TY - JOUR
T1 - A review and future direction of agile, business intelligence, analytics and data science
AU - Larson, Deanne
AU - Chang, Victor
N1 - Publisher Copyright:
© 2016 Elsevier Ltd. All rights reserved.
PY - 2016/10/1
Y1 - 2016/10/1
N2 - Agile methodologies were introduced in 2001. Since this time, practitioners have applied Agile methodologies to many delivery disciplines. This article explores the application of Agile methodologies and principles to business intelligence delivery and how Agile has changed with the evolution of business intelligence. Business intelligence has evolved because the amount of data generated through the internet and smart devices has grown exponentially altering how organizations and individuals use information. The practice of business intelligence delivery with an Agile methodology has matured; however, business intelligence has evolved altering the use of Agile principles and practices. The Big Data phenomenon, the volume, variety, and velocity of data, has impacted business intelligence and the use of information. New trends such as fast analytics and data science have emerged as part of business intelligence. This paper addresses how Agile principles and practices have evolved with business intelligence, as well as its challenges and future directions.
AB - Agile methodologies were introduced in 2001. Since this time, practitioners have applied Agile methodologies to many delivery disciplines. This article explores the application of Agile methodologies and principles to business intelligence delivery and how Agile has changed with the evolution of business intelligence. Business intelligence has evolved because the amount of data generated through the internet and smart devices has grown exponentially altering how organizations and individuals use information. The practice of business intelligence delivery with an Agile methodology has matured; however, business intelligence has evolved altering the use of Agile principles and practices. The Big Data phenomenon, the volume, variety, and velocity of data, has impacted business intelligence and the use of information. New trends such as fast analytics and data science have emerged as part of business intelligence. This paper addresses how Agile principles and practices have evolved with business intelligence, as well as its challenges and future directions.
KW - Agile methodologies
KW - Analytics and big data
KW - Business intelligence (BI)
KW - Lifecycle for BI and Big Data
UR - http://www.scopus.com/inward/record.url?scp=84966326638&partnerID=8YFLogxK
U2 - 10.1016/j.ijinfomgt.2016.04.013
DO - 10.1016/j.ijinfomgt.2016.04.013
M3 - Article
AN - SCOPUS:84966326638
SN - 0268-4012
VL - 36
SP - 700
EP - 710
JO - International Journal of Information Management
JF - International Journal of Information Management
IS - 5
ER -