Authors:
Pedro Almeida
1
;
Le Gruenwald
2
and
Jorge Bernardino
3
Affiliations:
1
ISEC, Portugal
;
2
University of Oklahoma, United States
;
3
University of Coimbra, Portugal
Keyword(s):
Data Mining, Data Mining Tools, Open Source.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Data Management and Quality
;
Data Mining
;
Data Modeling and Visualization
;
Databases and Information Systems Integration
;
Datamining
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Information Quality
;
Knowledge-Based Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Symbolic Systems
Abstract:
Businesses are struggling to stay ahead of competition in a globalized economy where there are more and
stronger competitors. Managers are constantly looking for advantages that can generate benefits at low
costs. One way to have such advantage is using the data about customers, demographic data, purchase
history, customer behavior and preferences that can help to take better business decisions. Data Mining
addresses the challenges of collecting value inside data and the ways to put that value to use for virtually
any area of our lives, including business. In this paper, we address the interest of Data Mining for business
and analyze three popular Open Source Data Mining Tools – KNIME, Orange and RapidMiner – considered
as a good starting point for enterprises to begin exploring the power of Data Mining and its benefits.