
Anti-Patterns in Data Mesh
This article explores common anti-patterns in implementing Data Mesh, a decentralized data architecture emphasizing domain-oriented data ownership. While Data Mesh aims to enhance data accessibility and usability across organizations, its success relies on understanding core principles: domain-driven data ownership, data products, and federated governance.

Data Mess to Data Mesh
The standard strategy of centralizing data into a single repository often leads to chaotic "data swamps.” Due to poor data quality and governance issues, these swaps hinder efficient analysis and decision-making. An alternative approach, known as Data Mesh, proposes a decentralized architecture focused on treating data as a product.

Your Starter Guide to Data Governance
Data governance establishes standards for data collection, storage, and analysis, ensuring accuracy and mitigating risks associated with regulatory non-compliance. Moreover, governance promotes ethical data practices, safeguarding individual privacy rights and societal norms.