Rapidly pilot and explore the advantages of a data mesh within a risk-free environment using our templates and expertise in data services such as; S3, AWS Glue, Athena, Redshift, AWS Lake Formation, Amazon DataZone, Dremio, Snowflake, Databricks, PowerBI, and QuickSight.
Tailored for organisations grappling with data management and scaling challenges, embarking on significant migration and modernisation endeavours, or seeking to unlock innovation and leverage GenAI use cases.
What is Data Mesh?
Data Mesh is a decentralised architecture for sharing and managing analytical data on a large scale. The Mesh architecture emphasises data as a product and assigns ownership to domain experts. It promotes federated governance and utilises a shared data platform, fostering innovation in data-intensive organisations.
This approach tackles common data challenges head-on by distributing data management and ownership.
It alleviates strain on centralised 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.
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
How it works
1. Discovery
The accelerator begins with a discovery workshop. Following this we work with you to understand the data landscape of your organisation and identify pilot data products and business use cases.
2. Pilot
During the pilot phase, we deploy our Mesh Accelerators to rapidly build out a self-service platform on top of AWS native data services. We work collaboratively with internal customer teams to define data contracts and enable the creation of pilot data products. This is an iterative and transparent process that is focused on delivering the identified business use cases.
3. Plan
The learnings from the pilot phase are used to develop a full incremental rollout and adoption plan for the Data Mesh tailored to your organisation as a key deliverable from the accelerator.
4. Roll Out
Post the accelerator, we support the incremental rollout and wider organisational adoption of the mesh through strategic consultancy and/or hands-on implementation.
Case Study – Financial Services Customer
The Problem: A data-heavy global financial services company faced numerous data challenges due to rapid business growth, hindering efficiency and agility. Additionally, there was a recognised need to modernise the application portfolio to adapt to evolving business requirements.
The Solution: Establish a central, self-service data platform that could accommodate the organisational domain structure and devolve responsibility for data to specific domains. Improve observability and data lineage, as well as democratise access to data across the organisation.
The Outcome: The creation of an evolutionary, event-driven platform maximised team autonomy, fostering innovation and agility within the organisation.
