Decentralized Data Management for Scalability, Agility, and Innovation
What you will learn
Understand the principles and practices of Data Mesh and its pillars
Identify common challenges in centralized data management and learn how to overcome them
Develop the skills to align operational and analytical data strategies to enhance decision-making and business value extraction
Learn how to build autonomous, domain-specific teams to improve data quality, scalability, and agility in organizational data initiatives
Why take this course?
Data Mesh 101 is an introductory course designed to help data professionals, business leaders, and IT teams understand and implement the principles of Data Mesh, a decentralized approach to data management. This course explores how to overcome common challenges in centralized data systems by promoting domain-specific ownership and fostering a more agile, scalable, and data-driven environment.
Throughout the course, you will learn about the four core pillars of Data Mesh: decentralized domain ownership, data as a product, federated governance, and self-serve data platforms. These pillars aim to address the limitations of traditional data architectures, ensuring that data is managed by the teams most familiar with it, thus improving data quality, accessibility, and alignment with business needs.
You will also gain insights into how to align operational and analytical data strategies, breaking down silos between business and IT departments to enhance decision-making and drive value from data. With a focus on data quality, governance, and scalability, the course will teach you how to set up autonomous teams responsible for managing and governing data in their domains, resulting in more efficient and sustainable data operations.
Whether you’re an experienced data engineer or just beginning your journey with data management, this course provides you with the knowledge to rethink your data strategy and take full advantage of modern decentralized data architectures.