Data Mesh in Practice

The data mesh is poised to replace data lakes and data warehouses as the dominant architectural pattern in data and analytics. By promoting the concept of domain-focused data products that go beyond file sharing, data mesh helps you deal with data quality at scale by establishing true data ownership. This approach is so new, however, that many misconceptions and a general lack of practical experience for implementing data mesh are widespread.

With this report, you'll learn how to successfully overcome challenges in the adoption process. By drawing on their experience building large-scale data infrastructure, designing data architectures, and contributing to data strategies of large and successful corporations, authors Max Schultze and Arif Wider have identified the most common pain points along the data mesh journey.

You'll examine the foundations of the data mesh paradigm and gain both technical and organizational insights. This report is ideal for companies just starting to work with data, for organizations already in the process of transforming their data infrastructure landscape, as well as for advanced companies working on federated governance setups for a sustainable data-driven future.

This report covers:

• Data mesh principles and practical examples for getting started
• Typical challenges and solutions you'll encounter when implementing a data mesh
• Data mesh pillars including domain ownership, data as a product, and infrastructure as a platform
• How to move toward a decentralized data product and build a data infrastructure platform