"Core Concept of Multi-Model Databases" is a comprehensive, practical, and accessible guide designed to equip students and professionals with the essential knowledge and skills to navigate the next generation of data management. In an era where data is inherently complex and multifaceted, this book demystifies the powerful paradigm of multi-model databases, which provide a unified platform to handle diverse data types like documents, graphs, and key-value pairs within a single, integrated system. Key Features: 1. Beginner to Advanced Trajectory: The book starts with the absolute basics of different data models and progressively builds up to advanced topics like cross-model querying, transaction management, and cloud deployment, making it suitable for all levels. 2. Hands-On Learning: Every chapter includes practical exercises, code snippets, and mini-projects that allow readers to immediately apply what they have learned. 3. Real-World Case Studies: Explores in-depth case studies from various industries like e-commerce, finance, and IoT, demonstrating how multi-model databases solve complex, real-world problems. 4. Complete Capstone Project: The final chapter is a comprehensive, step-by-step guide to building a full-stack "E-commerce Analytics Platform," complete with working code and detailed explanations. 5. Simplified and Relevant Content: Complex jargon is minimized, and concepts are explained in the easiest possible language, using practical examples that resonate with students and developers. 6. Focus on Core Concepts: While specific databases like ArangoDB are used for practical examples, the primary focus remains on the fundamental principles of multi-model architecture, ensuring the knowledge is transferable across different technologies. 7. Covers the Full Spectrum: From history and evolution to future trends like AI/ML integration, this book provides a 360-degree view of the multi-model database landscape. The content is meticulously curated to cater to both undergraduate (B.Tech) and postgraduate (M.Tech) students in Computer Science, Information Technology, and related fields. It also serves as a valuable resource for software developers, data engineers, and architects looking to upgrade their skills for the modern data landscape. The syllabus is designed with a global perspective, ensuring its relevance in universities worldwide.
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