Data Mesh with SAP Datasphere
We often hear the question of whether it would make more sense to implement a Data Fabric or a Data Mesh. On closer inspection we find that this question is not asked correctly in this way. To be able to ask this question in the right way, let me first work out what Data Fabric and Data Mesh actually is.
Data Fabric is a technical architecture that brings together heterogeneous data that spans across multiple data sources; it allows organizations to monitor and manage data regardless of the location, considering appropriate data governance and data cataloging.
Data Mesh is a new decentralized sociotechnical paradigm that provides a new approach to sourcing, sharing, accessing and managing analytical data at scale. It treats data as a product, considers domains as a primary concern, applies platform thinking to create self-serve data infrastructure and introduces a federated computational model of data governance.
A Data Mesh and a Data Fabric both give an architecture to get data across numerous platforms and technologies. Still, a Data Fabric is technology-centric, while a Data Mesh centers around organizational change. A Data Fabric can be built without adopting a Data Mesh architecture. To create data products, Data Mesh should depend on the Data Fabric’s discovery, integration and analysis principles.
Initial surveys, such as an expert interview that I was able to take part in recently, clearly show as a best practice that an existing Data Fabric must be used to successfully implement a Data Mesh. Organizations need to consider including elements of Data Fabric, particularly to address challenges related to federated computational governance, which have been cited as key barriers to successful Data Mesh adoption.
With the announcement of our SAP business data fabric, we are going a significant step further. SAP Datasphere – and its open data ecosystem – is the foundation for a business data fabric. It equips any organization to deliver meaningful data to every data consumer — with business context and logic intact.
While the business data fabric is designed to enable Data Mesh architectures, it also augments the business value of Data Mesh with agile delivery of data in business terms.
The introduction of the new Analytic Model is testament for how SAP emphasis the business aspect of a Data Mesh where the data products deliver unparalleled semantic value with important aspects such as exception aggregation or hierarchical associations.
The introduction of the new Replication Flow complements the strong proximity to SAP source systems with the ability to integrate and export into non-SAP sources. This facilitates customers to span the Data Mesh across the entire IT stack with SAP Datasphere.
The introduction of the new SAP Datasphere Catalog enables all data to be discovered, managed and controlled to ensure governance throughout the data lifecycle.
The real question is not Data Mesh or Data Fabric, but how quickly a business data fabric can be implemented to effectively support a Data Mesh implementation.
- Further Information:
- More than just a hype: Data Mesh as a new approach to increase agility in value creation from data
- Data Mesh with SAP Business Technology Platform Part 1 – SAP Data Warehouse Cloud
- Data Mesh with SAP Business Technology Platform Part 2 – SAP HANA Cloud
- Data Mesh with SAP Business Technology Platform Part 3 – SAP Master Data Governance
- Data Mesh with SAP Business Technology Platform Part 4 – SAP Data Intelligence Cloud
- Data Mesh with SAP Business Technology Platform Part 5 – SAP Analytics Cloud
- Data Mesh Architecture by INNOQ: