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Judul Decoding Data : A Complete Guide to Business Intelligence / M. A. Qureshi; Amara Atif; Yang Yang; Meena Jha; FLORENCE MWAGWABI; Marcella Papini
Pengarang A. Qureshi, M.
Atif, Amara
Yang, Yang
Jha, Meena
MWAGWABI, FLORENCE
Papini, Marcella
Penerbitan Sydney : UTS ePRESS, 2026
Deskripsi Fisik 320 p.
ISBN 9781923373068
Subjek DATA SCIENCE AND ANALYSIS
Catatan In an era where data-driven decision-making is paramount, “Decoding Data: A Complete Guide to Business Intelligence” serves as an essential Open Educational Resource (OER) tailored for both students and professionals seeking to develop a deep understanding of Business Intelligence (BI) strategies. This resource aims to empower learners with the knowledge and skills necessary to harness the full potential of BI in the modern business landscape. This comprehensive resource covers a wide spectrum of BI topics, including data to knowledge continuum, systems for decision support, the architecture of BI, business analytics, reporting, and emerging technologies. An innovative pedagogical approach combines theoretical concepts with practical skills for effective data utilisation by creating reports, visualisations, and dashboards, offering readers a holistic understanding of BI concepts. With hands-on exercises and real-world case studies, “Decoding Data: A Complete Guide to Business Intelligence” goes beyond traditi
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Lokasi Akses Online https://directory.doabooks.org/handle/20.500.12854/175846

 
No Barcode No. Panggil Akses Lokasi Ketersediaan
207826192 004 Dec Baca Online Perpustakaan Pusat - Online Resources
Ebook
Tersedia
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245 1 # $a Decoding Data : $b A Complete Guide to Business Intelligence /$c M. A. Qureshi; Amara Atif; Yang Yang; Meena Jha; FLORENCE MWAGWABI; Marcella Papini
260 # # $a Sydney :$b UTS ePRESS,$c 2026
300 # # $a 320 p.
505 # # $a In an era where data-driven decision-making is paramount, “Decoding Data: A Complete Guide to Business Intelligence” serves as an essential Open Educational Resource (OER) tailored for both students and professionals seeking to develop a deep understanding of Business Intelligence (BI) strategies. This resource aims to empower learners with the knowledge and skills necessary to harness the full potential of BI in the modern business landscape. This comprehensive resource covers a wide spectrum of BI topics, including data to knowledge continuum, systems for decision support, the architecture of BI, business analytics, reporting, and emerging technologies. An innovative pedagogical approach combines theoretical concepts with practical skills for effective data utilisation by creating reports, visualisations, and dashboards, offering readers a holistic understanding of BI concepts. With hands-on exercises and real-world case studies, “Decoding Data: A Complete Guide to Business Intelligence” goes beyond traditional learning methods, providing interactive tools that engage and challenge the reader. The content is organised as a roadmap, guiding readers through the complexities of BI implementation, starting from foundational concepts and progressing seamlessly toward advanced data analytics. This journey equips users with theoretical groundwork and practical skills directly applicable across diverse business scenarios. The book’s focus on key concepts and theories ensures users a sophisticated comprehension of BI, enhancing their analytical skills and decision-making capabilities. More than a textbook, “Decoding Data: A Complete Guide to Business Intelligence” is a pathway to enhancing analytical skills, refining decision-making abilities, and cultivating a profound appreciation for BI’s pivotal role in driving organisational success. This resource promises not just knowledge acquisition but tangible skills development. Embark on a transformative journey with “Decoding Data: A Complete Guide to Business Intelligence”, where theory meets practice, and education evolves into actionable insights.
650 # # $a DATA SCIENCE AND ANALYSIS
700 1 # $a Atif, Amara
700 1 # $a Jha, Meena
700 1 # $a MWAGWABI, FLORENCE
700 1 # $a Papini, Marcella
700 1 # $a Yang, Yang
856 # # $a https://directory.doabooks.org/handle/20.500.12854/175846
990 # # $a 207826192
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