Modernizing Business Intelligence for a High-Volume Logistics Operation
- shipments/year
- 100,000+
- carriers
- 25,000
- faster queries
- 5x
- faster Tableau reports
- 10x
Challenges
The client relied on an on-premises data warehouse for reporting, pricing, and route-optimization decisions for core logistics operations.
Growing data volume and complexity limited scalability, query performance, and reporting velocity for decision makers.
Multiple 3rd party platforms required standardized collection, normalization, and integration before downstream reporting could be trusted.
Technologies
- Google BigQuery
- Microsoft SQL Server
- Microsoft SQL Server Integration Services
- Tableau
- extract-transform-load pipelines
- comma-separated-value sources
- data partitioning
- query indexes
Solution
Deployed a Google BigQuery warehouse for centralized analytics and aggregated operational reporting across the business.
Integrated third-party platforms, Microsoft SQL Server databases, and comma-separated-value data sources into standardized pipelines.
Developed extract, transform, and load scripts, middleware, and Microsoft SQL Server Integration Services packages to normalize legacy data.
Reconfigured Tableau reporting and applied partitioning, indexing, and query optimization to improve retrieval performance for operational users.
Outcomes delivered
Centralized data from multiple logistics platforms for reporting.
Improved data access and reporting accuracy across operations.
Established a scalable cloud-analytics foundation for business growth.
Reduced reliance on on-premises warehouse infrastructure for reporting.