QlikView Implementation and Scripting Guide (eBook, ePUB)
Definitive Reference for Developers and Engineers
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"QlikView Implementation and Scripting Guide" The "QlikView Implementation and Scripting Guide" serves as the definitive resource for business intelligence professionals seeking to master all aspects of QlikView-from architectural foundations and system deployment to advanced scripting and application development. The book begins by demystifying QlikView's unique associative engine, multi-layered architecture, and options for both on-premise and cloud deployments, emphasizing reliability, scalability, and disaster recovery. By exploring core system components, data security, and robust scaling...
"QlikView Implementation and Scripting Guide"
The "QlikView Implementation and Scripting Guide" serves as the definitive resource for business intelligence professionals seeking to master all aspects of QlikView-from architectural foundations and system deployment to advanced scripting and application development. The book begins by demystifying QlikView's unique associative engine, multi-layered architecture, and options for both on-premise and cloud deployments, emphasizing reliability, scalability, and disaster recovery. By exploring core system components, data security, and robust scaling strategies, it empowers architects and administrators to design efficient and resilient QlikView environments tailored for enterprise needs.
A core focus of the guide lies in the breadth and depth of its data integration and modeling strategies. Readers are introduced to practical techniques for seamlessly connecting with relational databases, big data platforms, APIs, and file-based sources, along with a strong emphasis on authentication, metadata management, and data cataloging. Through detailed sections on associative and dimensional modeling, incremental loading, partitioning, and QVD layering, the book equips data engineers and modelers with the advanced tools and best practices required to build high-performance, manageable, and auditable QlikView data solutions across complex business domains.
The guide further distinguishes itself with in-depth coverage of advanced QlikView scripting, ETL automation, and professional application development. Readers learn to craft maintainable, modular scripts, implement effective ETL orchestration, and automate both data refreshes and operational reporting. The book delves into UI engineering, visualization excellence, mobile optimization, and rigorous performance tuning. Complemented by essential guidance on governance, security, DevOps workflows, and extensibility-including integration with APIs, advanced analytics services, and real-time streaming data-this comprehensive work is an indispensable companion for QlikView practitioners striving for technical mastery and scalable, future-ready analytics solutions.
The "QlikView Implementation and Scripting Guide" serves as the definitive resource for business intelligence professionals seeking to master all aspects of QlikView-from architectural foundations and system deployment to advanced scripting and application development. The book begins by demystifying QlikView's unique associative engine, multi-layered architecture, and options for both on-premise and cloud deployments, emphasizing reliability, scalability, and disaster recovery. By exploring core system components, data security, and robust scaling strategies, it empowers architects and administrators to design efficient and resilient QlikView environments tailored for enterprise needs.
A core focus of the guide lies in the breadth and depth of its data integration and modeling strategies. Readers are introduced to practical techniques for seamlessly connecting with relational databases, big data platforms, APIs, and file-based sources, along with a strong emphasis on authentication, metadata management, and data cataloging. Through detailed sections on associative and dimensional modeling, incremental loading, partitioning, and QVD layering, the book equips data engineers and modelers with the advanced tools and best practices required to build high-performance, manageable, and auditable QlikView data solutions across complex business domains.
The guide further distinguishes itself with in-depth coverage of advanced QlikView scripting, ETL automation, and professional application development. Readers learn to craft maintainable, modular scripts, implement effective ETL orchestration, and automate both data refreshes and operational reporting. The book delves into UI engineering, visualization excellence, mobile optimization, and rigorous performance tuning. Complemented by essential guidance on governance, security, DevOps workflows, and extensibility-including integration with APIs, advanced analytics services, and real-time streaming data-this comprehensive work is an indispensable companion for QlikView practitioners striving for technical mastery and scalable, future-ready analytics solutions.
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