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Streamlining Legacy Complexity Through Modernization
- 1. Streamlining Legacy Complexity Through Modernization We work in a complex and ever-changing arena. Our areas of policy responsibility cover natural and human systems that interact in unpredictable and dynamic ways
- 2. Path to Autonomy with Decentralized Architecture • Data Mesh is a decentralized architecture. • Dealing with diverse data domains and requires agility in data delivery. • Distributed data ownership provides more autonomy and democratization to domain owners. • Domain-specific governance can be adopted, allowing each department or team to manage its data. • Data products are owned and managed by domain experts. • This approach leads to setting up a self- service access area, such as a Data Marketplace. Democratizing Data – Why Data Mesh ?
- 3. The Dynamic Relationship Between Data Fabric and Data Mesh Some experts posit that Data Mesh represents a progressive evolution from Data Fabric. This perspective suggests that as organizations amass increasing volumes of data, a decentralized approach becomes essential for effective management Conversely, there's a contrasting viewpoint advocating the complementarity of Data Fabric and Data Mesh. Advocates of this stance argue that these architectures can work synergistically. Specifically, Data Fabric can serve as a robust foundation for Data Mesh, while the latter extends and enhances the capabilities established by Data Fabric.
- 4. Data Fabric Vs Data Mesh Feature Data Fabric Data Mesh Architecture Centralized Decentralized Data ownership Centralized Domain-based Data governance Centralized Distributed Scalability Limited High Flexibility Limited High
- 5. Data Mesh Unveiled: Exploring the Layers of Scalable Architecture A data mesh architecture is composed of three separate components: data sources, data infrastructure, and domain-oriented data pipelines managed by functional owners. Underlying the data mesh architecture is a layer of universal interoperability, reflecting domain- agnostic standards, as well as observability and governance. Proposed layered architecture for a data mesh would include the following layers: Data Infrastructure Layer: Responsible for providing foundational infrastructure (storage, compute, networking) for the data mesh Domain-oriented Data Product Layer: Manages and creates domain-specific data products viz. Data Domain for Marine , Rural Land, Marine, Food, Air Quality, International Trade, Waste and Resource system. Each product encapsulates a distinct data domain with all necessary data, metadata, and logic. Self-Service Data Infrastructure Layer: Offers a self-service platform for data engineers and users. Enables the creation and management of data products independently. Federated Computational Governance Layer: Establishes a governance framework for the data mesh. Defines policies for data access, quality, and security. Data Mesh Principals
- 6. Data Mesh Architecture Implementation in Azure : Physical Implementation
- 8. Data Domain : Data mesh embraces bounded context Each data domain owns and operates multiple data products with its own technology stack, which is independent from the others. • Bounded contexts establish logical boundaries in a domain for complexity management. • Teams must know what they can change, including data, and coordinate on shared dependencies. • Clarity on team control and collaboration needs within these boundaries is crucial for effective solutions in a complex system.
- 10. Interconnecting Domain-Specific Data Products: A Referencing Approach