Designing and Developing Decisional Data Warehouses: A Life Cycle Approach
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Beschreibung
This textbook introduces a groundbreaking methodology for data warehouse development, bridging the gap between technical design and real-world business needs. It offers a comprehensive, life cycle-oriented perspective that is both conceptually rigorous and practically relevant. Unlike traditional approaches that treat data warehouses as passive repositories, this book positions them as active enablers of business decision-making. It emphasizes aligning data warehouse design with organizational goals, ensuring that the system supports not just the identification of problems but also the selection of optimal decisions. The book covers the entire data warehouse development process—from requirements engineering to conceptual and logical design. It moves beyond the conventional focus on logical modeling to include upstream activities that are critical for building effective and usable systems. A unique, platform-agnostic conceptual model is introduced to represent analytical capabilities. This model facilitates seamless transitions between requirements, conceptual design, and logical implementation, making it adaptable to various technological environments. Recognizing the growing importance of unstructured data in decision-making, the book integrates support for both structured and unstructured data. It explores the use of both relational and NoSQL technologies to handle diverse data types effectively. The book advocates for an agile, iterative approach to data warehouse development. It introduces agility from the very beginning, starting with requirements engineering—and promotes continuous stakeholder involvement and incremental delivery of functional components. This book fills that gap by integrating business context, unstructured data analysis, and agile development principles into the core of data warehouse design. It is an essential resource for students, educators, and professionals seeking to build data warehouses that are not only technically sound but also strategically impactful.
This textbook introduces a groundbreaking methodology for data warehouse development, bridging the gap between technical design and real-world business needs. It offers a comprehensive, life cycle-oriented perspective that is both conceptually rigorous and practically relevant. Unlike traditional approaches that treat data warehouses as passive repositories, this book positions them as active enablers of business decision-making. It emphasizes aligning data warehouse design with organizational goals, ensuring that the system supports not just the identification of problems but also the selection of optimal decisions. The book covers the entire data warehouse development process—from requirements engineering to conceptual and logical design. It moves beyond the conventional focus on logical modeling to include upstream activities that are critical for building effective and usable systems. A unique, platform-agnostic conceptual model is introduced to represent analytical capabilities. This model facilitates seamless transitions between requirements, conceptual design, and logical implementation, making it adaptable to various technological environments. Recognizing the growing importance of unstructured data in decision-making, the book integrates support for both structured and unstructured data. It explores the use of both relational and NoSQL technologies to handle diverse data types effectively. The book advocates for an agile, iterative approach to data warehouse development. It introduces agility from the very beginning, starting with requirements engineering—and promotes continuous stakeholder involvement and incremental delivery of functional components. This book fills that gap by integrating business context, unstructured data analysis, and agile development principles into the core of data warehouse design. It is an essential resource for students, educators, and professionals seeking to build data warehouses that are not only technically sound but also strategically impactful.
Aligns data warehouse development with real business decision-making needs Covers the full data warehouse life cycle, from requirements engineering to logical design Handles both numeric and unstructured data like text and social media
Autor*in
Deepika Prakash
Themen in »Designing and Developing Decisional Data Warehouses: A Life Cycle Approach«
Data Warehouse System Decisional Requirements Engineering Conceptual Model for analysable data Unstructured data for data warehouse development Agile data warehouse development ROLAP Column Oriented Data Warehouses Document Oriented Data Warehouses Cassandra HBase MongoDB NoSQL