Business Intelligence Dashboard for Academic Program Management
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| Publicado en: | Association for Engineering Education - Engineering Library Division Papers (Jun 14, 2015), p. 26.312.1 |
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American Society for Engineering Education-ASEE
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| Acceso en línea: | Citation/Abstract Full text outside of ProQuest |
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|---|---|---|---|
| 001 | 2317750921 | ||
| 003 | UK-CbPIL | ||
| 024 | 7 | |a 10.18260/p.23651 |2 doi | |
| 035 | |a 2317750921 | ||
| 045 | 0 | |b d20150614 | |
| 100 | 1 | |a Wyne, Mudasser Fraz | |
| 245 | 1 | |a Business Intelligence Dashboard for Academic Program Management | |
| 260 | |b American Society for Engineering Education-ASEE |c Jun 14, 2015 | ||
| 513 | |a Conference Proceedings | ||
| 520 | 3 | |a Business Intelligence Dashboard for Academic Program ManagementAbstractIn higher education institutions, people managing academic program may require dataand an efficient analysis of the data in order to make well informed decisions regardingprogram and courses offerings, as well as, class staffing, etc.. Traditionally, it would taketoo much time and/or resources on manually gathering necessary data from varioussources for analysis. Implementing a business intelligence data dashboard could improveefficiency in data retrieval and can optimize data analysis for faculty programmanagement and decision making. The purpose of this paper is to present the research,design, and implementation of a business intelligence data dashboard prototype to meetsome of the main requirements for academic program management. The dashboardimplementation utilized database structure designed in Oracle and managed with SQLqueries to populate the data as well as retrieve data for the dashboard built with Tableau.The prototype data dashboard was successfully designed and implemented, usingdifferent types of graphs and tables, even though there were some moderate limitationson overall design due to data complexities. The dashboard shows cohort scheduling andstaffing using BS in Information System program data for over 7 years for over 60program cohorts. Specifically, the dashboard contains nine different tabs, that can befiltered using the drill down options on the Classes By Term, Section Details, InstructorsBy Program, and Instructor details by course. It also combines data that is used for coursescheduling and course evaluations, thus providing more information to the programdirector than any single query or report. By using ETL procedures, university data wasorganized and stored in a data mart using Oracle software that linked directly to Tableaufor dashboard design. With the creation of a data link between the database and theTableau dashboard, we enabled automatic data queries to be programmed for dashboardvisualizations. While most data visualizations used were standard, such as line charts andbar graphs. Users are able to navigate and interact within the Tableau dashboard by usingtheir mouse cursor on specific data metrics. By default, all data measures for requireditems are shown when the dashboard is initially opened. Utilizing different filtered viewsby adjusting date ranges or selecting by criteria allows for better views of the data in thedashboards. Other data visualizations are displayed as Pop-up tool tip windows whenusing the mouse cursor throughout certain parts of the graphs or charts which showadditional data metrics. Future work could focus on streamlining the data preparation andautomating the dashboard visualizations for even better efficiency in academic programmanagement. | |
| 653 | |a Data analysis | ||
| 653 | |a Dashboards | ||
| 653 | |a Decision analysis | ||
| 653 | |a Graphs | ||
| 653 | |a Mouse devices | ||
| 653 | |a Prototypes | ||
| 653 | |a Design | ||
| 653 | |a Business | ||
| 653 | |a Higher education institutions | ||
| 653 | |a Charts | ||
| 653 | |a Information management | ||
| 653 | |a Decision making | ||
| 653 | |a Data retrieval | ||
| 653 | |a Streamlining | ||
| 653 | |a Intelligence (information) | ||
| 653 | |a Colleges & universities | ||
| 653 | |a Databases | ||
| 653 | |a Higher education | ||
| 653 | |a Efficiency | ||
| 653 | |a Retrieval | ||
| 653 | |a College faculty | ||
| 653 | |a Staffing | ||
| 653 | |a Intelligence | ||
| 653 | |a Research design | ||
| 653 | |a Human-computer interaction | ||
| 653 | |a Competitive intelligence | ||
| 653 | |a Educational programs | ||
| 700 | 1 | |a Reeves, Jodi | |
| 700 | 1 | |a Montes, Frank Xavier | |
| 700 | 1 | |a Gurbach, Tom J | |
| 773 | 0 | |t Association for Engineering Education - Engineering Library Division Papers |g (Jun 14, 2015), p. 26.312.1 | |
| 786 | 0 | |d ProQuest |t Library Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2317750921/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u https://peer.asee.org/business-intelligence-dashboard-for-academic-program-management |