Building a Unified Data Platform for Healthcare Benefits Intelligence
Description Healthcare benefits data is one of the most underutilized strategic assets in enterprise organizations. Despite managing programs that generate millions of claims data points annually across medical, pharmacy, dental, and behavioral health lines, most organizations lack a unified data platform capable of turning this volume into usable intelligence. The result is siloed, reactive information that fails to inform the risk decisions driving organizational cost and employee outcomes, a challenge especially visible in large enterprises with significant annual financial exposure. This session presents a practical framework for building Enterprise Benefits Intelligence Platforms (EBIPs), scalable architectures that consolidate multi-source data from carriers, PBMs, TPA feeds, and eligibility systems into a single governed environment, dramatically reducing data latency versus siloed integrations. Attendees will explore how this foundation enables predictive risk stratification, utilization trending, and population health modeling, shifting organizations from reactive to proactive risk management, along with the governance models needed for HIPAA-compliant handling across complex vendor ecosystems. The session closes with decision intelligence layers that turn unified analytics into actionable dashboards for HR, Finance, and executive stakeholders. Attendees will leave with a replicable blueprint for modernizing benefits data infrastructure, drawn from real-world implementations.The AI-Assisted Data Developer: VS Code, Copilot & Claude Across Fabric, Power BI and SQL Server
AI features keep landing inside the Microsoft data platform — but the biggest productivity jump happens in your editor, not in the portal. In this demo-driven session I'll take one business request and build the solution end-to-end without leaving VS Code: exploring and refactoring T-SQL with the MSSQL extension and Copilot agent mode, scripting and deploying Fabric items with the Fabric CLI, editing semantic models as code with TMDL and PBIR, and generating DAX (including the new DAX user-defined functions) with AI assistance — all under source control with Git. Along the way I'll show where GitHub Copilot shines, where Claude does better, the prompting patterns that actually work for T-SQL, DAX and PySpark, and the guardrails you need so AI-generated code never reaches production unreviewed. Expect honest bloopers: you'll see where the AI gets it wrong and how to catch it. You'll leave with a setup checklist (extensions, MCP servers, repo layout), a set of reusable prompt patterns, and a practical decision guide for what to delegate to AI — and what not to.
Proactive Data Quality Engineering for Microsoft Fabric Healthcare Data Pipelines
Description Modern healthcare organizations increasingly rely on Microsoft Fabric to unify data engineering, analytics, and reporting across cloud-native platforms. As Medicare datasets such as claims, eligibility, enrollment, and provider information traverse multiple ingestion, transformation, and analytics layers, maintaining data quality becomes essential for regulatory compliance, operational efficiency, and trusted decision-making. Traditional quality assurance approaches that validate data only after pipeline execution often identify defects too late, resulting in costly remediation and inconsistent analytical outcomes. This session presents a proactive data quality engineering framework designed for Microsoft Fabric environments, embedding validation throughout the end-to-end data lifecycle. The framework integrates source-level verification for schema conformity, completeness, and referential integrity; transformation-level validation for mapping accuracy, business rule enforcement, and aggregations within Data Factory and Synapse Data Engineering; and cross-layer reconciliation across OneLake and analytical datasets. By incorporating automated validation workflows into Fabric pipelines, organizations can detect anomalies earlier, improve traceability, and support continuous data quality monitoring at scale. The session also demonstrates how healthcare-specific validation rules can be aligned with Medicare business processes while leveraging Microsoft Fabric's unified architecture for orchestration and analytics. Attendees will gain practical guidance on implementing scalable validation strategies that enhance governance, strengthen compliance readiness, and establish reliable healthcare data pipelines capable of supporting high-quality analytics and business intelligence.Handling Real Time data in Fabric Eventhouse
