---
url: "https://xcademia.com/courses/cdmp-data-management-foundations-training"
title: CDMP Data Management Foundations Training
description: "Learn data governance, quality, and architecture in this 3-day CDMP Foundations course aligned with DAMA DMBOK. Prepare for CDMP Associate."
publishedAt: "2026-03-23T04:57:30.733002+00:00"
updatedAt: "2026-05-16T11:11:01.30338+00:00"
type: course
code: "AID-0089"
level: Foundation
duration_days: "3"
track: "Data Engineering & Warehousing"
category: "AI, Data & Analytics"
credential_tier: tier1
price_gbp: "1999"
---

# CDMP Data Management Foundations Training

> Build a strong foundation in data management aligned with the DAMA Body of Knowledge. Prepare for CDMP Associate with mentor-led training and practical scenarios.

## Overview

The CDMP Data Management Foundations Training is a mentor-led programme designed to introduce learners to the core disciplines of data management aligned with the DAMA Body of Knowledge (DMBOK). This course provides a structured understanding of how organisations manage, govern, and leverage data as a strategic asset.

Through practical scenarios and guided discussions, participants will explore key domains such as data governance, data quality, data architecture, and data integration. The course emphasises real-world application, helping learners understand how to implement frameworks, policies, and controls within modern data environments.

By the end of the programme, learners will have a clear understanding of data management principles and be well-prepared for the CDMP Associate certification. The course supports both exam readiness and the ability to contribute effectively to data-driven organisations.

## Prerequisites

- Basic understanding of business processes
- Familiarity with data concepts
- No prior governance experience required

## What you will learn

- Design foundational data management frameworks
- Analyse data governance structures and roles
- Implement data quality monitoring practices
- Evaluate data architecture and integration approaches
- Communicate data management concepts effectively
- Lead foundational data governance initiatives

## Skills you will gain

- Data governance fundamentals
- Data quality management basics
- Data architecture concepts
- Data integration principles
- Master data management
- Metadata and lineage basics

## Career progression

- Data Analyst
- Data Steward
- Data Governance Analyst
- Business Analyst

## Curriculum

1. **Module 1**
2. **Module 2**
3. **Module 3**
4. **Module 4**

## Exam & certification

## Delivery options

- **Live Online** — Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- **Onsite Training** — We come to you. Training delivered at your workplace for teams of 6 or more.
- **Venue-Based** — Classroom training at a professional venue. Ideal for focused, immersive learning.
- **Blended** — Combine online and in-person learning for maximum flexibility and impact.

## Frequently asked questions

**Is this course suitable for non-technical professionals?**

Yes, it is designed for both technical and business roles.



**Does it cover the full CDMP syllabus?**

It covers the core domains required for the Associate level.



**Will I get practical exposure?**

Yes, through practical scenarios and guided exercises.



**Do I need prior experience in data governance?**

No, this is a foundational course.



**What certificate will I receive?**

You will receive a Certificate of Completion after the course.

## Course at a glance

| Field | Value |
| --- | --- |
| Code | AID-0089 |
| Duration | 3 days |
| Level | Foundation |
| Track | Data Engineering & Warehousing |
| Category | AI, Data & Analytics |
| Credential tier | tier1 |
| Price (GBP) | £1999 |

---

## About this content

This Markdown course profile is the citation-grade twin of [CDMP Data Management Foundations Training](https://xcademia.com/courses/cdmp-data-management-foundations-training). It is published by **Xcademia** (UK Companies House 12322710) and is available for AI search engines and large language models to index, summarise, and cite.

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