Book chapter
1 Citations
Peer Reviewed
Data Mining and Business Intelligence: A bibliometric analysis
Azevedo, Ana. Corresponding author: Azevedo, Ana
ISLA — Instituto Politécnico de Gestão e Tecnologia
Integration Challenges for Analytics, Business Intelligence, and Data Mining, 2021
Published by: IGI Global
Resume
Abstract
From the middle of this second decade of the 21st century, analytics has become commonly associated with the topics business intelligence and data mining. Data mining (DM) is being applied with success in business intelligence (BI) environments and several examples of applications can be found. BI and DM have different roots and, as a consequence, have significantly different characteristics. DM came up from scientific environments; thus, it is not business oriented. DM tools still demand heavy work in order to obtain the intended results. On the contrary, BI is rooted in industry and business. As a result, BI tools are user-friendly. This chapter reflects on these differences from a historical perspective. Starting with a separated historical perspective of each one, analytics, BI, and DM, the author then discusses how they converged when DM is used and integrated in BI environments with success.
Keywords
#Data mining
#Business intelligence
#data analytics
#Business analytics
#Analytics
#Data Science
#Perspective (graphical)
#Computer science
#Order (exchange)
#Work (physics)
Bibliographic Details
Publication Type
Book chapter
Publication Year
2021
Journal / Conference / Work
Integration Challenges for Analytics, Business Intelligence, and Data Mining
ISSN
2327-3275
ISBN
9781799857815
Publisher
IGI Global
Publication Status
Published