Agile BI � The Future of BI

Muntean, Mihaela; Surcel, Trăian

doi:10.12948/issn14531305/17.3.2013.10

Cited by 20 publications

(30 citation statements)

References 2 publications

(2 reference statements)

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“…The most popular Agile development methodologies for BI are Agile Data Warehousing, Extreme Scoping, and Scrum (Muntean & Surcel, 2013). Agile Data Warehousing and Extreme Scoping work well with BI if a data warehouse is involved.…”

Section: Agile and Business Intelligencementioning

confidence: 99%

“…Scrum, while not limited to BI, is the most popular Agile approach used in Agile software development and BI (Muntean & Surcel, 2013). The concepts of Scrum primarily used in the BI are the user story, sprint backlog, product backlog, the sprint, and the daily scrum.…”

Section: Agile and Business Intelligencementioning

confidence: 99%

“…Users are involved in all of the sprint steps. Daily meetings which are less than 15 minutes are held to review status (Muntean & Surcel, 2013). …”

Section: Agile and Business Intelligencementioning

confidence: 99%

“…The discovery, design, and development phases benefit from iterative cycles, stakeholder collaboration, small time-boxed increments, and co-located resources (Ambler & Lines, 2016;Hughes, 2013;Muntean & Surcel, 2013;Powell, 2014).…”

Section: Synthesis Of the Fast Analytics/data Science Lifecycle And Amentioning

confidence: 99%

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A review and future direction of agile, business intelligence, analytics and data science

Larson¹,

Chang

2016

International Journal of Information Management

331

184

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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.

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Section: Agile and Business Intelligencementioning

confidence: 99%

Section: Agile and Business Intelligencementioning

confidence: 99%

“…Users are involved in all of the sprint steps. Daily meetings which are less than 15 minutes are held to review status (Muntean & Surcel, 2013). …”

Section: Agile and Business Intelligencementioning

confidence: 99%

Section: Synthesis Of the Fast Analytics/data Science Lifecycle And Amentioning

confidence: 99%

See 2 more Smart Citations

A review and future direction of agile, business intelligence, analytics and data science

Larson¹,

Chang

2016

International Journal of Information Management

331

184

View full text Add to dashboard Cite

show abstract

“…A DSS is generally narrower in scope (initially only used by a few managers within an organization) than BI. Through the advancement of technology the applications of DSS and the access of users grew, expanding the usefulness of DSS and leading to further evolution into the realm of the more agile [23] BI systems. Research and case studies provide evidence that a well-designed and appropriate computerized decision support system can encourage fact-based decisions, improve decision quality, and improve the efficiency and effectiveness of decision processes.…”

Section: Methodsmentioning

confidence: 99%