Manufacturing & consumer goods

Manufacturing

Sales, operations and marketing data turned into reporting finance trusts and tables models can use.

← All industries

Revenue explained.
Data ready for models.

Client work first, then applications we build for teams like yours.

01
From a client engagement

Price-volume-mix analytics

The challenge

Finance cannot say whether revenue moved on price, volume or product mix, and the analysis takes a quarter to produce.

What we build

A medallion lakehouse on AWS with change data capture, preserved history and PVM logic, served to Power BI through Snowflake.

Engineering considerations
  • Keeping history accurate as records change
  • Complex PVM business logic
  • Scale to a terabyte a day
Project outcome
Revenue reporting in days, not months.
Reporting in days.The reporting cycle moved from months to days.
Fewer data-quality issues.Change data capture and preserved history catch problems before reports do.
Built for volume.The lakehouse takes large daily sales volumes in its stride.
Manufacturing · individual engagementView case study
02
From a client engagement

Marketing data hub

The challenge

For a global consumer goods company, marketing data arrived from many sources and outside agencies, and model-ready data took weeks after each quarter closed.

What we build

Our core engineering team designed and built a Marketing Data Integration Hub on Databricks on Google Cloud: governed agency uploads, historical tracking and hard-stop quality gates feeding model-ready tables.

  • Model-ready data right after quarter close
  • No more waiting weeks for data
  • Every source in one governed hub
Engineering considerations
  • Governing uploads from outside agencies
  • Keeping history as sources change
  • Stopping bad data before models see it
Delivery by design

Every source. Model-ready tables.

Built for a global consumer goods company

  1. 01IngestPlatform data and agency uploads
  2. 02CheckHard-stop quality gates
  3. 03TrackHistory preserved
  4. 04DeliverModel-ready tables
Model-ready data right after quarter close.

Your next step

Tell us what has
to run, and where.

Your users, workloads and constraints are where the design starts.