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Data Analytics for Business: Foundations and Industry Applications / Fenio Annansingh.

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Abingdon : Routledge, 2022.Edition: 1st edDescription: vi, 276 p. : ill. ; 2 cmISBN:
  • 9780367654191
  • 9780367654214
  • 9781003129356
Uniform titles:
  • Data Analytics for Business: Foundations and Industry Applications
Subject(s): DDC classification:
  • 23 658.05 ANN
Contents:
1 History and Evolution of Data Analytics 2 Data Mining and Analytics 3 Data Analytics Tools 4 Business Analytics and Intelligence 5 Customer Relationship Analytics, Cloud Computing, Blockchain, and Cognitive Computing 6 Cybersecurity and Data Analytics 7 Data Analytics and the Retail Industry 8 Data Analytics in the Financial Services Industry 9 Data Analytics in the Sports Industry 10 Data Analytics in the Accounting Industry 11 Data Analytics in the Medical Industry 12 Data Analytics in the Manufacturing Industry 13 Data Analytics in the Marketing Industry 14 Data Analytics in the Transportation Industry 15 Data Analytics in Education
Summary: Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor’s manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.
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Text Books Text Books CUTN Central Library Medicine, Technology & Management Non-fiction 658.05 ANN (Browse shelf(Opens below)) Available 47809

1 History and Evolution of Data Analytics 2 Data Mining and Analytics 3 Data Analytics Tools 4 Business Analytics and Intelligence 5 Customer Relationship Analytics, Cloud Computing, Blockchain, and Cognitive Computing 6 Cybersecurity and Data Analytics 7 Data Analytics and the Retail Industry 8 Data Analytics in the Financial Services Industry 9 Data Analytics in the Sports Industry 10 Data Analytics in the Accounting Industry 11 Data Analytics in the Medical Industry 12 Data Analytics in the Manufacturing Industry 13 Data Analytics in the Marketing Industry 14 Data Analytics in the Transportation Industry 15 Data Analytics in Education

Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results.

The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor’s manual are also provided as online supplements.

This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.

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