital transformation, and modern AI initiatives.


If you want to understand how organizations manage data beyond databases and technology alone, this course gives you a structured and practical foundation.

Who this course is for:

  • Beginners entering data, governance, or business-analysis roles.
  • Managers and team members who want a shared understanding of data responsibilities.
  • Technical professionals seeking an introduction to the organizational side of data management.

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