Data Integration & Reporting

No, usually you keep the systems you already use. The service connects your ERP, CRM, finance, warehouse and e-commerce systems, cleans the data, and agrees one set of KPI definitions across teams. Dashboards and reports are built on top of your existing reporting tool unless you specifically ask us to review alternatives. A first working dashboard or report is common within 3 to 5 weeks.

Cost depends on the number of systems connected, data volume, and how many KPIs and dashboards are needed. We usually start with one report or business area as a fixed-price pilot before pricing a wider rollout. This lets you confirm accuracy and adoption before expanding to more systems or teams. Ongoing support and monitoring are quoted separately as ongoing engagements.

We run a short workshop with business owners to agree one calculation, one source and one owner for each important measure. This becomes a written KPI dictionary that dashboards and reports are built against. When new conflicts appear later, the same owner and definition process resolves them. This keeps reporting consistent as new systems or teams are added.

Accuracy is maintained through data quality checks, freshness monitoring and clear ownership rules for each pipeline. We test coverage and correctness against source systems before launch, then track pipeline reliability and report preparation time on an ongoing basis. Alerts flag failed connections or unusual data changes so issues are caught before they reach a dashboard. This is reported alongside usage metrics after go-live.

You need to grant read access to the systems in scope, such as your ERP, CRM or finance database, following your normal approval process. We work within your existing security and access controls rather than requesting broad permissions. A system and data map is agreed with you first so only the required data flows are built. No changes to your core systems are needed.

The same clean, structured data and KPI definitions used for dashboards can feed models, assistants and automated workflows later. Because sources, fields and quality rules are already documented, AI teams do not need to redo data preparation. This removes one of the most common blockers to starting an AI project. Many clients treat integration and reporting as the foundation step before automation work.