Reported impact
Business outcome
DXC replaced fragmented reporting with a single trusted cloud data platform, improved access to near-real-time insights, reduced the confusion caused by thousands of inconsistent dashboards, and put production AI capabilities into daily use through natural-language analytics, staffing optimization, and document analysis.
- Cost Reduction
- Productivity Improvement
- Scalability
- Speed to Market
Solution
DXC rebuilt its internal data foundation on a cloud-hosted lakehouse powered by AWS and the Databricks Data Intelligence Platform. The program migrated data from systems including Azure Synapse and SQL Server into one secure environment, where Spark modernized ingestion and preparation and Qlik Sense handled visualization. DXC also changed the operating model around the platform, adopting DataOps, automated CI/CD, unified batch and streaming workloads, FinDevOps visibility, and secure sharing through Delta Sharing. Once the data was centralized and governed, DXC put AI to work on top of it: Databricks Genie let employees query data in natural language, and production AI agents began supporting staffing optimization and unstructured document analysis across HR, finance, and delivery workflows. The result is a single trusted data platform that supports both near-real-time analytics and enterprise AI use cases at scale.
Data flow
Data from Azure Synapse, SQL Server, and other repositories is ingested with Spark into an AWS-hosted Databricks lakehouse, where it is standardized, governed, and prepared for analytics. Qlik Sense serves dashboards on the unified data, Delta Sharing exposes secure shared datasets, and Databricks Genie plus production AI agents consume the governed information for natural-language analysis, staffing optimization, and unstructured document workflows.