Data Management - Fundamentals and Solutions

Name: Data Management - Fundamentals and Solutions
Rating: 5.0 (26 reviews)

Learn essential data technologies, operating models, and practical solutions for modern data management

Highest Rated

Created byAlbert Fabritius, Olawanle Precious

Last updated 11/2025

English

What you'll learn

Key Technology Concepts: Gain an understanding of essential data management technologies, including ETLs, integrations, data lakes, and data warehouses.
Data Management Operating Model: Learn the foundational pillars of a data management operating model.
Advanced Solution Implementation: Explore the alternatives for selecting and implementing advanced data solutions within an organization.
Toolsets and Processes: Discover sample toolsets and processes that provide practical and cost-effective solutions to most data management challenges.

Course content

4 sections • 26 lectures • 5h 0m total length

Introduction & Blind Spot8:43
Course Content2:39
Data Management & its 5 Dimensions12:37
Evolution Curve of Organizational Data Management13:57
This chapter explains how organizations assess and improve their data management performance.
Data Science vs Data Engineering8:05
In this chapter, we will learn about Data Engineering and Data Science.

Solution Ecosystem3:00
Cloud9:54
Core Functionalities10:11
Integrations6:37
Queries12:12
In this chapter, we’ll learn about queries and how they help us retrieve specific information from a database.
ETL-ELT14:34
In this chapter, we will learn about ETL and ELT processes and how they help integrate data across different systems.
OLTP vs OLAP14:53
In this chapter, we learn the key differences, functions, and use cases of OLTP and OLAP.
OLAP Architectures8:38
In this chapter, we learn hoe OLAP system organize data into cubes and dimensions to enable fast, flexible analysis and reporting.
Data Warehouse vs Data Lake8:23
This chapter teaches differences between data warehouses and data lakes, including storage, structure, and uses.
RPA13:24
In this chapter, we will learn how RPA software robots automate repetitive tasks and improve workflow efficiency
Artificial Intelligence AI16:58
In this lesson, we will learn about Artificial Intelligence (AI).
Scheduler Orchestrator5:41
In this chapter, we’ll learn how schedulers and orchestrators automate data pipelines.
Architectures14:29
In this chapter, we will learn about different system architectures and how they structure, organize, and manage data workflows.

Reporting and Analytics6:31
In this lesson, we learn how Reporting and Analytics turns raw data into useful insights.
Inhouse vs Outsourcing9:55
In this chapter, we will learn the difference between in house work and outsourcing, and how each approach affects cost, control, and efficiency.
Support Model9:15
In this lesson, we learn how Support Models define the wat a business is organized to help its users and solve problems.
Agile Methodology6:23
In this lesson, we learn how Agile Methodology helps teams manage projects in short, flexible cycles.
Data Governance22:53
In this lesson, we will learn about Data Governance
Skills and Knowledge13:34
In this lesson, we will learn that skills and knowledge are better retained when spread across many teams, not held by just a few.
Provider & Implementation16:09
In this lesson, we explore tool driven vs use case driven implementation and its impact on provider selection.

Requirements

Basic Data Management Knowledge: A basic understanding of everyday data challenges is helpful.
No Advanced Skills Needed: No prior programming experience or advanced technological knowledge is required. You’ll learn everything you need to succeed.

Description

In today’s data-driven world, organizations depend on fast, reliable, and well-structured data to make smarter decisions. Yet many teams still struggle with scattered systems, inconsistent processes, and a lack of clarity around how data should actually be managed. This course provides a clear and practical introduction to modern Data Management, giving you a solid foundation in the essential technologies that power successful data ecosystems—ETLs, integrations, data lakes, and data warehouses. You’ll learn how these systems connect, support analytics, and solve real business problems.

Beyond the technology, the course walks you through the core pillars of a strong data management operating model. You’ll explore how organizations structure governance, roles, responsibilities, and processes to ensure data remains accurate, accessible, and secure. With real-world examples and simple explanations, you’ll see how effective operating models reduce complexity, increase efficiency, and improve decision-making at every level.

Finally, you’ll dive into practical solution design and modern implementation strategies. From evaluating toolsets to selecting cost-effective systems, you’ll discover how organizations choose the right solutions for their needs—without overspending or overcomplicating their architecture. Whether you’re working with data directly or leading teams that depend on it, this course gives you the clarity, confidence, and strategic insight needed to contribute to successful data initiatives and drive meaningful business outcomes.

Why This Course Stands Out

Breaks down complex data concepts into simple, practical explanations anyone can follow
Covers the full spectrum of modern data management—from technologies to operating models
Helps you understand how real organizations build, govern, and scale their data systems
Designed for busy professionals who want clarity without technical overwhelm
Includes real-world examples that show how data roles, processes, and solutions work in practice
Equips you with the strategic insight needed to support better decision-making in any company
Ideal for both future data leaders and current professionals looking to upgrade their skillset

Enroll now and start building the clarity and confidence you need to excel in modern data management.

Who this course is for:

Aspiring Chief Data Officers: Professionals aiming to become Chief Data Officers.
Decision Makers: Leaders seeking to enhance their organization’s data management capabilities.
Data Analysts: Analysts who face challenges with their current toolsets and are looking for more effective solutions.

Data Management - Fundamentals and Solutions

What you'll learn

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Course content

Foundations of Data Management5 lectures • 46min

Tools, Systems & Technical Ecosystem13 lectures • 2hr 19min

Business Operations, Governance & Delivery7 lectures • 1hr 25min

Practical Demo1 lecture • 31min

Requirements

Description

Who this course is for: