Building a Future-Ready Data Platform with Microsoft Fabric and Medallion Approach

⚡ Accelerating Enterprise Intelligence: Real-Time Data Pipelines on Snowflake + Microsoft Fabric Data-driven enterprises can’t afford delays; insights need to flow in real time to fuel smarter decisions, optimize spend, and unlock innovation. In our latest blog, we break down how combining Snowflake + Microsoft Fabric empowers you to: ✅ Build high-performance, real-time pipelines ✅ Simplify integration across multi-cloud environments ✅ Deliver analytics at the speed of business 🔗 Read the Blog: https://lnkd.in/dpCgDDed 👉 Ready to move from batch to real-time? Start building your enterprise intelligence edge today. #EnterpriseAnalytics #Snowflake #MicrosoftFabric #RealTimeData #DataEngineering #InfojiniBlogs

🚀 Microsoft Fabric Deep Dive (Part 3): Data Factory in Microsoft Fabric — The New Era of Data Movement! Data Factory isn’t gone — it’s evolved inside Microsoft Fabric. Now pipelines, orchestrations, and dataflows sit right next to your data in OneLake for a truly unified experience. 📘 What is Data Factory in Fabric? It’s the orchestration and ingestion layer inside Fabric that helps you move, transform, and schedule data — while calling notebooks, dataflows, and other Fabric services without leaving the portal. 💡 Step-by-step (how a typical Fabric pipeline flows): 1️⃣ Ingest — Bring data from sources (APIs, databases, Event Hubs, S3, ADLS) into OneLake or via shortcuts. 2️⃣ Prepare — Run Spark notebooks or dataflows to clean, enrich, and write Delta tables. 3️⃣ Orchestrate — Use Fabric pipelines to schedule, chain, and trigger notebooks, dataflows, and downstream jobs. 4️⃣ Deliver & Monitor — Load transformed data to Lakehouse/Warehouse and monitor runs in Fabric’s unified monitoring experience. 💡 Key Concepts Simplified: Pipelines — Visual workflows that orchestrate tasks and dependencies. Notebooks & Dataflows — Code-first (Spark notebooks) or low-code transforms (dataflows). Triggers — Schedule-based, event-based, or manual triggers to run pipelines. Shortcuts & Linked services — Connect or point to external data without copying. Unified monitoring — End-to-end run logs, lineage, and alerts in the Fabric portal. 🔥 Why It’s a Game-Changer: No cross-service hops — faster data movement and simpler debugging. Seamless collaboration — engineers and analysts work with the same data surface. Less ops overhead — single access control, monitoring, and governance inside Fabric. 📎 Want to explore? 🔗 Official Docs: https://lnkd.in/d3dp5wrc Stay tuned — my next post will cover “Lakehouse vs Data Warehouse in Fabric” — when to use each and how they work together. 💬 Comment below if you’d like a sample pipeline diagram, a demo notebook, or a step-by-step pipeline template I can share next! #MicrosoftFabric #DataFactory #Azure #ETL #DataEngineering #FabricCommunity #PowerBI #OneLake #CloudData #DataOps

🚀 Building Dynamic Dataflows with Parameterized Dataflow Gen2 in Microsoft Fabric 🚀 As data engineers, we know the pain of maintaining multiple versions of the same pipeline just to handle small differences across environments or business scenarios. That’s where Parameterized Dataflow Gen2 in Microsoft Fabric comes in. Instead of hardcoding values, you define parameters that can be injected at runtime—making your dataflows flexible, reusable, and automation-ready. 🔑 What this means for you: • One dataflow definition, many use cases • Seamless CI/CD across dev, test, and prod • Less duplication, less maintenance overhead • Dynamic execution by passing parameters via pipelines or APIs 💡 Example: You can parameterize your source workspace/lakehouse IDs, filtering values, and even the destination tables—so the same logic runs everywhere, with just different inputs. For anyone working on scalable, enterprise-grade data pipelines, this is a game changer. 👉 Check out the official guide here: https://lnkd.in/eR8YmiDs #DataEngineering #MicrosoftFabric #DataFactory #ETL #DataPipelines #DataIntegration #CloudData #BigData #AnalyticsEngineering #DataOps #Azure #DataTransformation

