Applied Data Mining for Business and Ind
β Paolo Giudici, Silvia Figini
π Library
π
2009
π Wiley
π English
β¦ LIBER β¦
π
Data Analytics for Business: Foundations and Industry Applications
β Scribed by Fenio Annansingh, Joseph Bon Sesay
- Publisher
- Routledge
- Year
- 2022
- Tongue
- English
- Leaves
- 289
- Category
- Library
β¬ Acquire This Volume
No coin nor oath required. For personal study only.
β¦ Synopsis
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 instructorβs 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.
β¦ Table of Contents
Cover
Half Title
Title Page
Copyright Page
Table of Contents
List of figures
List of tables
Acknowledgements
1 History and Evolution ofΒ Data Analytics
2 Data Mining and Analytics
3 Data Analytics Tools
4 Business Analytics andΒ Intelligence
5 Customer Relationship Analytics, Cloud Computing, Blockchain, and Cognitive Computing
6 Cybersecurity and Data Analytics
7 Data Analytics and theΒ 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
Index
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