Building a Modern Marketing Campaign Operations App with Microsoft Fabric & Rayfin
Excited to share a new project: Fabric App – Rayfin Marketing Campaign Operations! Built using Microsoft Fabric, Rayfin, React, interactive maps, persistent workflows, and performance analytics, this application demonstrates how organizations can move beyond dashboards and create operational apps directly on top of Fabric data. ✅ Campaign workflow management ✅ Interactive geospatial visualisation ✅ Embedded analytics & KPIs ✅ Modern React-based experience A great example of how Microsoft Fabric can power both analytics and business applications on a unified platform. Marketing teams often manage campaigns across multiple regions, channels, and vendors. While analytics platforms provide visibility into campaign performance, operational actions still happen outside the analytics environment through emails, spreadsheets, and disconnected applications. This creates challenges such as: Limited operational visibility Manual campaign tracking Delayed decision-making Fragmented workflows Lack of location-based campaign insights The application combines: Microsoft Fabric as the unified data platform Rayfin for application development React for modern user interaction Geospatial Maps for regional campaign visibility Persistent Workflows for campaign management Analytics Dashboards for performance monitoring The solution demonstrates how organizations can: Business Need Solution Campaign Tracking Persistent workflow management Regional Insights Interactive maps Performance Monitoring Embedded analytics Faster Decisions Real-time data access Operational Efficiency Unified application experience Conclusion: This project demonstrates how Microsoft Fabric and Rayfin can be combined to create modern, data-driven operational applications that move beyond traditional dashboards. By integrating interactive maps, persistent workflows, React-based experiences, and analytics, organizations can empower business users to both understand and act on their data from a single application. If you are exploring how to operationalize your Fabric investments beyond reporting, this project provides a practical example of what's possible.Building a Modern Marketing Campaign Operations App with Microsoft Fabric & Rayfin
🚀 Excited to share my latest Microsoft Fabric application built using Rayfin, React, interactive maps, persistent workflows, and performance analytics. This solution demonstrates how Microsoft Fabric can be used for more than analytics by enabling operational business applications directly on top of Fabric data. I recently built an interactive marketing campaign operations application using Microsoft Fabric, Rayfin, React, interactive maps, persistent workflows, and real-time analytics. The goal was simple: demonstrate how business teams can move beyond static reports and spreadsheets to a fully interactive operational application running directly on top of Fabric data. The Challenge Marketing teams often manage campaigns across multiple regions, channels, and vendors. While analytics platforms provide visibility into campaign performance, operational actions still happen outside the analytics environment through emails, spreadsheets, and disconnected applications. This creates challenges such as: Limited operational visibility Manual campaign tracking Delayed decision-making Fragmented workflows Lack of location-based campaign insights Solution Architecture The application combines: Microsoft Fabric as the unified data platform Rayfin for application development React for modern user interaction Geospatial Maps for regional campaign visibility Persistent Workflows for campaign management Analytics Dashboards for performance monitoring Key Features 🗺️ Interactive Campaign Maps One of the most exciting capabilities is geospatial visualization. Users can: View active campaigns by location Identify regional performance differences Drill into campaign details Monitor coverage across territories Instead of looking at rows in a table, stakeholders can instantly understand campaign reach on a map. 🔄 Persistent Workflow Management Campaign execution requires multiple steps and stakeholders. The application enables: Campaign creation Approval workflows Status tracking Ownership management Execution monitoring Workflow state persists even after users leave and return to the application, creating a true operational experience rather than a simple dashboard. 