• Corpus ID: 18992038

BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS, TECHNIQUES AND BENEFITS

@inproceedings{Ranjan2009BUSINESSIC,
  title={BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS, TECHNIQUES AND BENEFITS},
  author={Jayanthi Ranjan},
  year={2009}
}
For companies maintaining direct contact with large numbers of customers, however, a growing number channel-oriented applications (e.g. e-commerce support, call center support) create a new data management challenge: that is effective way of integrating enterprise applications in real time. To learn from the past and forecast the future, many companies are adopting Business Intelligence (BI) tools and systems. Companies have understood the importance of enforcing achievements of the goals… 

Figures and Tables from this paper

Business Intelligence: Concepts, Issues and Current Systems
TLDR
The term BI is discussed from different views, the concepts and ideas behind its applications and systems are presented, and more enlightening about the pros and cones of BI are given with a high focus on implementation challenges.
Business Intelligence Application in the Natural Gas Industry: A Company Case
TLDR
The aim of this study is to demonstrate the stages of business intelligence and information technology approaches in the natural gas sector and to evaluate and analyze their applicability.
Review on Business Intelligence (BI) Success Determinants in Project Implementation
TLDR
This paper compiles critical success factors or successful determinants required to make a business intelligence project deemed as successful, based on previous studies that have been used for business intelligence, data warehouse, executive information systems and decision support systems in other parts of the world.
Business Intelligence in a Nutshell
TLDR
This research paper explores the concepts of BI, data quality characteristics and data quality issues, types of BI tools and delivery mechanisms and the key features of BI architecture.
Business Intelligence Solutions for Decision-Making in Global Organizations
TLDR
Business intelligence solutions and techniques will be introduced, followed by explanation of the use of these systems in decision making processes within the context of global organizations.
DATA ANALYSIS AND ETL TOOLS IN BUSINESS INTELLIGENCE
TLDR
ETL (Extract, Transform, and Load) is a procedure of pulling out data from various data sources and processing them according to business calculations and transferring the reformed data into a data warehouse.
Business Intelligence for E-commerce: Survey and Research Directions
TLDR
A review of the literature, suggests new research directions, and proposes an architecture to combine e-commerce with business intelligence, which would enable the analysis of customers’ behavior, discovering purchasing patterns, and improve relationship management with customer.
Business Intelligence: Concepts, Components, Features, Extraction Transformation Loading Technology
TLDR
The paper explores the concept of BI, objective of BI system, its key components and features, and Extraction, Transformation, Loading (ETL) process.
Business Intelligence - Enabled Adaptive Enterprise Architecture
TLDR
This thesis utilizes insights from Business Intelligence and uses the User Requirements Notation (URN), which enables modeling of business processes and goals, to provide a framework that exploits links between business objectives and Information Systems.
A Five-Layered Business Intelligence Architecture
TLDR
A framework of BI architecture which consists of five layers: data source, ETL, data warehouse, end user, and metadata layers is proposed which are essential to ensure high data quality and smooth information flow in a BI system.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 42 REFERENCES
Techniques, Process, and Enterprise Solutions of Business Intelligence
TLDR
This article reviews the concept of Business Intelligence and provides a survey, from a comprehensive point of view, on the BI technical framework, process, and enterprise solutions.
Business intelligence systems: design and implementation strategies
  • G. Gangadharan, S. Swami
  • Business, Computer Science
    26th International Conference on Information Technology Interfaces, 2004.
  • 2004
TLDR
The life cycle comprising various phases in the development of a BI system is described, including the implementation issues of BI in an organization focusing on a case study.
Enhanced business intelligence - supporting business processes with real-time business analytics
TLDR
An architecture for enhanced business intelligence is suggested that aims to increase the value of business intelligence by reducing action time and interlinking business processes into decision making.
Beyond data warehousing: what's next in business intelligence?
TLDR
The aim of this paper is to encourage the research community to acknowledge the coming of a second era in BI, to propose a general architecture for BPM, and to lay the premises for investigating the most challenging of the related issues.
Support of Decision Making by Business Intelligence Tools
  • Milena Tvrdíková
  • Computer Science
    6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07)
  • 2007
TLDR
The attention is paid to the data warehouses and to a new tool in this field, to the operational data stores, which enable to get the data of first-rate quality.
Sense & response service architecture (SARESA): an approach towards a real-time business intelligence solution and its use for a fraud detection application
TLDR
This work proposes an event-driven IT infrastructure to operate BI applications which enable real-time analytics across corporate business processes, notifies the business of actionable recommendations or automatically triggers business operations, and effectively closing the gap between Business Intelligence systems and business processes.
Building Data Mining Applications for CRM
TLDR
This one-stop guide to choosing the right tools and technologies for a state-of-the-art data management strategy built on a Customer Relationship Management (CRM) framework helps you understand the principles of data warehousing and data mining systems and carefully spell out techniques for applying them so that your business gets the biggest pay-off possible.
Benefits of Ontologies in Real Time Data Access
TLDR
This paper highlights the importance of a data integration layer in a Business Intelligence system and the benefits that the use of an ontology as data description formalism and query interface, can bring to the system.
Process Innovation: Reengineering Work Through Information Technology
The business environment of the 1990s demands significant changes in the way we do business. Simply formulating strategy is no longer sufficient; we must also design the processes to implement it
A survey of data mining and knowledge discovery software tools
TLDR
An overview of common knowledge discovery tasks and approaches to solve these tasks is provided, and a feature classification scheme that can be used to study knowledge and data mining software is proposed.
...
1
2
3
4
5
...