The challenge
Decisions wait on manual reports. Data sits in separate systems, teams define the same metric differently, and nobody is fully sure the numbers are right.
Service 07 ยท Data & Analytics
Data and analytics your teams can trust.
We build the data foundation, dashboards and reports that let leaders make decisions from current, consistent numbers.
Business problem
The problem we solve
Our approach
How we approach it
We establish one reliable data foundation, agree the definitions of the metrics that matter, and deliver dashboards and reports that update from live data.
Define the questions
Start with the decisions the numbers must support, and the definitions everyone will use.
Connect and clean
Bring data from source systems together and resolve inconsistencies.
Build and validate
Create dashboards and reports, then check them against known figures with the people who own them.
Operate and extend
Monitor data quality and add new metrics as questions change.
Capabilities
What Data & Analytics includes
Business intelligence
Dashboards that show the metrics leaders actually use, drawn from current data.
Reporting
Scheduled and on-demand reports with consistent definitions across teams.
Data engineering
Pipelines that collect, clean and combine data from your systems.
Data modeling
Structuring data so questions can be answered quickly and correctly.
Analytics
Analysis of sales, operations and customer behavior to find where to act.
Predictive analytics
Forecasting and prediction where your data quality and volume justify it.
Technology
Technology and what we use it for
Only technologies our team uses hands-on are listed.
- PostgreSQLAnalytical and transactional data storage
- MySQL and MongoDBConnecting to existing operational databases
- PythonData pipelines, analysis and models
- ReactInteractive dashboards inside your applications
Architecture considerations
How we structure the system
Trustworthy analytics starts with a reliable data foundation. Dashboards are only as good as the pipelines and definitions behind them.
Source to warehouse
Data from operational systems is extracted, cleaned and loaded into one structured store for analysis.
Governed definitions
Each metric has one written definition and one calculation, so reports agree with each other.
Scheduled and event-driven pipelines
Data refreshes on a schedule or when events occur, with checks that flag missing or unusual data.
Separation from operations
Analytical queries run against a separate store so they do not slow down the systems people work in.
Access by role
Dashboards and datasets expose only what each role is allowed to see.
Security considerations
How we protect it
These are the practices we plan into the work. They are not certifications.
Role-based data access
Datasets and dashboards expose only the data each role is permitted to see.
Sensitive data handling
Personal and confidential fields are masked, minimized or excluded from analytical stores where possible.
Encrypted storage and transfer
Data is encrypted in transit and, where the platform supports it, at rest.
Lineage and auditability
We record where data came from and how it was transformed, so figures can be traced and verified.
Retention rules
How long data is kept, and how it is deleted, is agreed at the start.
How we work
Our development process
Every engagement follows the same seven stages, with a checkpoint at each.
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Discover
Business requirements, users, constraints and objectives.
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Architect
Technology strategy, system architecture and a delivery roadmap.
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Design
UX and UI design with technical specifications.
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Build
Engineering and integrations, delivered in tested increments.
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Validate
QA, security and performance testing before release.
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Deploy
Production deployment with monitoring in place.
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Scale
Optimization, maintenance and future development.
Relevant industries
Where this applies
Retail
Digital commerce, inventory, customer engagement and analytics.
Manufacturing
Inventory, production, bill of materials, workflow and operational systems.
Finance
Business platforms, automation, analytics and secure digital systems.
Relevant projects
Related work
We do not have a published client case study for Data & Analytics yet, and we do not show work we cannot stand behind. Our own products, and the solutions we can build, are listed with their status.
FAQ
Frequently Asked Questions
Can you connect to our existing databases and tools?
Usually, yes. If a system exposes a database, an API or regular exports, its data can be brought into a reporting foundation.
Do you provide predictive analytics?
Where the data supports it. Prediction needs enough clean, relevant history, and we will say clearly if your data is not yet ready.
How do you make sure the numbers are correct?
We validate outputs against figures your team already trusts, document each metric definition and add checks that flag unusual data.
Discuss Your Data Needs
Tell us about your situation. An engineer will review it and reply with questions and a suggested approach.