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Packaged snacks · LATAM and Middle East & South Africa retail

Revenue analytics across 12 retail chains, refreshed hourly

global snack food company

Replaced a nightly Excel-and-SSIS revenue pack with a Databricks lakehouse serving trade-spend-adjusted net revenue to 400+ commercial users across LATAM and Middle East & South Africa.

AzureDatabricksDelta LakeUnity CatalogdbtPower BI

The problem

Sell-out data arrived from twelve retailers in twelve formats across LATAM and Middle East & South Africa. Finance and sales argued over net revenue every month, and the close took nine days.

Our approach

  1. 1Landed retailer EPOS, distributor and SAP order feeds into ADLS Gen2 with Auto Loader and schema evolution.
  2. 2Built a medallion model in Delta Lake with a conformed product-and-customer hierarchy and Unity Catalog governance.
  3. 3Modelled gross-to-net: list price, trade promotions, rebates, returns and logistics deductions as auditable fact tables.
  4. 4Shipped a Power BI revenue cockpit with lineage back to source rows for finance sign-off.

Measurable outcomes

9 → 2 days
Commercial close cycle
98.6%
Gross-to-net reconciliation accuracy
$4.1M
Recovered promo leakage in year one

Architecture and workflow

Architecture and workflow
  1. 01

    Sources

    12 retailer EPOS · distributor · SAP

  2. 02

    Ingest

    Auto Loader · ADF · schema evolution

  3. 03

    Lakehouse

    Delta bronze / silver / gold

  4. 04

    Model

    dbt gross-to-net facts

  5. 05

    Consume

    Power BI revenue cockpit

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