📊 Campaign Performance Analytics Analytics are embedded directly into operational processes. Business users can monitor: Campaign ROI Regional performance Campaign effectiveness Operational KPIs Trend analysis This removes the gap between insights and actions. ⚛️ Modern React-Based Experience The application delivers a responsive and intuitive experience using React. Benefits include: Fast performance Interactive user experience Component-driven architecture Easy extensibility Mobile-friendly design Why Rayfin + Microsoft Fabric? Many organisations already use Fabric for analytics but struggle when they need operational applications. Rayfin enables teams to: ✅ Build applications directly on Fabric data ✅ Reduce application development complexity ✅ Accelerate business solution delivery ✅ Combine analytics and operational workflows ✅ Create engaging user experiences without extensive custom development This dramatically shortens the time between identifying a business problem and delivering a working solution. Repository 🔗 GitHub: https://github.com/nikunj11itdhm/Fabric-App-Rayfin-MarketingCampaign I'd love to hear feedback from the community and discuss ideas for future enhancements such as AI-powered recommendations, Copilot integration, and predictive analytics. #MicrosoftFabric #FabricApps #Rayfin #React #PowerBI #DataEngineering #Analytics #DataApps #MicrosoftDataPlatform #CommunityShowcase
IBCS inspired Fabric app designed with Framework Skill
I created the following app with Claude Code, OPUS 5.5 and subagents. - I used an IBCS Skill which I developed for creating IBCS-inspired custom Visuals - I also used a Semantic model which was used for Controlling Demo cases before - The layout: I used a framework I used before to align Power BI reports to Grids -The idea is to provide the coding agent with skills, a playbook, and a framework to generate reproducible, similar outputs. Maybe this is not the crazy cool report for a showcase, but is the report the finance and controlling department will like ;) at least the ones in Germany ;-)Accounts Receivable Dashboard
📊 Accounts Receivable Dashboard for Enhanced Financial Oversight An interactive Power BI dashboard developed to provide end-to-end visibility into receivables performance, supporting proactive credit control and cash flow optimization. 🔹 Core Features: Summary of Total Invoices, Payments, Outstanding Balances, and Due Invoices Receivables Ageing by customer with overdue flags and settlement timelines Trend insights on monthly receivables, payment behavior, and balance fluctuations Dynamic filtering by Year, Month, Product, Region, and Sales Representative 🎯 Value Delivered: Improves operational efficiency by enabling real-time monitoring of ageing receivables, supporting quicker recovery actions, and enhancing overall working capital health. Designed for finance and commercial teams to align collection strategies with data-driven insights. Thanks, eyJrIjoiMmM2OWQ3ZWItZDBmNS00ZjUyLTk2NTMtOTZhNGQwM2Y1ZjhkIiwidCI6ImQ4ZTFiMDVlLTcwYWEtNGVmNy1iODc4LTQ2NmI2ODhmOTUyZiJ9Golden Wok Delivery Network Intelligence
From network pressure to service reliability and corridor-level action Golden Wok’s delivery network presents a connected operational challenge: understanding where delivery pressure originates, when service reliability begins to deteriorate, and which corridors require attention. The report follows a three-stage analytical journey: Network Performance → Service Reliability → Network Optimization 01 | Network Performance The first page explores where delivery pressure originates across the network. Delivery radius, traffic friction, weather conditions and zone tiers provide the context for understanding where operational pressure is concentrated and how those conditions affect delivery performance. Outcome: Identify where network conditions create the greatest delivery pressure. 02 | Service Reliability The second page focuses on what happens as delivery performance deteriorates. One of the clearest findings was the relationship between delivery duration and SLA risk. Breach rates increased sharply across longer delivery-time bands, while customer ratings remained comparatively stable. This made service reliability a stronger operational signal than the customer-rating response in the supplied data. Outcome: Understand when delivery performance begins to translate into significant SLA risk. 03 | Network Optimization The final page moves from diagnosis to action. I combined Profit Efficiency and SLA Risk to classify delivery corridors into Priority Intervention, Service Intervention, Economic Optimization, and Protect & Maintain. ABC classification then adds economic importance, helping distinguish valuable corridors that should be protected or repaired from weaker, higher-risk corridors that may warrant deeper review. Interactive tooltips provide additional corridor and intervention context without overcrowding the main report. Outcome: Prioritize corridor-level action based on economic value and service reliability. Validation Before Visualization The brief served as a checklist for testing key assumptions against the supplied data. Where discrepancies appeared, values were adjusted only when defensible or excluded when they could not be reliably interpreted. This kept the analysis grounded in the brief while allowing validated evidence to determine the final story. Final Takeaway Golden Wok became a simple decision journey: Diagnose → Understand → Prioritize The project reinforced the importance of validating assumptions before visualization and keeping each report page focused on a clear business question. A rich operational dataset does not need a crowded report. Every visual should help move the analysis closer to a decision. Data Source: September 2026 DataDNA – Golden Wok Food Delivery Analytics ChallengeF&B Sales Performance Dashboard
