Trustworthy data foundations
Map sources, data grain and refresh needs. Build pipelines and validation so missing records, duplicate joins and changing definitions are visible before they mislead a decision.
Business technology / Built for the work
Analytics & Business Intelligence
A useful dashboard starts before the chart. We help connect sources, define metrics and build reporting that answers real operational questions, with a clear view of where the numbers came from.
Talk to an Engineer ↗Recognize the friction?
When your reports raise more questions than answers
- Teams disagree about what the numbers mean.
- Reports require manual exports and spreadsheet reconciliation.
- Dashboards look polished but do not answer working questions.
- Data arrives late or without enough checks to trust it.
What we work on
Reliable data behind useful business reporting
Analytics & Business Intelligence makes reliable information available to the people making business decisions. We connect reporting needs, KPI definitions, data quality and delivery so a polished chart has a dependable foundation. Bring together data from separate systems, establish consistent calculations and give teams reports they can use to understand performance and decide what to do next.
Reports and dashboards
Design reports around the audience and the decisions they need to make. We work with Power BI, Looker, Sigma and in-app dashboards, choosing a format that fits your data and working routines. Use clear measures, useful filters and appropriate detail so people can answer questions without rebuilding the report each time.
Decision support and handoff
Document metric definitions and refresh behavior, and help users trace results back to their sources. Explain known data gaps and how they affect interpretation. Training and review sessions help people use the reports in real decisions and identify where another view or a clearer definition would help.
Models that explain the business
Agree KPI definitions, reporting periods and the level represented by each record. Where appropriate, introduce a warehouse or shared data model to reconcile sources and reuse consistent logic. Document transformations and check totals before broadening access; a technically successful refresh can still produce misleading numbers.
Access, distribution and adoption
Define which audiences may see sensitive detail and which need summaries. Plan report distribution, refresh visibility and training around actual working routines. Review adoption and questions after handoff so reporting can improve as the business changes, with responsibility for access and metric updates clearly assigned.
Example Projects
An operational scorecard
For a team needing an operational scorecard, combine workload and service data into a shared view with consistent definitions, useful filters and a documented refresh schedule.
Financial reporting validation
For a finance team preparing recurring reports, reconcile source totals before distribution and surface exceptions that need investigation, with enough detail to trace each discrepancy.
How we engage
From business questions to dependable answers
- Start with the decisions, audience and existing source systems.
- Agree definitions and validate the source data.
- Build reporting and review it against realistic questions.
- Document refresh, ownership and how to investigate discrepancies.
What you take forward
Practical deliverables.
- Metric definitions with calculation rules, source ownership, business context and known limitations.
- Data model and pipeline documentation describing validation, transformations and refresh dependencies.
- Reports or dashboards with appropriate access, distribution and operational checks.
- Handoff and training guidance, plus a backlog for improving coverage and answering new questions.
Before we get started
Questions worth asking.
Can you work with our reporting platform?
We work with Power BI, Looker, Sigma and embedded dashboards. We review your current tools, data access and reporting needs before recommending a change. An existing platform may be a good fit with better data preparation, clearer definitions or a more useful report design.
Do we need a new data warehouse?
Not always. The right foundation depends on source complexity, volume, refresh needs and the questions you need to answer.
What if the source data is unreliable?
We identify quality gaps and make their impact clear. A dashboard cannot repair a broken definition or missing records by itself; those issues need an explicit plan.
How does this differ from an in-app dashboard?
App Development may include a dashboard that helps a user complete a workflow. An analytics engagement focuses on reliable sources, shared definitions, data quality and decision support across the reporting lifecycle. The two can connect when application data becomes part of a wider reporting model.
Connected services
When the next step connects.
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Build applications that fit your workflows, connect your systems, and replace outdated software.
Explore App DevelopmentProcess Automation & Integration
Connect your tools and automate repetitive work so your team spends less time on manual handoffs.
Explore Process Automation & IntegrationA useful next conversation
Make the numbers useful to the people deciding.
Share the decisions you need to make and the reports you currently rely on. We can identify the missing foundations.