What does this service deliver?
We begin with the source, definition and quality of the data.
Shared KPI definitions
Traceable data quality
Reports governed by access permissions
Data Analytics & Reporting
A shared data layer for analytics and reporting.
We bring data from different systems under shared definitions and connect management reports and operational dashboards to a dependable data layer.
What is included?
Consistent reporting depends on shared data definitions.
When the same metric differs between reports, the cause is often not the visualisation tool but inconsistent source, date, filter or calculation definitions. We first identify these differences and establish who produces and owns the data.
We connect source systems through ETL or ELT pipelines and build quality rules, the data warehouse, a shared metric model, management dashboards and role-based access as one system. If an existing Power BI or similar reporting investment remains suitable, we retain it rather than recommending an unnecessary tool change.
Service scope
What the engagement can include
Data source integration
We collect data from operational systems, files and services while preserving its source and lineage.
ETL/ELT and data quality
We use transformation, validation and error rules to identify missing or inconsistent records.
Data warehousing and modelling
We design analytical data models that use a shared definition and calculation for each KPI.
Management dashboards and user reports
We develop reporting interfaces that give teams access to the KPIs and detail allowed by their roles.
Forecasting and advanced analytics
We develop demand, risk or behaviour forecasts so that predictions can be compared with actual outcomes.
Data ownership and access
We define the data dictionary, quality ownership, access permissions and sensitive-data rules within the project scope.
Technologies considered for the project
ETL / ELTData warehousePostgreSQLClickHousePower BIPython
The final stack depends on your current environment, team and requirements.Decision guide
When is this service a good fit?
When different numbers are being discussed in the same meeting.Current situation
Reports are prepared manually and arrive too late
How we approach it
We combine sources in dependable data pipelines and automate repeat reporting.
Intended outcomeAccess to current information when a decision is being made
Current situation
KPI definitions differ between teams
How we approach it
We establish a shared business glossary, metric owners and calculation rules.
Intended outcomeOne agreed definition for each KPI
Current situation
Data exists, but forecasts cannot be used
How we approach it
After establishing data quality and baseline reporting, we compare forecast outputs with actual results.
Intended outcomeForecast performance measured against actual outcomes
Let us assess the use case, available data and cost of error together.Review your reporting environment ↗
Frequently asked questions
Common questions about data, quality and production use.
Can we keep our current Power BI or reporting tool?+
Yes. If the underlying need is a stronger data model rather than a new visualisation tool, we can retain the existing investment and improve the foundation.
Will data-quality issues stop the project?+
We define a rule, owner and remediation plan for each issue. Critical sources can be cleaned and validated in stages.
How is access controlled?+
Access can be designed at user, role, row, column and sensitive-data levels, with access events recorded where required.
Can we begin with forecasting immediately?+
We first assess data sufficiency, quality and the decision the forecast must support. If the foundation is not ready, a small validation exercise can reduce risk before wider implementation.
How are timescale and cost determined?+
Timescale and cost are set after we understand the scope, current systems, integrations, data migration, testing and support requirements. We do not promise a fixed duration or price without this information.