“In this eBook, I offer a detailed iterative approach to building a data mesh, rooted in its four core principles and enriched by lean manufacturing methodologies. This approach is based on the idea that building must be viewed as a learning process, one that organizations can embark on swiftly by leveraging their existing human and technological resources.”
– Guillaume Bodet – Co-founder & CPTO, Zeenea
This guide is designed to arm you with practical strategies for implementing data mesh in your organization, helping you:
Understand the critical factors behind the rise of decentralized data management and data mesh adoption.
Start your data mesh journey with a focused pilot project, leveraging an initial use case.
Discover efficient methods for scaling up your data mesh, enhancing the creation of data products.
Acknowledge the pivotal role an internal marketplace plays in facilitating the effective consumption of data products.
Learn how Zeenea emerges as a robust supervision system, orchestrating an enterprise-wide data mesh.
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Here is the link to “The Practical Guide to Data Mesh”.
Centralized and monolithic data management, anchored in a data lake or warehouse, creates a massive bottleneck that stifles innovation and hinders data teams from meeting the rapidly evolving demands of the business. In response, the industry is progressively embracing decentralized data management, especially through the data mesh.
Introduced by Zhamak Dehghani in 2019 and inspired by Amazon’s early 2000s transformation, this paradigm shift is grounded in four fundamental principles: domain-oriented decentralized data ownership and architecture, data as a product, self-serve data infrastructure as a platform, and federated computational governance.
While the data mesh is well-documented, literature often portrays an idealized end state without detailing the practical steps to achieve it. This gap raises a crucial question: how can organizations effectively transform their data management practices and implement a data mesh.