TY - GEN
T1 - Business Intelligence, Based on the Ralph Kimball Methodology, for Decision-Making in General Management
AU - Aguilar-Chávez, Alexander
AU - Banda-Barrientos, Jeshuá
AU - Cabanillas-Carbonell, Michael
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Today's organizational world is faced with large amounts of data that is not being used properly. As a result, some information is ignored, making it difficult to make effective business decisions and optimal analysis for good strategic planning. This paper shows the development of a business intelligence tool that uses Ralph Kimball's methodology for decision making and determines the influence he has on decision making. Using the experimental design, the sample consists of 30 decision-making processes (experimental group) for pre-test and post-test. The results show an 82.10% reduction in time, a 23.57% increase in reliability, a 59.19% reduction in losses, and a 17.93% increase in accuracy rating compared to at the post-test, applied to the experimental group.
AB - Today's organizational world is faced with large amounts of data that is not being used properly. As a result, some information is ignored, making it difficult to make effective business decisions and optimal analysis for good strategic planning. This paper shows the development of a business intelligence tool that uses Ralph Kimball's methodology for decision making and determines the influence he has on decision making. Using the experimental design, the sample consists of 30 decision-making processes (experimental group) for pre-test and post-test. The results show an 82.10% reduction in time, a 23.57% increase in reliability, a 59.19% reduction in losses, and a 17.93% increase in accuracy rating compared to at the post-test, applied to the experimental group.
KW - Business Intelligence
KW - Decision Making
KW - ETL
KW - Ralph Kimball Methodology
KW - Reports
UR - https://www.scopus.com/pages/publications/85129437518
U2 - 10.1109/ISKE54062.2021.9755430
DO - 10.1109/ISKE54062.2021.9755430
M3 - Conference contribution
AN - SCOPUS:85129437518
T3 - 2021 IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021
SP - 643
EP - 646
BT - 2021 IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021
T2 - 16th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021
Y2 - 26 November 2021 through 28 November 2021
ER -