A Data Mesh is a decentralized method for sharing and managing analytical data on a large scale, highlighting data as a product and assigning ownership to domain experts. It promotes federated governance and utilizes a shared data platform, fostering innovation in data-intensive organizations.
Data Mesh Accelerator
What is a Data Mesh?
This approach tackles common data challenges head-on by distributing data management and ownership. It alleviates strain on centralized data teams, addresses operational database performance issues, diminishes reliance on ETL jobs, enhances data quality and governance, and facilitates accessibility by breaking down data silos.
Data Mesh Accelerator
Rapidly pilot and explore the advantages of a data mesh within a risk-free environment.
Tailored for organizations grappling with data management and scaling challenges, embarking on significant migration and modernization endeavours, or seeking to unlock innovation and leverage GenAI use cases.
Benefits:
- Remove bottlenecks: From the central data team, by devolving responsibility for data products to domain experts
- Zero-ETL integration: Published data products that can be consumed in place without copying
- Evolutionary architecture: Decoupled and decentralised architecture means that the data platform can flex and scale with the business
- Improved data quality: Data is published and described by decentralised expert teams
- Increased agility: Autonomous domains can run faster with higher agility
- Improved data observability: Platform monitors, data production and consumption metrics
- Improved data provenance: Platform can track lineage and improve auditability
- Improved governance and security: Data platform controls access policies and contracts centrally
Case Study
RenaissanceRe, a data-heavy global reinsurer, faced numerous challenges due to disparate data sources and siloed data. Analytics were being performed against operational tables, hindering efficiency and agility. Additionally, RenaissanceRe recognized the need for modernization of its Application Portfolio to adapt to evolving business requirements.
RenaissanceRe aimed to establish a central, self-service data platform that could accommodate the organizational domain structure and devolve responsibility for data to specific domains. Additionally, they sought improved observability and data lineage, as well as democratized access to data across the organization. The goal was to create an evolutionary, event-driven platform that maximized autonomy for teams, fostering innovation and agility within the organization.
By implementing a Data Mesh architecture, RenaissanceRe achieved the following outcomes. They experienced increased agility across teams, facilitated by secure, democratized access to data. Currently, they have 10TB of data products in production, with plans to increase volume tenfold in the near term. Notably, the integration process was streamlined, with zero-ETL integrations, minimizing complexity and improving efficiency across the organization. This initiative also laid a solid foundation for future migrations.
Architecture Diagram:
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