Situation
Our client is a Fortune 50 logistics and transportation company that wanted to enhance business visibility and actionability to ensure business continuity and improve cost and margin decisions. The organization relied on over a million legacy SAS workloads, which were costly to maintain, spending tens of millions of dollars annually on licensing and operations.
The SAS to Databricks migration will reduce workload by 10x and provide huge savings over 3 years.
Additionally, the legacy systems didn’t have the agility to support modern requirements such as real-time data access, AI-driven intelligence, advanced analytics and reporting.
Action
We led a comprehensive modernization of our client’s data, AI, and analytics platforms by leveraging Databricks. This transformation incorporated Gen AI-based code migration and transformation accelerators, enabling faster and smarter migration from legacy systems.
We automated the migration of hundreds of on-prem Oracle data warehouse tables to Azure Synapse, and complex Ab Initio Extract, Transfer, Load (ETL) graphs to ELT-based PySpark notebooks with Gen AI based automation accelerations.
In addition, we implemented an Azure Data Factory based ingestion pipeline and Databricks ETL frameworks for both historical and real-time change data capture. To improve visibility and actionability for business users, we converted thousands of SAP BusinessObjects (BO) intelligence and transferred to Microsoft Power BI.
Results
- 10x reduction in workload through platform consolidation and optimization
- Tens of millions in cost savings over 3 years
- Real-time intelligence enablement for business users to meet operational and financial goals
- Future-ready architecture for scalable, AI-powered decision-making
Operational and financial goals are now achieved using real-time intelligence.
Platform consolidation and optimization led to a 10x reduction in workload.
Gen AI-based code migration and accelerators enabled a faster data migration.
Operational and financial goals are now achieved using real-time intelligence.
Platform consolidation and optimization led to a 10x reduction in workload.
Gen AI-based code migration and accelerators enabled a faster data migration.
Operational and financial goals are now achieved using real-time intelligence.
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1M+
Workloads from SAS to Databricks -
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3x
Usage cost reduction -
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40%
Acceleration with 5+ Gen AI accelerators