A large MNC supporting analytics across market research, retail, and business intelligence functions faced rising costs, slow analytics delivery, and limited scalability due to its dependence on legacy commercial analytics platforms. High licensing fees and rigid architectures constrained performance and restricted broader access to insights.
Blackstraw enabled the organization to retire its legacy analytics systems and modernize its data platform, delivering $15–16M+ in annual cost savings, accelerating analytics delivery and enabling enterprise-wide self-service analytics, all while completing the migration with zero downtime.
The organization used costly, rigid proprietary analytics platforms that struggled as data volumes and analysis needs grew. Performance issues and high licensing fees affected reliability and limited the ability to broaden analytics access across teams. The outdated setup also stifled innovation, delayed the use of advanced analytics, and limited access for business users. The organization needed a modern, flexible analytics system to cut costs, boost resilience, and support future growth without disrupting current operations.
Blackstraw worked with the organization to shift to a cloud-native, open analytics ecosystem designed for scalability and long-term efficiency.
Modern Lakehouse Architecture: Implemented a cloud-based lakehouse platform combining scalable storage with high-performance analytics to replace legacy systems.
Open, Flexible Technology Stack: Leveraged open-source and cloud-native technologies- including Spark, Databricks, Kubernetes, and MLOps – to reduce vendor lock-in and improve extensibility.
Seamless Platform Migration: Executed phased migration strategies that ensured zero downtime and uninterrupted access to critical analytics workloads.
Enterprise-Grade Analytics Enablement: Designed the platform to support governed, self-service analytics across both business and technical teams.
Significant Cost Reduction: Delivered $15–16M+ in annual savings by eliminating high-cost commercial licenses and infrastructure dependencies.
Faster Analytics Delivery: Improved analytics and reporting cycles by 40–50%, enabling quicker insights and decision-making.
Improved Operational Resilience: Reduced platform fragility through a scalable, fault-tolerant, cloud-native architecture.
Scalable Self-Service Analytics: Enabled enterprise-wide access to analytics capabilities, supporting broader adoption and innovation without increasing operational overhead.
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