01
Data warehouses
Structured, modelled data for reporting and analysis: facts and dimensions designed around the questions the business asks, fast to query and consistent over time.
05Data & integration · Data platforms
Enterprise data platform development.
A data platform is the place where data from every system in a company is collected, cleaned and kept ready for reporting, analysis and AI.
We build it to order, around the way you work, or extend and connect the one you already have.
01What it is
In plain words.
A data platform is the place where data from every system in a company is collected, cleaned and kept ready for reporting, analysis and AI.
Each business system is built to run its own process, not to be asked questions across the company. Query them directly and you slow them down and get five formats of the same fact.
A data platform copies the data out, brings it into one consistent shape and keeps its history. Everything that depends on data, from a monthly report to an AI assistant, then has one dependable source. Without it, each new project builds its own fragile copy.
02What it includes
Every part, explained.
8 parts. Each can be built by itself; together they are one system.
02
Data lakes
Raw data of every kind kept cheaply in its original form: files, logs, documents, sensor readings, images. The store you keep because tomorrow's question is not yet known.
03
Data lakehouses
One platform that keeps the low cost and openness of a lake and adds the structure, reliability and query speed of a warehouse, on open table formats so you are not tied to one vendor.
04
ETL and ELT pipelines
The jobs that extract data from each source, load it and transform it, in batches or as a stream, with tests, monitoring and alerts so a failed load is known before the report is opened.
05
Data engineering
The craft underneath: modelling, orchestration, versioning, performance and cost control, and documentation that lets the next engineer understand what was built.
06
Master data management
One agreed record for each customer, supplier, product, material and employee across all systems, with duplicates matched and merged, and rules for who may change what.
07
Data governance
Ownership, definitions, quality rules, lineage, access control, retention and privacy: who is responsible for each dataset, where it came from and who may see it.
08
Enterprise search
One search across systems, shared drives and documents, which understands meaning as well as keywords and returns only what the person asking is allowed to see.
Buy, extend or build?
Use an established engine for storage and compute; nobody should write their own database. What is built to order is the design on top: the model, the pipelines, the master data rules and the governance that fit your systems. Choose warehouse, lake or lakehouse by the data you have and the questions you ask, not by fashion.
Where intelligence fits
Master data is where we are strongest. Finding that two records with different names are the same supplier, material or customer is the work our flagship product does on industrial data, with rules first, meaning next and reasoning last, and a confidence on every match. A data platform is also the precondition for any AI that is supposed to know your business.
03What it works with
Never on an island.
A system is worth most when it shares its records with the ones beside it.
- Business intelligenceBusiness intelligence turns what a company's systems record into charts and figures its people can read and act on.
- Data analytics and decision systemsAnalytics explains what happened and estimates what will; a decision system puts that estimate in front of the person deciding, at the moment they decide.
- Integration platform as a serviceAn integration platform is the switchboard between a company's systems: it carries data from each one to the others that need it.
- Enterprise AI and intelligenceEnterprise AI is software that reads, searches, reasons and acts on a company's own data and documents, inside the company's own walls.
- Enterprise resource planningAn ERP is the one system that records what a company owns, owes, buys, makes and sells, so every department works from the same numbers.
Part of a family
Data, integration and automation: Systems that talk to each other, work that moves by itself, and numbers you can trust.
04How we build it
Five steps, in the open.
- 01
Listen
You describe the work and where it hurts. We look at the systems and the data you have now.
- 02
Specify
A written specification: what the system does, what it does not, what it connects to and how we will know it works. A clear quote before any work starts.
- 03
Build in stages
A working piece at each stage, on real data, so you steer early. The part that matters most comes first.
- 04
Move the data
Existing records mapped, cleaned of duplicates and reconciled against the old system before anything is switched off.
- 05
Hand over
Training, documentation and the keys. Your team can run it, and we keep it working for as long as you want us to.
One set of records underneath
Customers, products, suppliers, people and stock are each defined once. A second system joins the first; it does not start a competing copy.
Runs where you decide
Your own servers, a private cloud or a cloud account that belongs to you. Customer, employee and financial data stays on infrastructure you control.
Yours to keep
You own the code, the data, the configuration and the documentation. There is no licence fee to us and nothing stopping another team from taking it on.
05Questions
Before you ask.
Questions about data platforms
Data warehouse, data lake or lakehouse: which do we need?
A warehouse if your data is structured and the goal is reporting. A lake if you hold large volumes of varied raw data for future use. A lakehouse if you want both on one platform, which is where most new builds now land. Small companies often need only a modest warehouse.
What is the difference between ETL and ELT?
The order of the steps. ETL transforms data before loading it into the store. ELT loads raw data first and transforms it inside the store, which is simpler to maintain now that storage and compute are cheap. Most modern platforms use ELT.
What is master data management, and do we need it?
It is keeping one agreed record for each core thing the business deals with: customers, suppliers, products, materials. You need it once the same thing appears in more than one system and the copies disagree, which is nearly every company with more than one system.
Can the platform run on our own infrastructure?
Yes. It can be built on premises, in a private cloud or in a public cloud account you own, using open formats so the data is never held hostage.
Guides
Plain-language guides on the problems this work solves.
- CRM, ERP, HRMS, CDP, PIM, WMS and the rest: thirty business systems explained in plain wordsBusiness systems · 8 min
- Custom software or off-the-shelf: how to decide whether to build, buy or extendBuild or buy · 3 min
- Custom CRM or off-the-shelf CRM: which does your sales team need?CRM · 3 min
- When does a company need a custom ERP?ERP · 3 min
- All 16 guides on this →
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