F&B Sales Intelligence Dashboard An interactive dashboard developed as part of my data analytics portfolio to explore sales performance across three F&B outlets in Indonesia. It uses the Anonymous Transactional Dataset from Mendeley Data, containing historical POS transactions and product metadata for January–September 2025. The dashboard covers sales KPIs, outlet performance, weekly trends, transaction intensity by day and operating hour, and product rankings. It also incorporates RFM-based transaction segmentation using K-Means, replicating a published methodology with the full dataset. Four transaction segments are summarized by volume, average spending, and total transaction value. The analysis covers 53,820 transactions with a total transaction value of approximately IDR 1.32 billion. Key findings include SHOP001 contributing nearly 49% of total transaction value and high-value transactions contributing a substantial share despite their smaller volume. Tools: Power BI and Google Colab (Python) Skills: Data modeling, DAX, KPI development, interactive visualization, RFM analysis, K-Means clustering, and insight communication. Dataset: https://data.mendeley.com/datasets/kcgf45y24m/2 Feedback on the dashboard’s design, analysis, and usability is welcome.Kanban Board
A sales pipeline where moving a card changes more than its column. Drag individual deals or a group of cards between stages and watch the weighted forecast update. Capacity limits, keyboard moves, and undo make the board as practical as it is tactile. The board is live connected to a database so moving cards between columns updates and saves automatically.Makeover Monday week 36 - Americans favourite season
At the start of the week I saw that at dm-p had developed and released a chart xkcd custom visual for Power BI so I thought I'd use it for this weeks Makeover Monday data on Americans favourite season. It's a very small dataset and not all of it ideal for the visuals but was a good opportunity to try it out, I even bought myself to create some pie and Doughnut charts. eyJrIjoiZjc4MTY4YjItMzNmMi00YzBiLTgyMGYtNTM3MDgxMTBmMGY1IiwidCI6IjgzNzBjZjE0LTE2ZjMtNGMxNi1iODNjLTcyNDA3MTY1NDM1NiIsImMiOjh9E-commerce Profitability Audit: Protect, Monitor or Act
Built with the dataset from the ZoomCharts 4U Report Challenge (European e-commerce, 2024–2025). The question: Sales grew 69% and contribution margin more than doubled, but which categories actually stayed profitable? Page 1 – Audit: each category gets a verdict (Protect, Monitor, Act) based on three rules: CM %, product cost % of sales, and other operating cost %. The rules are shown on the page, so the verdict is transparent. Hover over any category to see a tooltip comparing its cost lines with the healthy categories. Page 2 – Detail: a P&L variance table (current vs prior year) and a margin bridge from prior-year CM to current-year CM. Every subtotal reconciles. Key findings: Beauty, Fashion and Sports & Outdoors deliver about 79% of margin. Electronics runs at 3.4% CM, the only category in Act. Product cost rose about $97K, but most costs grew slower than sales, so CM % improved by 3.3 pp. Feedback welcome.E-commerce Profitability Audit: Protect, Monitor or Act
Built with the dataset from the ZoomCharts 4U Report Challenge (European e-commerce, 2024–2025). The question: Sales grew 69% and contribution margin more than doubled, but which categories actually stayed profitable? Page 1 – Audit: each category gets a verdict (Protect, Monitor, Act) based on three rules: CM %, product cost % of sales, and other operating cost %. The rules are shown on the page, so the verdict is transparent. Hover over any category to see a tooltip comparing its cost lines with the healthy categories. Page 2 – Detail: a P&L variance table (current vs prior year) and a margin bridge from prior-year CM to current-year CM. Every subtotal reconciles. Key findings: Beauty, Fashion and Sports & Outdoors deliver about 79% of margin. Electronics runs at 3.4% CM, the only category in Act. Product cost rose about $97K, but most costs grew slower than sales, so CM % improved by 3.3 pp. Feedback welcome.
