Enterprise-scale data warehousing

The organization was grappling with complex, manual data pipelines that were difficult to scale and costly to maintain. They wanted to eliminate bottlenecks and ensure consistent data quality to drive quick and effective decision-making. They required a modern solution that onboarded new datasets with minimal development effort, while meeting the compliance and governance measures.

Nagarro helped the client modernize their enterprise data platform using the Databricks Lakehouse. We leveraged a flexible PySpark-based framework to automate data ingestion and validation across domains. Delta Live Tables made it easy to load data into Delta Lake with built-in quality checks and smart, self-fixing data pipelines. Intuitive dashboards allowed all users to review data, while Unity Catalog ensured governance, security, and lineage. The Medallion architecture organized data into raw, cleansed, and business-ready layers. Serverless compute reduced infrastructure costs, making the solution scalable, governed, and cost-efficient. 

This implementation automated ingestion, validation, and curation at scale - resulting in faster, cleaner, and more reliable data. Databricks Workflows reduced pipeline runtimes by 60%, significantly accelerating insights delivery. With a configuration-driven approach, the client eliminated the need for custom development when onboarding new datasets, enabling rapid, zero-code scalability, and 10x faster onboarding. Users can now access data on their own, giving them more independence. The platform offers high quality data with complete tracking of data changes and clear visibility into the source. It also reduced computing costs by 30%.