Data and analytics
Data and analytics engineering
Every AI programme we have rescued failed at the data layer, not the model.
- Sector
- Services
- What you get
- 4
Our approach
Data and analytics engineering
We build the load-bearing part of a data-driven organisation: one trustworthy definition of your customers, patients, transactions or assets.
Ingestion, entity resolution across records never designed to agree, and a warehouse analysts and models can both query.
What you get
Artefacts you own and can hand to any engineer or auditor.
- Data architecture and modelling
- Batch and streaming pipelines
- Entity resolution and master data
- Quality monitoring, lineage and access control
Outcomes you should expect
Outcomes you should expect
- One agreed number for contested metrics
- Reporting without spreadsheet exports
- Data good enough to train models on
Tools and platforms
Tools and platforms
- dbt
- Airflow and Dagster
- Spark and Kafka
- Snowflake, BigQuery and Redshift
How we work
How we deliver
Best-practice process and development methodology, applied methodically.
- 01
Planning
We collect the relevant information from you and your stakeholders, including the constraints you have not written down.
- 02
Defining
We document the software needs, agree acceptance criteria, and write down what is out of scope.
- 03
Designing
System and interface documents are prepared against the specification: architecture, data model and stack.
- 04
Building
We implement in short cycles, with a working increment and a visible demonstration at the end of each.
- 05
Testing
We evaluate quality to find and fix defects: automated where possible, exploratory where judgement matters more.
- 06
Deployment
Release runs through an automated pipeline, checked for deployment issues, with a rehearsed rollback.
- 07
Maintenance
We keep the system current, secure and monitored, so you hear about problems from us first.
Questions
Frequently asked
Our data is spread across systems. A blocker?
No. Reconciling those systems is the work.
Do we need a warehouse first?
Usually a modest one, not a grand programme.
How does this relate to AI?
Retrieval, features and evaluation all depend on it.
Related services
Related services
Let’s talk
Let’s engineer your next advantage.
Tell us what you are trying to achieve. You will speak to an engineer, not a call centre.
Monday to Friday, 08:00 to 18:00 East Africa Time (GMT+3). Urgent support by arrangement.