We’re excited to share a new article from our Senior Consultant, Alexander Turlov, now live on our blog. In "Why Microsoft Fabric Is a Game-Changer for Modern Data Platforms", Alex explores how Microsoft Fabric is reshaping the data landscape, bringing together engineering, analytics, and governance in one unified platform. If you're building or modernizing your data stack, this is a must-read. https://lnkd.in/gabAFUFJ #MicrosoftFabric #Data

We’re excited to share a new article from our Senior Consultant, Alexander Turlov, now live on our blog. In "Why Microsoft Fabric Is a Game-Changer for Modern Data Platforms", Alex explores how Microsoft Fabric is reshaping the data landscape, bringing together engineering, analytics, and governance in one unified platform. If you're building or modernizing your data stack, this is a must-read. https://lnkd.in/gabAFUFJ #MicrosoftFabric #Data

Guide to implementing Data Mesh on Microsoft Fabric—use domains, OneLake, Synapse, and Purview to build governed lakehouses, with challenges and real-world examples.

Proof Your Data Estate technical briefing events - an opportunity to explore how Microsoft Fabric is reshaping the future of data platforms. This session is designed for data leaders, engineers, and IT decision-makers who are navigating modernisation journeys—whether you're evolving from Synapse, SQL, or another legacy platform. We’ll walk through Microsoft’s roadmap, the rationale behind the shift to Fabric, and what it means for customer’s data estate, architecture, and team readiness.   What Customers Can Expect: Microsoft’s Vision: Understand how Fabric fits into the next-generation data strategy and what it means for legacy platforms. Migration Insights: Explore transition paths, tooling, timelines, and architectural shifts—whether you're coming from Synapse, SQL, or other environments. Business Value: Discover how Fabric can unlock cost efficiencies, scalability, and performance improvements. Technical Benefits: Learn about Fabric’s capabilities—from OneLake integration to Real-Time Intelligence and AI-powered analytics. Decision Points: Get clarity on what decisions you need to make now to prepare your team and platform for the future. https://lnkd.in/gBnTZFZH

🚀 Microsoft Fabric is redefining the modern data stack. With a unified architecture powered by OneLake, it seamlessly integrates Power BI, Synapse, and Data Factory into a single SaaS platform—eliminating silos and accelerating time to insight. From data ingestion to visualization, Fabric simplifies engineering, analytics, and governance—empowering organizations to manage and analyze data at scale with unprecedented agility. Whether you're building real-time dashboards or orchestrating complex pipelines, Fabric delivers a cohesive, scalable foundation for enterprise-grade analytics. 🔍 As data complexity grows, Fabric offers clarity. How do you see Microsoft Fabric transforming the future of data analytics in your organization? #MicrosoftFabric #PowerBI #DataEngineering #ModernDataStack #AnalyticsTransformation #CloudComputing

🏠 Week 3: Microsoft Fabric Foundations Fabric Architecture Overview Microsoft Fabric isn’t just another tool—it’s a unified SaaS analytics platform. ✨ What makes it powerful? ✔️ Built on a SaaS model → easy to manage, scale, and secure ✔️ Brings together components from: Power BI (visualization) Azure Synapse Analytics (data warehousing & analytics) Azure Data Factory (data integration & pipelines) ✔️ Provides a single environment for data engineering, integration, analytics, and visualization. 💡 Simply put → Fabric = One Lake, One Platform, One Experience. 🚀 Fabric architecture makes analytics faster, simpler, and smarter. 🔖 #FabricArchitecture #DataEngineering #MicrosoftFabric #DataPlatform #Analytics