Business intelligence architectural framework for internet service providers | |
| Author | Nuchjanee Intarat |
| Call Number | AIT Thesis no.IM-22-04 |
| Subject(s) | Business intelligence--Data processing Business intelligence--Evaluation Internet service providers |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Information Management |
| Publisher | Asian Institute of Technology |
| Abstract | Business intelligence (BI) improves data-driven decision-making. BI systems aggregate data from various sources and display a matrix. BI technologies need self service data visualization to let users’ access and understand data fast, even for flexible questions. ISPs must manage data silos and retain massive amounts of network data and usage data. When distinct departments are responsible for incomplete datasets, other departments don't know what data exists in their firm. Data silos often cause chaos of different data definitions and inconsistency. These obstacles slow cross functional BI data integration for enterprise-wide analytics. Most reviewed papers focus on system architecture or large data analytics, there is a gap for research contribution on the empirical study of BI and analytical system governance and architecture framework implementation on enterprise BI. This work aims to propose an architectural framework for BI in the ISPs, which also could be used as a guideline for the practitioners in other domains to achieve satisfied BI and analytics which provides effectively, efficiency, trustable, and sustainable to the business and IT infrastructure. First, analytical system architecture and data pipeline from previous works are summarized. Second, the potential solutions for coping with data silos are discussed. Third, several techniques for query speed improvement are investigated. Next, a flexible cross-functional architectural framework for BI in the ISP is developed to enable fast and flexible analysis, supporting different groups of users in the enterprise. Lastly, the BI prototype has been implemented on an ISP firm to evaluate the successes of the proposed framework. The result system reflects the importance of data integration automation with multiplatform architecture improves the centralized-BI and analytics system efficiency. Besides, collaboration between IT and businesspeople under enterprise’s data governance helps provide trusted data to users. |
| Year | 2022 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information Management (IM) |
| Chairperson(s) | Chutiporn Anutariya; |
| Examination Committee(s) | Vatcharaporn Esichaikul;Chaklam Silpasuwanchai; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2022 |