Event Details: Date: 19 September Time: 10:00 AM IST Speaker: Naveen Nagar | LinkedIn Profile About the Event: In today's data-driven world, organizations increasingly need to make sense of high-volume, fast-moving data - sensor telemetry, clickstreams, transactions, and logs - before the opportunity to act on it passes. Join us for this technical meetup as we explore Fabric Eventhouse, Microsoft Fabric's purpose-built engine for real-time analytics. This session will move beyond traditional batch pipelines to demonstrate a modern, low-latency data architecture where streaming data is captured, indexed, and made queryable within seconds. We will walk through a complete real-time data flow - from a live streaming source, into Eventhouse, and out to every consuming engine in Fabric via OneLake - without data duplication or performance trade-offs. What we will cover: Architecture: An end-to-end walkthrough of a real-time pipeline built on Fabric Eventstream, Eventhouse, and OneLake. Eventstream & Ingestion: How Eventstream captures, transforms, and routes streaming events from sources such as Azure Event Hub, IoT Hub, and CDC connectors into Eventhouse. Eventhouse & KQL Database: How KQL databases automatically index and time-partition data on arrival, and how update policies and materialized views enrich and aggregate data as it lands. OneLake Availability: How a single copy of streaming data becomes instantly available to Power BI, Warehouses, Notebooks, and Lakehouses through OneLake, eliminating the need for separate ETL copies. Live Demo: A practical, live walkthrough showing data flow from a streaming source, through Eventstream, into Eventhouse, out to OneLake, and into a live Power BI report in near real-time. This session is designed for: Data Engineers & Architects working with streaming data Power BI Developers & Fabric Users Analytics teams building real-time or near-real-time dashboards Anyone evaluating Microsoft Fabric's Real-Time Intelligence capabilitiesReal-Time Loyalty Intelligence on Microsoft Fabric for Agentic Commerce
Description Agentic commerce is projected to redirect three to five trillion dollars in global retail spending by 2030, and AI-driven retail website traffic grew 693% year-over-year during the 2025 holiday season. Every major agentic commerce protocol today treats agent-initiated transactions as anonymous guest checkouts, which means loyalty tier, points, and benefits disappear the moment an AI agent completes a purchase on a customer's behalf. Since loyalty members generate two to five times the revenue of non-members, this is a costly blind spot, and it is also a data engineering problem Fabric is well suited to solve. This session walks through a reference architecture for restoring tier recognition, benefit eligibility, and points accrual to machine-speed checkout flows operating under 100-millisecond latency budgets, built on Fabric's real-time stack. Eventstream and KQL Database power a Loyalty State Cache that serves pre-computed tier state in single-digit milliseconds using change-data-capture pipelines from the loyalty system of record. Data Activator drives a Benefit Eligibility Evaluator that resolves banner-parameterized offers and gated access in real time, while OneLake and Lakehouse provide the unified storage layer connecting transactional, promotional, and identity data without duplication. An asynchronous accrual engine settles points and benefit updates within seconds of payment confirmation, decoupled from the hot path. The talk covers concrete implementation patterns: staleness policies tuned by benefit type, from 15-minute tolerances for standard discounts to under 2 minutes for gated event access; a layered security model using short-lived, single-use tokens; and graceful degradation logic that preserves the purchase with retroactive accrual when real-time loyalty resolution fails. Attendees will leave with a working blueprint for using Fabric's real-time intelligence and OneLake foundation to keep loyalty programs intact as an increasing share of retail transactions shift to autonomous AI agents.Your Data Is Everywhere, Now What? Building A Modern Data Platform.
Microsoft Fabric User Group Accra: A Ghanaian company has data in Excel, SQL databases, APIs, operational systems and applications. Different teams have different numbers. Reports take days. Nobody trusts the dashboard. As far as you make decisions based on data, this is for you. This session introduces the Fabric ecosystem and demonstrates how the different workloads work together. Attendees will build a simple end-to-end solution that takes raw data, stores and transforms it in a Lakehouse, and exposes it for analysis. Learning objectives By the end of the session, attendees will be able to: Explain what Microsoft Fabric is and where it fits in the Microsoft data ecosystem. Identify the major Fabric workloads. Understand the role of OneLake. Distinguish between Lakehouse, Warehouse, and other Fabric workloads. Create a Fabric workspace. Build a basic data-to-insight workflow.Workforce Compliance and Time Fraud Detection reporting using PowerBI
