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Data Integration Services

One source of truth, across all your systems

When your data lives in silos, every report is a manual stitch-together and no number is fully trusted. We build the pipelines that consolidate and sync your data so your business runs on one consistent picture.

Sound familiar?

Your data is scattered across tools that don't agree with each other.

Reporting means exporting from three systems and reconciling by hand.

No single, trustworthy source of truth — so decisions run on stale or conflicting numbers.

Analytics is an afterthought because the data was never wired together.

How we fix it

1

Data pipelines & ETL

Reliable pipelines that extract, transform, and load your data on a schedule or in real time — with monitoring so you trust what's flowing.

2

Consolidation & warehousing

We bring your data into one consistent model, so operations, reporting, and analytics all draw from the same source.

3

Kept in sync, owned end to end

Ongoing sync across your tools, with someone owning the outcome — not a brittle export nobody maintains.

Single source

of truth built from siloed enterprise systems

Proven in production

Datamart Integration

Consolidating scattered enterprise data into one reliable datamart — the single source of truth reporting and decisions run on.

Read the case study

What is data integration?

Data integration is the process of combining data from your different systems — CRM, accounting, operations, product — into one consistent, trustworthy view. It replaces the manual exports and reconciliations that eat your team's time, and it's the foundation every reliable report and dashboard is built on.

ETL, ELT, and data virtualization — which fits

There's no single right way to integrate data; the right approach depends on your data volume, your systems, and how fresh the data needs to be.

  • ETL (Extract, Transform, Load) — transform data before it lands. Best for structured data and strict consistency.
  • ELT (Extract, Load, Transform) — load first, transform in a cloud warehouse. Best for large volumes and modern data stacks.
  • Data virtualization — a unified, real-time view across sources without physically moving the data. Best when you need instant access and agility.
Image: ETL vs ELT vs data virtualization compared (team to replace)

The data integration process

A reliable pipeline follows the same shape every time: extract from each source, transform and cleanse into a consistent model, then load it into the destination your reporting and operations run on — with monitoring so you know it's working.

  • Extract — pull data from every relevant source, nothing left behind.
  • Transform — cleanse, standardize, and structure it into one model.
  • Load — deliver it to the warehouse, app, or dashboard that needs it.

The challenges we handle for you

Most integration projects stall on the same things — mismatched formats, brittle point-to-point scripts nobody owns, and security and governance concerns. We standardize formats, build resilient integrations with monitoring, and apply the ISO 27001 discipline we use on sensitive enterprise systems — so your data stays accurate, secure, and owned.

Image: Data integration governance and security (team to replace)

Frequently asked questions

What's the difference between ETL and ELT?

ETL transforms data before loading it into the destination; ELT loads raw data first and transforms it inside a cloud warehouse. ELT suits large volumes and modern cloud stacks; ETL suits structured data and strict pre-load consistency. We pick the right one for your systems and volume.

How do you avoid brittle, one-off integration scripts?

We build resilient, monitored integrations with clear ownership — event-driven where it helps — instead of point-to-point scripts that break when a system changes. Alerting tells you before something silently fails.

Is our data secure during integration?

Yes. We apply the ISO/IEC 27001:2022 discipline we've used on sensitive enterprise systems for 7+ years — encryption, access control, and governance built into the pipeline, not bolted on.

Can you connect legacy systems and modern SaaS together?

Yes — CRMs, ERPs, data warehouses, legacy databases and SaaS APIs into one consistent flow, so operations and reporting draw from a single source of truth.

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