DWH, Data Lake и Data Lakehouse: архитектурные различия и практическое применение // Инженер данных

📍 Webinar Agenda: Data Warehouse (DWH) Classic Architecture and Principles Pros and Cons: Strict Schema, Performance, Cost Data Lake Storing Raw Data of Any Format Management and Governance Issues Data Lakehouse Combining DWH and Data Lake Best Practices ACID Transactions and BI Analytics Support Comparative Analysis Selection Criteria for Different Tasks Implementation Examples Use Cases When to Choose a DWH and When a Lakehouse Migration Between Approaches 👥 Who will benefit from this webinar: Data Engineers and Architects Analysts and BI Specialists Technical Managers ✅ What Users Will Get: A Clear Understanding of the Differences Between Approaches Criteria for Choosing an Architecture for Your Needs Successful Examples Implementations Practical Implementation Guidelines "Data Engineer" - https://otus.pw/pGAm/ Instructor: Vadim Zaigrin - Leading Technology Expert Take the survey following the event - https://otus.pw/6KUE/ Follow the project news: → VK: https://vk.com/otusru → Telegram: https://t.me/Otusjava → Habr: https://otus.pw/S0nM/ → Max: https://otus.pw/wVga/