Case Studies | SaaS B2B

From spreadsheets to a single source of truth

Automated Data Pipeline and BI

About

A SaaS B2B business working with Cloud Combinator on AWS. The client is anonymised at their request.

Challenge

The challenge had four focus areas.

Unifying three disconnected systems

Recruitment, HR and finance data sat in Bullhorn, HiBob and Xero, each with its own API, authentication model and quirks. The pipeline had to pull reliably from all three and bring them into one place.

Removing manual, error-prone reporting

Hand-built spreadsheets meant stale figures and transformation mistakes. Ingestion, cleaning and the business-rule transformations, such as calculating Net Fee Income, all needed to be automated and repeatable.

Delivering timely, self-service insight

Leaders needed near real-time visibility with the ability to drill down themselves, rather than waiting for a weekly report, which called for a hourly refresh and interactive dashboards.

Making it trustworthy and maintainable

A pipeline is only useful if it is dependable. The solution needed monitoring, alerting and data-quality checks, plus documentation and training so the client's own team could run it.

Solution

Cloud Combinator worked in two-week sprints, delivering core ingestion and a minimum viable dashboard first, then layering on transformation, visualisation, monitoring and handover.

Hourly

Automated data refresh across all sources

3 systems

Bullhorn, HiBob and Xero unified

99%

Target dashboard availability

By the numbers:

  • Hourly - Automated data refresh across all sources
  • 3 systems - Bullhorn, HiBob and Xero unified
  • 99% - Target dashboard availability
Changes

The engagement delivered an automated, serverless reporting platform, replacing manual scorecards with a single source of truth and self-service dashboards, built to clear, measurable acceptance targets.

  • One source of truth — Recruitment, HR and finance data now flow automatically into a central data lake, ending the manual export-and-pivot routine.
  • Near real-time visibility — A hourly refresh replaces weekly reporting, with a target of 95% of records reflected in dashboards within a hour of change.
  • Self-service dashboards — QuickSight gives business users interactive drill-down and natural-language Q&An across their core metrics, including Net Fee Income.
  • Operational resilience — CloudWatch alarms and SNS alerts, plus automated data-quality checks, surface failures and anomalies quickly so the numbers stay trustworthy.
  • Handover — Runbooks, deployment guides and a live workshop left the client's IT team able to operate, extend and add new data sources to the pipeline.

With a dependable, automated reporting foundation in place, the client are positioned to onboard further data sources with minimal effort and, in a future phase, to layer predictive analytics with Amazon SageMaker onto the same platform.

AWS Stack

AWS Lambda

For serverless ingestion and transformation functions.

Amazon EventBridge

For scheduling the hourly data pulls.

Amazon S3

For the raw landing zone and transformed data lake.

AWS Glue

For cataloguing and schema inference across the data.

Amazon Athena

For SQL queries over data in S3 and serving QuickSight.

Amazon QuickSight

For interactive dashboards, drill-down and natural-language Q&A.

Amazon CloudWatch

And Amazon SNS for monitoring, alarms and email alerts.

AWS IAM

And AWS Secrets Manager for least-privilege access and secure credential management.

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