Business intelligence and decision support systems: business applications in the modern information system era
-
A. Ilmudeen
Abstract
Today, the business intelligence and decision support systems are proven as a vital infrastructure for the ever-growing business organization. Business enterprises are ever more depending on data to respond to key operational and strategic operation of their customers, markets, and their stakeholders. The business intelligence has progressed as the volume of data created by the intelligent devices and the Internet have grown up exponentially. Nevertheless, without appropriate applications and systems in a position to analyze the increasing big data, the enterprises are encountering various complexities. This chapter discusses the applications, challenges, and conceptually designed architecture that includes skills requirement, mining techniques, technical, design elements in business intelligence, and decision support systems.
Abstract
Today, the business intelligence and decision support systems are proven as a vital infrastructure for the ever-growing business organization. Business enterprises are ever more depending on data to respond to key operational and strategic operation of their customers, markets, and their stakeholders. The business intelligence has progressed as the volume of data created by the intelligent devices and the Internet have grown up exponentially. Nevertheless, without appropriate applications and systems in a position to analyze the increasing big data, the enterprises are encountering various complexities. This chapter discusses the applications, challenges, and conceptually designed architecture that includes skills requirement, mining techniques, technical, design elements in business intelligence, and decision support systems.
Chapters in this book
- Frontmatter I
- Contents V
- Knowledge engineering for industrial expert systems 1
- Machine learning integrated blockchain model for Industry 4.0 smart applications 13
- Prototyping the expectancy disconfirmation theory model for quality service delivery in federal university libraries in Nigeria 26
- Design of chatbot using natural language processing 60
- Algorithm development based on an integrated approach for identifying cause and effect relationships between different factors 80
- Risk analysis and management in projects 96
- Assessing and managing risks in smart computing applications 122
- COVID-19 visualization and exploratory data analysis 145
- Business intelligence and decision support systems: business applications in the modern information system era 156
- Business intelligence implementation in different organizational setup evidence from reviewed literatures 173
- Conceptualization of a modern digital-driven health-care management information system (HMIS) 187
- Knowledge engine for a Hindi text-to-scene generation system 201
- Index 229
Chapters in this book
- Frontmatter I
- Contents V
- Knowledge engineering for industrial expert systems 1
- Machine learning integrated blockchain model for Industry 4.0 smart applications 13
- Prototyping the expectancy disconfirmation theory model for quality service delivery in federal university libraries in Nigeria 26
- Design of chatbot using natural language processing 60
- Algorithm development based on an integrated approach for identifying cause and effect relationships between different factors 80
- Risk analysis and management in projects 96
- Assessing and managing risks in smart computing applications 122
- COVID-19 visualization and exploratory data analysis 145
- Business intelligence and decision support systems: business applications in the modern information system era 156
- Business intelligence implementation in different organizational setup evidence from reviewed literatures 173
- Conceptualization of a modern digital-driven health-care management information system (HMIS) 187
- Knowledge engine for a Hindi text-to-scene generation system 201
- Index 229
