Data Engineering
Analytics that don't run on a warehouse are slow analytics. Models that don't run on clean data are wrong models. Activation that doesn't run on governed data is risky activation.
We build the data infrastructure — warehouse, pipelines, transformation, quality, activation — that every other analytics initiative downstream silently depends on.
What we do
Does this sound familiar?
You're working off stale data
You have to wait for manual exports from your tools or for key staff members to update numbers in a spreadsheet. By the time it's ready, you're already a week behind and you still have to manually adjust things from there.
You are trying to do more with your data but the overhead of manually updating data is stopping business growth.
Diagnosis:You're technology is holding back your data
Data is stuck in platforms and spreadsheets
You're stuck with manual exports and uploads or a home-brewed script that tries to save you time, but ends up needing hours of maintenance to support.
You have to manually clean up the exports and align them just so you can put together a report, and if you miss a step? Starting over from scratch.
Diagnosis:Manual steps and work arounds cost more in the long run
Different reports, different results
Marketing's CPA doesn't match finance's, revenue figures diverge in key reports, executive's just want to know where to look for the right number.
You've tried auditing the data, but teams stick to what they know, and point the finger when the answers don't add up.
Diagnosis:Data Modelling is siloed instead of unified
Dashboards stop refreshing, users lose trust
A team introduces a new feature and break your reporting schema, you're left without a working report, while trying to chase down what changed.
You don't find out until it's too late leading to decisions being made on incorrect data, and slowing down your growth.
Diagnosis:Lack of observability leads to vulnerable setups
Your warehouse is a data graveyard
Data lands in the warehouse, gets visualised in a dashboard, and dies there. Sales still works off CRM exports and Marketing relies on in-platform measurement.
You've tried to get everyone using the same reports, but they have to go back to their own tools to action it, so they stop using them.
Diagnosis:Activate your data in the tools that need it
How we engineer data successfully
Transforming not just piping data
Modelling
Dimensional models, semantic layers and rich documentation help every consumer of the data to adopt the same source of truth. The end of 'which dashboard is right?'
Observable
Data tests, schema monitoring, freshness checks and anomaly alerting. Any issues are caught early, and end users never know or are alerted before they read stale data.
Activated
The warehouse syncs back to the operational tools your teams use, actively driving return on your investment in the data that underpins your business.
Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.
Frequently asked questions
Data engineering, demystified
BigQuery, Snowflake, DataBricks, AWS all these systems have pros and cons. We prioritise understanding your stack, team skills, and workloads when deciding which tool is the right one for you.
We approach data modelling from a business perspective, understanding what you need to know to measure success, and using that lens to build the right model for your use case.
This depends a lot on your current setup and the systems that you are using. We can provide an estimate after an initial discovery phase, and create a roadmap that works with your timelines and level of maturity.
We build into infrastructure that is secure and private by design, implementing any compliance requirements and data retention policies along the way. We can also implement data residency where required.
We typically hand over operations to your teams with full documentation and training. However if you requiring ongoing support we can discuss managed service options, but you always own your data and systems.
Ready to start with data engineering?
Tell us where you are today and what you're trying to fix. We'll show you exactly how we'd plan, execute, and measure.
- No commitment required
- Speak to a senior consultant
- Get a rough scope and timeline