Description Mode: Online Date & Time: 26 Sept 10 AM IST Managing time and attendance across a global workforce requires organizations to balance regulatory compliance, corporate policies, and operational efficiency. Traditional approaches often rely on manual reviews and fragmented processes, making it difficult to consistently identify compliance risks and potentially fraudulent activities in a timely manner. This session presents a real-world success story of a Machine Learning-powered Working Hours Alert System (WHAS) for modernizing workforce compliance monitoring and fraud detection. The solution analyzes time and attendance data to identify compliance risks, detect anomalous working-hour patterns that may indicate fraud, and recommend schedule adjustments aligned with labor laws and organizational policies. The session focuses on the data and machine learning aspects of building an intelligent compliance monitoring solution. Attendees will learn how workforce data can be analyzed to identify meaningful patterns, design effective alerts, support anomaly detection, and enable proactive intervention. The discussion will also cover implementation considerations, transparency, human oversight, and lessons learned from deploying an AI-driven compliance solution in a global enterprise environment. By connecting machine learning with enterprise workforce data, the presentation demonstrates how organizations can reduce manual effort, improve consistency in compliance monitoring, strengthen governance, and support more informed operational decisions. Attendees will gain practical perspectives they can apply when designing scalable data and analytics solutions for workforce compliance and operational integrity.Carreira na Europa com Microsoft Fabric: Como entrar, crescer e trabalhar na área de Dados
📅 04 de setembro de 2026 🕗 20:00 — Hora de Portugal (Lisboa) 💻 Online — Microsoft Teams 🌍 Idioma: Português Queres trabalhar na Europa na área de Dados? Já estás na Europa e queres fazer uma transição para Data Engineering, Data Analytics ou Business Intelligence? Então esta sessão é para ti. 🚀 O mercado europeu tem uma procura crescente por profissionais de Dados, Analytics e Data Engineering, e o Microsoft Fabric está a ganhar cada vez mais espaço nas organizações que procuram centralizar e modernizar as suas plataformas de dados. Nesta sessão do Fabric Lusófono, vamos falar sobre como podes utilizar o ecossistema Microsoft — especialmente Microsoft Fabric, Power BI, SQL, Azure, Python e outras tecnologias de dados — para construir uma carreira competitiva no mercado europeu. 🎯 O que vamos abordar? 🔹 Como está o mercado europeu de Dados e Analytics Que perfis são mais procurados e quais as competências que as empresas valorizam. 🔹 Microsoft Fabric como oportunidade de carreira Como o Fabric se encaixa nos papéis de Data Engineer, Analytics Engineer, Data Analyst, BI Developer e outros. 🔹 Como entrar na área de Dados na Europa Estratégias para quem está a começar ou pretende fazer uma mudança de carreira. 🔹 Como transformar conhecimento técnico em empregabilidade Certificações, projetos, GitHub, LinkedIn, portefólio e experiência prática — o que realmente pode fazer diferença. 🔹 Como construir um perfil internacional Como apresentar as tuas competências, experiência e projetos para empresas europeias. 🔹 Remote, Hybrid ou On-site? O que considerar quando procuras oportunidades em diferentes países europeus. 🔹 Do zero à primeira oportunidade Um possível caminho de aprendizagem para quem quer entrar em Data Analytics ou Data Engineering. 🌍 Para quem é esta sessão? Esta sessão é especialmente indicada para: 👨🏾💻 Profissionais de Dados que vivem fora da Europa e querem encontrar oportunidades no mercado europeu. 🌍 Profissionais que já estão na Europa e querem migrar para a área de Dados. 📊 Data Analysts, BI Developers e profissionais de Power BI que querem evoluir para Data Engineering ou Analytics Engineering. ⚙️ Data Engineers que querem fortalecer o seu conhecimento em Microsoft Fabric e posicionar-se melhor no mercado. 🎓 Estudantes e profissionais em transição de carreira que querem perceber por onde começar. 🚀 Profissionais que já trabalham com Microsoft, Azure, SQL ou Power BI e querem transformar essas competências numa carreira internacional. 💡 Mais do que aprender uma ferramenta Aprender Microsoft Fabric é importante. Mas saber construir uma carreira com essas competências é ainda mais importante. A ideia desta sessão é mostrar o caminho entre: 📚 Aprender → 🛠️ Praticar → 🧩 Construir projetos → 🎯 Criar um perfil profissional → 🇪🇺 Encontrar oportunidades Não precisas de saber tudo para começar. Precisas de saber o que aprender, como praticar e como demonstrar o teu valor ao mercado. Se tens o objetivo de trabalhar com Dados na Europa — ou simplesmente queres descobrir se esta pode ser a tua próxima carreira — junta-te a nós. Fabric Lusófono — Aprender. Partilhar. Crescer.
