loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock
Business Intelligence Process Model Revisited

Topics: Best Practices & Communities of Practice; Business Intelligence & CRM; Business Process Management; Impact Measurement of Knowledge Management; KM Strategies and Implementations ; Management and Organisational Issues in Information Systems; Studies, Metrics & Benchmarks; Tools and Technology for Knowledge Management

Authors: Pasi Hellsten and Jussi Myllärniemi

Affiliation: Information and Knowledge Management Unit in Faculty of Management and Business, Tampere University and Finland

Keyword(s): Business Intelligence, Business Intelligence Process Model, Decision-Making, Organizational Development.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Best Practices & Communities of Practice ; Business Intelligence ; Business Process Management ; Communities of Practice ; Computer-Supported Education ; e-Business ; Enterprise Engineering ; Enterprise Information Systems ; Impact Measurement of Knowledge Management ; KM Strategies and Implementations ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Learning/Teaching Methodologies and Assessment ; Society, e-Business and e-Government ; Software Engineering ; Studies, Metrics & Benchmarks ; Symbolic Systems ; Tools and Technology for Knowledge Management ; Web Information Systems and Technologies

Abstract: Today many organizations have come to value knowledge as a production factor. Thus, there is a constant need for getting the information in and sorted. Business intelligence (BI) is a process for systematic acquiring, analyzing, and disseminating data and information from various sources to gain understanding about the business’s environment. This is required for supporting decisions for achieving organization’s business objectives. Literature has introduced models for planning and executing BI. However, as business environments and technologies evolve in a rapid pace, are the models still applicable? Not all recent issues are taken into consideration in the previous models. BI is considered to be integrated into business processes, so the similar evolution is expected to take place. There are two studies investigating BI instigating this study, but there are still questions to be answered. Literature on different models and findings of these studies were combined to form a vision to better match reality. Various issues like users’ active involvement, real-time analysis and presentation, and social media resources were brought up. Practitioners can use the approach to assess their current state of BI activities or planning the organization of BI program. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.149.233.97

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Hellsten, P. and Myllärniemi, J. (2019). Business Intelligence Process Model Revisited. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KMIS; ISBN 978-989-758-382-7; ISSN 2184-3228, SciTePress, pages 341-348. DOI: 10.5220/0008354503410348

@conference{kmis19,
author={Pasi Hellsten. and Jussi Myllärniemi.},
title={Business Intelligence Process Model Revisited},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KMIS},
year={2019},
pages={341-348},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008354503410348},
isbn={978-989-758-382-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KMIS
TI - Business Intelligence Process Model Revisited
SN - 978-989-758-382-7
IS - 2184-3228
AU - Hellsten, P.
AU - Myllärniemi, J.
PY - 2019
SP - 341
EP - 348
DO - 10.5220/0008354503410348
PB - SciTePress