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2 Data Foundation

ETL & Integration

Your data lives in a dozen systems. We build the pipelines that bring it together, transform it, and deliver it where finance needs it - reliably, every time.

The integration headaches finance teams live with

The Monday morning data wait

You arrive at 8am to find last night's data load failed. Now you're debugging ETL jobs instead of closing the books. It happens every month.

Spreadsheet integrations

Data from System A goes into Excel. Someone adds columns. Then it's copy-pasted into System B. This is your "integration layer".

Silent failures

The overnight job ran fine. But it only loaded 80% of records because the source format changed. Nobody noticed for three days.

IT bottleneck

Need a new data feed? Join the queue. IT has a six-week backlog. By the time they build it, the requirement has changed twice.

One person knows

Dave built the integrations five years ago. Dave doesn't work here anymore. The documentation is a folder of scripts nobody understands.

Reconciliation hell

The numbers in your planning tool don't match the ERP. The ERP doesn't match the data warehouse. You spend hours finding why.

Integration that finance can rely on

We build data pipelines designed for finance workloads. Reliable, auditable, and maintainable. When the data arrives, you can trust it.

1

Map your data flows

We document every source, every transformation, every destination. You'll finally see how data actually moves through your organisation.

2

Design the architecture

Right-sized integration approach. Sometimes that's enterprise ETL. Sometimes it's simple scheduled queries. We match the solution to the problem.

3

Build with monitoring

Every pipeline has error handling, logging, and alerts. When something fails, you know immediately. When records are missing, you get notified.

4

Validate at every step

Row counts, checksums, business rules. We build validation into the pipeline so bad data is caught before it reaches your reports.

5

Document everything

Data dictionaries, pipeline documentation, runbooks for common issues. Knowledge doesn't live in someone's head anymore.

6

Enable self-service

Train your team to handle routine changes. Give finance the ability to add fields, adjust mappings, and extend pipelines without IT.

Tools we work with

We're tool-agnostic. The right platform depends on your existing stack, data volumes, and team capabilities.

Alteryx

Visual data prep for business users. Complex transformations without code. Our go-to for self-service analytics.

IBM DataStage / InfoSphere

Enterprise-grade ETL for complex, high-volume data integration. Proven in demanding environments.

MuleSoft

API-led connectivity for complex system landscapes. Real-time integration with proper governance.

Azure Data Factory

Microsoft's cloud ETL service. Great for Azure-heavy environments and complex orchestration.

Power Query / Power BI Dataflows

Self-service data prep that finance teams can manage. Ideal for smaller-scale transformations.

Custom Python / APIs

When off-the-shelf tools don't fit. REST API integrations, custom logic, specialist sources.

How integration projects work

Why us for ETL & Integration

Finance-First Data Engineering

We're not generic data engineers - we understand finance workloads, month-end pressures, and what reliable data actually means for FP&A teams.

20+
Years integration experience
50+
Integration projects delivered
Certified
Alteryx, MuleSoft, Azure
View all case studies

Frequently asked

How is this different from what IT builds?
IT builds for IT requirements. We build for finance requirements. That means understanding month-end timelines, reconciliation needs, and the specific data quality checks that matter for financial reporting.
Do we need to buy new tools?
Usually not. Most organisations already have ETL capabilities in their existing stack. We often use Azure Data Factory (included with Azure), Power Query, IBM DataStage, or tools you already have licensed like Alteryx.
What about real-time data?
For most finance use cases, near-real-time (refreshed hourly or more frequently) is sufficient. True real-time streaming adds complexity and cost. We'll advise honestly on what you actually need.
How do you handle source system changes?
We build pipelines that detect schema changes and alert before breaking. Validation rules catch data format changes. And we document dependencies so updates are straightforward.
Can our team maintain this?
That's the goal. We build with maintainability in mind, document thoroughly, and train your team. Routine changes should be handleable in-house. We're on hand for complex additions.

Ready to fix your data flows?

Start with an integration audit. We'll map what you have, identify the weak points, and show you what reliable pipelines look like.