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Case study: a 5.5-hour job, now under four minutes

A finance team was moving data by hand between two systems that wouldn't talk. We built the bridge.

3 min read7 November 20262 sources

The short version

  • Finance data reached reporting only through manual Excel exports.
  • We built a custom connector into a central data platform.
  • The nightly refresh fell from about 5.5 hours to under four minutes.

The client asked not to be named. The details are real.

The sales team worked in Salesforce. Finance worked in NetSuite. Apart from a basic customer sync, the two never spoke, so the finance team did the talking.

Orders were downloaded, reformatted in Excel and uploaded again. Weekly reports were stitched together by hand. Sales and finance ran their own numbers, and got different answers.

The bridge

The fix was a data warehouse, which Google describes as a way of "consolidating siloed data" and "enabling business reporting".[1] The standard connector needed a licence the client didn't have, so we built a custom one.

It reads the finance system securely, keeps bank details out entirely, and only picks up what's changed each night instead of copying everything again.

89xfaster nightly refresh
5.5 hrs → 4 minper refresh

Because reporting now runs on the central platform, it no longer slows the systems people use all day, a benefit AWS highlights for this kind of setup.[2] And the team's biggest question, "has this invoice been paid?", can finally be answered from one place.

Sources

  1. Google Cloud: What is a data warehouse?
  2. Amazon Web Services: What is a data warehouse?

Sources checked 7 November 2026. Product features and prices change often, so check the vendor's site before you buy.