RetailMax's Data Platform Modernization: From Chaos to Clarity
The Challenge
RetailMax, a mid-market e-commerce company with $200M in annual revenue, had 5+ years of data scattered across a legacy data warehouse, multiple MySQL databases, a Salesforce instance, and Google Sheets. Their analytics team spent 70% of their time on data cleaning and pipeline maintenance rather than business insights.
- 4TB of data across 7 disconnected systems
- Analytics team spending 70% of time on data wrangling
- No internal data engineering capability
- Inventory decisions being made on T+2 data (2-day lag)
- 6 different BI tools in use with inconsistent numbers
Our Approach
Tallend led a full implementation engagement: 2-week discovery, 2-week architecture design, 8-week build, and 2-week cutover. We built a modern Snowflake + dbt + Airflow stack with a single source of truth across all data domains.
- 12-week discovery: data audit, stakeholder interviews, requirements
- 2Architecture design: Snowflake + dbt + Airflow recommendation approved
- 3Data model design covering inventory, orders, customers, marketing
- 4ETL pipeline build with incremental loading strategies
- 5Historical data migration (4TB) with full validation
- 6Real-time inventory dashboard (from T+2 to T+15 minutes)
- 7Analyst training and documentation
The Results
The new data platform consolidated all data sources into a single governed Snowflake environment. Analytics team time-on-insights jumped from 30% to 85%. RetailMax retired 4 legacy data systems, saving $1.2M annually. Inventory decisions now run on near-real-time data.
$1.2M
Annual infrastructure savings
85%
Analyst time on insights (was 30%)
T+15m
Inventory data latency (was T+2d)
4
Legacy systems retired
“We'd been burned by offshore vendors before on data projects. Tallend was different — fixed deliverables, transparent weekly reports, and the data quality coming out of the new pipeline is night and day from what we had.”