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Data Engineering
Retail
38% lower data spend

Modern analytics for 40,000 stores

How Northwind traded 11-hour ETL for a real-time lakehouse — and cut platform spend by nearly 40%.

Client
Northwind Retail Group
Industry
Retail
Timeline
9 months to production
Business impact

Results at a glance

0x
Faster reporting
0%
Lower TCO
0k+
Stores served
0
Reports migrated
Situation

Where they started

  • Nightly ETL took 11 hours and regularly missed SLAs.
  • Six regional warehouses reported divergent numbers.
  • Platform spend growing 34% year-over-year.
Approach

How we did the work

  1. 1

    Target architecture

    Databricks medallion, dbt transforms, unified semantic layer.

  2. 2

    Metric alignment

    Aligned finance, merchandising and supply chain on one metric set.

  3. 3

    Migration

    Phased cutover of 220 reports with dual-run validation.

  4. 4

    FinOps

    Introduced query governance and warehouse right-sizing.

Results

What changed

Dashboards load in under 800ms for 40k store managers.

Platform spend down 38% in year one.

Every function trusts the same numbers.

Technology

Tools of the trade

Databricks
dbt
Airflow
AWS S3
Snowflake
Looker
Terraform

"Dataamps replaced a decade of legacy plumbing with something our teams actually love using. The ROI showed up in the first quarter."

Priya MenonVP Data & Analytics, Northwind Retail Group
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