Implementing data mesh architecture to create a data-driven enterprise

Enabling self-service analytics, improving data scalability, and optimizing operational efficiency

the story

Our client is a very successful luxury property development company in the Middle East. They were looking to revamp their existing data strategy and move to a modern cloud-based enterprise data platform.

Nagarro developed a platform that acted as a strategic enabler for the client’s growth by enabling analysts, data scientists, and other business users to leverage data as products for actionable insights. The architectural framework and pattern, developed by Nagarro, became a backbone for the enterprise data platform that helped the client standardize and accelerate their development on the cloud.

challenge

In a time of necessary agility and quick adaptability, the existing monolithic architectural pattern was slow to respond to changes and requests by the data consumers. The client sought an enterprise data platform that delivers high-quality data across different departments through a reliable, scalable, and optimized framework. It also wanted to enable self-service analytics and create a data-driven enterprise.

solution

Nagarro’s data engineering team implemented data mesh architecture on the Azure platform. The team created sales, marketing, and inventory domain data products using infrastructure-as-code, leveraging data mesh principles managed by decentralized domain teams. A common data ingestion framework enabled extracting data from different sources and storing it in various data repositories such as data lakes and warehouses. The implementation made the data products self-serviceable to users. And a governance model was employed to govern and control all data assets. The team also trained users to adapt to the change toward a data-driven culture and improved data consumption.

outcome

Self-serviceable data products made stakeholders self-reliant and encouraged adopting a data-driven culture. It enabled faster scaling of data products and accessibility, leading to data adaptability and discovery within the organization. With self-serve infrastructure, continuous integrations, deployments, and monitoring, the time to market for business units decreased considerably.
Data ingestion and data sharing have become more scalable and consistent. Our solution helped the client observe significant cost savings, decreased data processing time, sharing of data products across the organization, and a 2x increase in operational efficiency.

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Implementing data mesh architecture to create a data-driven enterprise

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