Data Management & Strategy Based On Dama

Master the pillars of modern Data Management with a strategic approach aligned to the international DAMA standard

What you'll learn

Understand what data management is and why it is strategic for any organization

Gain in-depth knowledge of the DAMA-DMBOK framework and its structured approach to data management

Design a data strategy aligned with business objectives and focused on generating value

Identify and prioritize data management initiatives based on impact, effort, and organizational maturity

Understand the fundamentals of data integration and the various architectures such as ETL, ELT, and virtual

Recognize the key role of governance in interoperability processes and data protection

Apply data governance principles: role assignment, standards definition, and monitoring

Distinguish between logical and physical data modeling, and understand how to adapt them to different organizational contexts

Structure the management of unstructured data and the documentation lifecycle

Understand how Data Warehousing and Business Intelligence support the data strategy

Explore real implementation cases of strategy, integration, governance, modeling, and data management

Internalize best practices to build an organizational culture based on reliable and business-aligned data

Requirements

Familiarity with data-related terminology can be helpful, but no prior knowledge is required

Description

Do you want to learn how to transform data into a true strategic asset for your organization? Are you interested in designing a solid data strategy, improving information quality, and ensuring effective governance? Then this course, “Data Management & Strategy Based on DAMA”, is exactly what you need.In this course, you will discover the fundamental principles of Data Management and how to apply them using the internationally recognized DAMA-DMBOK framework. You will learn how to develop a data strategy aligned with business objectives, prioritize initiatives effectively, and structure data management with a global and sustainable vision.We will dive deep into key areas such as data integration and interoperability, data governance, logical and physical modeling, content and business documentation management, as well as business intelligence and data warehousing environments.You will also explore the role of Master Data Management (MDM) and Data Quality within a well-governed strategy. All of this will be covered with a practical approach and real-world cases, helping you apply what you learn to common professional scenarios.This course is designed both for data professionals and for those with no prior experience who want to enter the field of Data Management. With a clear, progressive, and flexible approach suited to different levels, you’ll gain a comprehensive and actionable understanding of how to structure, govern, and leverage data in any type of organization.Enroll now and learn how to build a data strategy that drives efficiency, innovation, and value in your company!

Overview

Section 1: Introducción

Lecture 1 What is Data Management and Why Does It Matter?

Lecture 2 The DAMA Framework and Its Strategic Approach

Section 2: Data Management Strategy

Lecture 3 Data as a Strategic Asset: Principles and Challenges

Lecture 4 How to Develop a Business-Aligned Data Strategy

Lecture 5 Tools to Prioritize Data Management Initiatives

Lecture 6 Practical Case: Designing a Basic Strategy

Lecture 7 Real-World Example: A Data Strategy for a Tech SME

Section 3: Data Integration and Interoperability

Lecture 8 Key Concepts in Data Integration

Lecture 9 Integration Architectures: ETL, ELT and Data Virtualization

Lecture 10 Governance in Data Interoperability

Lecture 11 Real-World Example: Data Consolidation in a Banking Company

Section 4: Data Governance in Practice

Lecture 12 Overview of Data Governance

Lecture 13 How to Establish Effective Policies and Standards

Lecture 14 Key Metrics to Assess Data Governance

Lecture 15 Introduction to MDM within the Data Governance Framework

Lecture 16 Introduction to Data Quality within the Data Governance Framework

Lecture 17 Real-World Example: Implementing Data Policies in a Multinational Company

Section 5: Advanced Data Modeling and Design

Lecture 18 Differences Between Logical and Physical Modeling

Lecture 19 How to Adapt Data Models to Complex Scenarios

Lecture 20 Real-World Example: Building a Logical Model for a Supermarket Chain

Section 6: Content and Documentation Management

Lecture 21 The Role of Unstructured Data in Business Strategy

Lecture 22 Best Practices for Content Lifecycle Management

Lecture 23 Real-World Example: Content Lifecycle Management in a Media Company

Section 7: Data Warehousing and Business Intelligence

Lecture 24 Fundamentals of Data Warehousing and BI

Lecture 25 How These Technologies Support Data Strategy

Lecture 26 Real-World Example: Implementing a Sales Analysis Data Mart

Section 8: Real-World Cases by Topic

Lecture 27 Data Management Strategy

Lecture 28 Data Integration and Interoperability

Lecture 29 Data Governance

Lecture 30 Data Modeling and Design

Lecture 31 Content and Documentation Management

Anyone who wants to learn how to manage data strategically to improve decision-making,Professionals who want to understand how to apply the DAMA-DMBOK framework to structure and align data management,Individuals with no prior experience in data who want to enter the world of Data Management and learn its key principles,Managers and team leaders seeking to implement an effective data strategy and improve governance,Students and recent graduates interested in starting a career in one of the most promising fields in the digital era,Developers, data scientists, or IT professionals who want to better understand organizational data management,Entrepreneurs, freelancers, or professionals from any sector looking to use data more efficiently and strategically,Business consultants who want to understand the fundamentals and benefits of a well-structured data strategy