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Dashboard Development
Custom dashboards in Tableau, Looker, Power BI, or custom-built React — designed around the specific decisions they need to support.
- Decision-first design
- Mobile-friendly
- Drill-through capability
OSYSTIC
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We build the pipelines, models, and dashboards that give your teams reliable self-serve access to the metrics that drive their decisions.
We scope around the system you actually need to operate, maintain, and operate — not a fixed vendor product or a one-size-fits-all implementation.
Custom dashboards in Tableau, Looker, Power BI, or custom-built React — designed around the specific decisions they need to support.
dbt models transforming raw data into reliable, documented, tested metrics — the single source of truth every downstream system depends on.
Semantic layers letting non-technical users answer their own questions without opening engineering tickets.
Scheduled report generation and distribution replacing manual export workflows — delivered to email, Slack, or any destination.
Working with your team to define, agree, and implement the metrics that matter — with a single documented definition for each.
Each engagement is broken into defined phases with reviewable outputs. Scope can adapt, but accountability stays visible.
Map the decisions each dashboard needs to support and the data sources available to answer them — before touching any data.
Assess data quality, freshness, and completeness. Surface issues now — not after building dashboards on bad data.
Build staging, intermediate, and mart models with tests at each layer. Every metric defined once, documented, tested.
Iterative delivery of dashboard views — reviewed with end users at each milestone, not just at the end.
Self-serve analytics layer so non-technical users can explore data without engineering support.
Technology choices follow your environment, operating constraints, team capability, and long-term ownership requirements.
The same technical capability can require very different controls, integrations, and operating models across industries.
Sales performance, inventory analytics, customer segmentation, promotion effectiveness.
P&L reporting, risk dashboards, regulatory reporting, cost centre analytics.
Clinical performance metrics, operational dashboards, population health analytics.
OEE dashboards, quality metrics, supply chain analytics, cost tracking.
The exact architecture and delivery plan depend on your environment. These answers describe how OSYSTIC approaches the work.
Yes, but we do not hide the problem. We surface data quality issues and build the dbt tests and transformations to address them. Dashboards on bad data produce bad decisions.
Looker, Tableau, Power BI, and Metabase most frequently. For custom requirements we build on React with charting libraries. The right tool depends on your existing stack and user base.
By building a semantic layer where metrics are defined once and referenced everywhere. When the definition changes, it changes in one place.
Yes. We run a metric definition workshop to agree on what matters, how each metric is calculated, and who owns it — before building anything.
Tell us what decisions your team needs to make faster. We will come back with an honest data and BI plan.