Situation
A global banking behemoth faced high regulatory penalties and an erosion of trust in its data storage and processing mechanism. To rebuild credibility and agility, they needed a robust data strategy that could transform fragmented pipelines into a cohesive, efficient system.
Challenge
Their journey was hampered by systemic hurdles:
- Delayed innovation cycles due to cumbersome data access and lack of clarity
- Data trust issues caused by inconsistencies across decentralized pipelines
- Absence of self-service, leaving teams reliant on others to unlock data’s potential.
The bank’s data challenges stalled progress and stifled the ability to innovate rapidly.
Approach
Mu Sigma introduced a tailored Data Mesh framework, prioritizing resilience and scalability. Key interventions included:
- Creating a unified ‘data highway’ for faster prototyping and experimentation.
- Addressing diverse needs of five distinct user groups with adaptive solutions.
- Shifting from speed-first to trust-first design for long-term flexibility and broader usability.
The new architecture empowered teams to access and utilize data independently, unlocking agility without compromising governance.
Impact
- 80% reduction in data discovery time, enabling faster decision-making.
- 30 products unified, reducing complexity and fostering cohesion.
- Restored trust in data, reinforcing the bank’s resilience and adaptability.
Business Impact
-
80%
reduction in data discovery time
-
30+
products unified, reducing complexity
Let’s move from data to decisions together. Talk to us.
The firm's name is derived from the statistical terms "Mu" and "Sigma," which symbolize a
probability distribution's mean and standard deviation, respectively.
