These are showcase templates designed to demonstrate dashboard direction. Once a customer is onboarded, each template is tailored to their data model, security needs, and workflows.
Weaving data into Intelligent Decisions.
Explore how Dataloom crafts intelligent dashboards for enterprises across Pharma, Crop Science, Consumer Health, Insurance, and Retail — turning complex data into decisions that move businesses forward.
PharmaCrop ScienceConsumer HealthInsuranceRetail
Pharma
Trial execution, safety monitoring, and commercial analytics.
Crop Science
Yield forecasting, climate sensitivity, and supply reliability dashboards.
Consumer Health
Portfolio health, campaign lift, and omnichannel behavior intelligence.
Insurance
Claims transparency, fraud detection support, and policy lifecycle insights.
Retail
Store intelligence, margin control, and dynamic demand sensing.
App Experience Preview
Template experiences can be delivered as responsive web dashboards or embedded views with clean, low-friction interactions.
What teams say in discovery
Early-stage template reviews help stakeholders align quickly on KPIs, layout, and decision flow.
“The examples felt closer to production than a mockup. It helped our leadership team lock scope in one session.”
Pharma Strategy Lead
“We could clearly see how Power BI and custom web dashboards would fit different user groups without duplicating metrics.”
Retail Analytics Director
FAQ
Quick answers before you start a pilot engagement.
Yes. We design templates for practical integrations, including cloud warehouses, APIs, and enterprise systems. The integration layer is finalized during discovery.
Yes. Dataloom supports both Power BI templates and web-based dashboard builds. We recommend the format based on audience, governance, and interaction needs.
Most pilot engagements can begin within one to two weeks once scope, data readiness, and access dependencies are clear.
Ready to shape your first template?
Share your business goals and we will map the right dashboard format, KPI model, and data integration path.