Your data warehouse was cutting-edge when it was built. But that was a decade ago. Today, it's a bottleneck—slow queries, rigid schemas, and licensing costs that climb year after year while the business demands real-time insights.
We've modernized dozens of legacy data warehouses—from Teradata to Snowflake, from on-premises Netezza to cloud-native Databricks. The transformation isn't just about technology. It's about fundamentally changing how your organization uses data to make decisions.
The Legacy Data Warehouse Trap
We see it constantly: organizations trapped in a cycle where their data warehouse can't keep pace with business needs, but the migration seems too risky, too expensive, or too complex to attempt.
"By 2025, 80% of organizations will have migrated from traditional data warehouses to cloud data platforms. Those who don't risk being left behind as competitors gain real-time insights while they wait for overnight batch jobs to complete."
The symptoms are familiar: ETL jobs that run all night and still don't finish before morning stand-ups. Analysts waiting hours for queries to return. Business users who've given up on official reports and maintain their own Excel spreadsheets. Meanwhile, you're paying premium prices for proprietary hardware and maintenance contracts.
ETL Taking Too Long
Nightly batch jobs missing SLAs, leaving reports stale when decisions are needed
No Real-Time Capability
Unable to ingest streaming data or provide up-to-the-minute analytics
Rigid Schema Design
Adding new data sources takes months of modeling and development
Escalating Costs
Proprietary hardware and licensing eating budget with diminishing returns
Our Modernization Approach
Modernization isn't about ripping and replacing everything at once. It's about strategically migrating workloads while maintaining business continuity, and often improving service during the transition itself.
Current State Assessment
We catalog every data source, ETL job, report, and user. We identify what's actually used versus what's just accumulated over the years. Often, 80% of value comes from 20% of the workloads.
Target Platform Selection
Snowflake, Databricks, Azure Synapse, BigQuery—each has strengths. We match your specific requirements to the right platform: query patterns, data volumes, skill sets, and cloud strategy all factor in.
Data Model Redesign
Legacy warehouses were built for ETL. Modern platforms excel at ELT. We redesign data models to leverage cloud-native capabilities: separation of storage and compute, elastic scaling, and semi-structured data support.
Pipeline Modernization
We rebuild ETL using modern tools like dbt for transformations, Fivetran for ingestion, and native cloud services. Jobs that took hours now complete in minutes. Real-time streaming becomes possible.
Phased Migration & Validation
Workloads migrate incrementally. Each phase is validated against the legacy system before cutover. Business users see improvements immediately, not just at the end of a multi-year project.
Case Study: From 8-Hour ETL to Real-Time Retail
The Situation
A national retailer with 1,200 stores was running a 15-year-old Teradata warehouse costing $800K annually in licensing and maintenance. Their nightly ETL took 8 hours, which meant morning inventory decisions were based on yesterday's data. During peak holiday season, the system couldn't keep up at all.
"We were flying blind during our busiest season," the VP of Analytics told us. "We'd run out of popular items in some stores while they sat unsold in others, and we wouldn't know until the next day's reports."
Our Approach
We designed a migration to Snowflake with a complete pipeline modernization:
- Platform Migration: Migrated to Snowflake with multi-cluster compute for elastic scaling during peak query periods
- Pipeline Rebuild: Replaced 200+ legacy ETL jobs with dbt models and Fivetran connectors, reducing maintenance overhead by 70%
- Real-Time CDC: Implemented change data capture from transactional systems, enabling near-real-time inventory visibility
- Self-Service BI: Connected Power BI with semantic models that let analysts build their own reports without IT involvement
The Results
"Last holiday season was our best ever. Real-time inventory visibility meant we could rebalance stock between stores on the fly. We prevented stockouts that would have cost us millions. The modernization paid for itself in the first quarter."— VP of Analytics, National Retailer
What You Can Expect
Data warehouse modernization is transformative when done right. Here's what our approach delivers:
10-100x Faster Queries
Complex analytics that took hours now complete in minutes. Users get answers when they need them, not when the system finally responds.
Real-Time Data
Move from overnight batch to streaming ingestion. Make decisions based on what's happening now, not what happened yesterday.
Elastic Scaling
Scale compute resources automatically during peak demand. No more month-end report slowdowns or holiday season capacity crunches.
50-70% Cost Reduction
Replace expensive proprietary licensing with pay-per-use cloud pricing. Your costs align with actual usage, not peak capacity.
Self-Service Analytics
Enable business users to explore data and build reports without waiting for IT. Governed access with freedom to analyze.
Future-Ready Platform
Modern platforms support AI/ML, advanced analytics, and data sharing. You're positioned for whatever comes next.