Tech Series: Data Mesh Experimentation to Industrialisation
Explore the key driving principles for the Data Mesh from MVP, to productionisation to industrialisation.
Discover what happened when a large financial service organisation who were already underway with a DevOps and Agile transformation went from a Monolithic Data Lake architecture, onto a federated self-service Data Mesh on Google Cloud Platform (GCP).
In this session, we explore the key driving principles for the Data Mesh from MVP, to productionisation to industrialisation.
Who will benefit
Anyone who wants to understand how Data Mesh can help businesses achieve their organisational objectives.
What you’ll learn
-What is Data Mesh.
-The key driving principles.
-How the hyper-new concept delivers business value.
-How Data Mesh works across different programmes.
About this event
The key driver from the transformation was to reduce Lead times and improve the Flow Efficiency for Business Change. The typical approaches to transformation demonstrated substantial efficiencies across the core operational platforms but no material impact was seen on the downstream Data Publishing and Data Analytics platforms. These were faced with more fundamental blockers around lack of autonomy, monolithic architecture and proxy ownership of the data, compounded by legacy tech estate of on-prem data warehouses, data marts, data lakes, etc. End to end solutions required coordination between specialised teams working in silos leading to extended lead times.
This required a paradigm shift on both the systems architecture and Ways of Working.
In this session, we’ll explore the key driving principles for the Data Mesh from MVP, to productionisation to industrialisation.
The Data Mesh was built to be an Open Self Service platform whereby the various tenants can contribute to the features themselves alongside using the Core Platform self-service features. The success of the Data Mesh led to buy-in across the business and the Data Mesh Adoption accelerated exponentially. During the talk, we’ll highlight some of the key outcomes and business value delivered through the Data Mesh including:
Rapid business values delivered to many ongoing programmes building ML models, MI Dashboards, cross-domain analytics, Data Provider APIs, Enquire and Reporting apps, etc.
Teams were able to react to fast changing business and client demand with lead times dropping from months to days.
New business models identified
The Data Mesh brought parity across the varying levels of technology maturity and skills within the organisation
The Data Mesh is now a de facto part of the downstream data publishing, reporting and analytics for the organisation.
Data Mesh Platform Owner
Sunny Jaisinghani Read more...
Thought Leader within the Data technologies space with an acute focus on Customer Success. Proven Track record of delivering customer outcomes across a variety of roles within the Data domain and most recently in the Data Mesh space through a high fidelity open self-service platform.
Data Mesh Technologist
Simon Massey Read more...
A creative technologist with two decades of hands-on delivery, technical leadership and architecture experience within financial services and government. Simon has led geographically dispersed technical teams to deliver distributed systems using self-service DevOps, agile methodologies, and continuous delivery.