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In this Knowledge Sharing Session (KSS), Ranjeev Kumar delivers a clear, practical, and interview-focused walkthrough of essential Databricks concepts—a must-have skillset for every aspiring or working Data Engineer. This session helps you understand not just how Databricks works, but why each component matters in real-time projects and interviews. 🧠 Topics Covered in This Session: 1. Databricks Workspace: Understanding the workspace layout, environment structure, and productivity features. 2. Cluster Configuration: Types of clusters, autoscaling, worker nodes, drivers, and best practices for configuration. 3. Databricks Architecture: High-level architecture, integration with cloud platforms, and workflow execution lifecycle. 4. Databricks Notebooks, Catalogs & SQL Editor: Working with notebooks, managing data through Unity Catalog, and writing SQL queries efficiently. 5. Delta Lake & ACID Transactions: What makes Delta Lake different, the importance of ACID compliance, and real-time use cases. 🎯 Who Should Watch? • Data Engineers • Data Analysts transitioning to DE • Anyone preparing for Databricks, Spark, or Azure/AWS-based DE roles • Students and professionals looking to build strong hands-on fundamentals 📌 About DataVerse Hub DataVerse Hub is a community-driven initiative with 1700+ members, helping each other grow in the fields of Data Engineering, Data Science, Analytics, and AI. We share: • Job referrals • HR contacts • Interview Q&A • Knowledge Sharing Sessions • Study resources • Peer support Empowering Data Careers, Together. 📲 Join the Community Become part of our WhatsApp DataVerse Hub group: https://chat.whatsapp.com/JSu09Ic5cbv... Follow us for updates: LinkedIn: / dataverse-hub 👍 If you found this session helpful: • Like the video • Comment your questions • Share it with others preparing for data roles • Subscribe for more KSS sessions and data-focused content