<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The global Business Intelligence (BI) market grew by 7.3% in 2016 according to the Gartner report (2017). Today, organizations require better use of data and analytics to support their business decisions. Internet power and business trend changes have provided a broad term for data analytics - Big Data. To be able to handle it and leverage a value of having access to Big Data, organizations have no other choice than to get proper systems implemented and working. However, traditional methods are not efficient for changing business needs. Long time between project start and go-live causes a gap between initial solution blueprint and actual user requirements at the end of the project. This article presents the latest market trends in BI systems implementation by comparing agile with traditional methods. It presents a case study provided in a large telecommunications company (350 BI users) and the results of a pilot research provided in the three large companies: media, digital, and insurance. Both studies prove that agile methods might be more effective in BI projects from an end-user perspective and give first results and added value in a much shorter time compared to a traditional approach. </p></abstract>

The global Business Intelligence (BI) market grew by 7.3% in 2016 according to the Gartner report (2017). Today, organizations require better use of data and analytics to support their business decisions. Internet power and business trend changes have provided a broad term for data analytics - Big Data. To be able to handle it and leverage a value of having access to Big Data, organizations have no other choice than to get proper systems implemented and working. However, traditional methods are not efficient for changing business needs. Long time between project start and go-live causes a gap between initial solution blueprint and actual user requirements at the end of the project. This article presents the latest market trends in BI systems implementation by comparing agile with traditional methods. It presents a case study provided in a large telecommunications company (350 BI users) and the results of a pilot research provided in the three large companies: media, digital, and insurance. Both studies prove that agile methods might be more effective in BI projects from an end-user perspective and give first results and added value in a much shorter time compared to a traditional approach.

Effectiveness of Agile Compared to Waterfall Implementation Methods in it Projects: Analysis Based on Business Intelligence Projects

Foundations of Management

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The global Business Intelligence (BI) market grew by 7.3% in 2016 according to the Gartner report (2017). Today, organizations require better use of data and...

Effectiveness of Agile Compared to Waterfall Implementation Methods in it Projects: Analysis Based on Business Intelligence Projects

Publié en ligne: 28 oct. 2017

Pages: 273 - 286

DOI: https://doi.org/10.1515/fman-2017-0021

Mots clés
agile, waterfall, business intelligence, analytics, big data, end-users requirements, sprint

© Faculty of Management, Warsaw University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Effectiveness of Agile Compared to Waterfall Implementation Methods in it Projects: Analysis Based on Business Intelligence Projects

Publié en ligne: 28 oct. 2017

Pages: 273 - 286

DOI: https://doi.org/10.1515/fman-2017-0021

Mots clésagile, waterfall, business intelligence, analytics, big data, end-users requirements, sprint

© Faculty of Management, Warsaw University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
agile, waterfall, business intelligence, analytics, big data, end-users requirements, sprint