02 / Data

Platforms, pipelines, analytics, and governance.

We make the numbers a business runs on clean, current, and trusted. The plumbing underneath, the analytics on top, and the governance that keeps it all honest.

Overview

What it is

Most companies do not have a data problem so much as a trust problem: numbers that disagree, reports that take days, and access nobody can fully account for. We build the platform, the pipelines, and the governance so the business runs on one trusted source, and so the data is ready for the practical AI that comes next.

Outcomes

  • One trusted source for the numbers, not five that disagree
  • Faster answers for the people who need them
  • Governance that satisfies an auditor without slowing the team
What is included

The sub-services in the Data practice.

01

Data platform and architecture

Warehouse or lakehouse foundations sized for how you actually work.

02

Pipelines and integration

Reliable, observable pipelines that keep data current across your systems.

03

Analytics and BI

Reporting and self-serve dashboards people trust and actually use.

04

Governance and quality

Ownership, lineage, and quality checks that satisfy an auditor without slowing the team.

05

Master and reference data

One agreed definition of the entities the business depends on.

06

AI-ready foundations

The clean, governed data that makes machine learning and generative AI reliable.

Our approach

How we deliver.

  1. 01

    Map the sources and the questions the business needs answered.

  2. 02

    Build the platform and pipelines for reliability and lineage from day one.

  3. 03

    Layer analytics and access on top, governed by clear ownership.

  4. 04

    Operate and improve, so the numbers stay current and trusted.

Platforms and tools

Fluent across your stack.

We pick the right tool for the job and stay fluent across the ones below. If your stack is not listed, we have almost certainly worked with something close.

The full ecosystem
SnowflakeDatabricksBigQuerydbtPostgreSQLApache KafkaApache AirflowFivetranLookerPower BI
Questions

About the Data practice.

Do we need a warehouse or a lakehouse?
It depends on your workloads. We will recommend the simplest thing that fits, and we are fluent in both.
Can you fix our existing pipelines instead of replacing them?
Often, yes. We prefer to stabilize and improve what works before rebuilding what does not.
How does governance avoid slowing us down?
We bake ownership and quality into the platform so it is automatic, rather than a committee you have to ask.
Lower cost, lower risk, one partner

Let us take Data off your plate.

One team, one bill, one point of accountability across cloud, data, AI, security, and software. Tell us where you are.