Dashboards we have built and shipped.
Kadmoon is a US Power BI and Microsoft Power Platform practice run by a senior, Microsoft-certified team, with more than 35 clients served. The dashboards you can open at /dashboards are illustrative demos built with the exact structure we ship on live projects; detailed client results are available under NDA.
QlikView to Power BI migration
- Reports migrated
- 1,247
- Parity validated
- 98.6%
The challenge
A large report estate on legacy BI was expensive to license and hard to trust, and the business needed to move to Power BI without losing years of logic or leaving users without reports mid-migration.
What we built
We inventoried every report, mapped dependencies, and rebuilt the estate in Power BI over a governed semantic model, migrating in waves so each business unit kept working the whole way through.
A single source of truth on Microsoft Fabric
- Net sales
- $18.42M
- Gross margin
- 27.8%
The challenge
An omnichannel retailer had three versions of the truth, with sales, inventory, and margin living in separate systems for physical stores and e-commerce, so no report agreed.
What we built
We consolidated the sources into OneLake on Microsoft Fabric and served Power BI through Direct Lake, so store and online data meet on one governed model with fast reports.
Executive OEE and cost BI
- Consolidated OEE
- 74.3%
- Availability
- 88.1%
The challenge
A multi-plant manufacturer could not see OEE and cost per line in time to act, because machine data and financials lived apart and reports arrived days late.
What we built
We brought MES and sensor data together with the ERP financials on a governed model and built executive Power BI dashboards for OEE, loss, and cost per line and product.
Purchasing and approvals on Power Platform
- Open
- 312
- Cycle time
- 2.4 d
The challenge
A purchasing process ran on email and spreadsheets, so requests stalled, approvals were hard to track, and no one could see where a given order actually was.
What we built
We rebuilt the flow on Power Apps and Power Automate with a governed environment, and put a Power BI view on top so leaders can see volume, aging, and bottlenecks by stage.
Predictive credit risk and collections
- Average 12m PD
- 6.8%
- 90+ delinquency
- 4.2%
The challenge
A lender managed a large portfolio with a rear-view mirror, seeing delinquency only after it happened, and could not prioritize collections by real risk.
What we built
We built the data foundation, trained a risk model on Azure Machine Learning, and served the score and a collections ladder through Power BI so the team works the highest-risk accounts first.
S&OP and demand planning
- Forecast accuracy
- 78.4%
- Average coverage
- 34 days
The challenge
An S&OP process ran on disconnected spreadsheets, so forecast accuracy was unknown and every function came to the meeting with a different number.
What we built
We built a governed planning model and Power BI dashboards that track demand, supply, and forecast accuracy by product family and horizon, giving the S&OP cycle one shared view.
Freight cost and OTIF service-level BI
- Freight cost
- 6.8%
- OTIF
- 92.4%
The challenge
A distribution network could not tell which carriers and regions were hurting service and cost, because tracking, freight, and orders lived in separate systems.
What we built
We consolidated carrier, freight, and order data on a governed model and built Power BI dashboards for OTIF and freight cost by carrier, lane, and region.
Management P&L across entities
- Net revenue
- $248.6M
- Gross margin
- 38.4%
The challenge
A group with several entities closed a management P&L by hand each month, so it arrived late, differed by preparer, and was hard to trust or drill into.
What we built
We built a governed financial model and a Power BI waterfall P&L that consolidates entities, compares actual to budget, and drills from the statement line to the transaction.
Enrollment and dropout BI
- Active enrollments
- 24,180
- Dropout in the semester
- 11.4%
The challenge
An education network saw enrollment and dropout only after the term closed, too late to intervene, with data spread across academic and financial systems.
What we built
We built a governed model over the academic and financial data and Power BI dashboards for enrollment, dropout, and results by campus, program, and term, with early-risk signals.
Claims denial and length-of-stay BI
- Occupancy rate
- 84.6%
- Average length of stay
- 4.2 days
The challenge
A hospital network lost revenue to claim denials it could not explain and could not see length of stay in time to manage capacity, with clinical and billing data apart.
What we built
We brought clinical operations and billing onto a governed model and built Power BI dashboards for claim denials by payer and reason and length of stay by unit and specialty, built with HIPAA in mind.
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