Data visualizations to support CIO's decision making : a case of API management at Techberry company | |
| Author | Acharya, Suhel |
| Call Number | AIT RSPR no.DSAI-22-05 |
| Subject(s) | Chief information officers--Decision making--Case studies Application program interfaces (Computer software) Information visualization |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Science in Data Science and Artificial Intelligence |
| Publisher | Asian Institute of Technology |
| Abstract | In recent years, the use of APIs in the development of an application has been increasing rapidly. Rapid development of APIs is conducted so that the application can be deployed into production quickly. While APIs are created in a rapid manner, monitoring and maintenance is not considered. This makes it difficult for all the parties involved in the use of those APIs. The consumer, the manager, and the developer. To solve this problem, certain actions should be taken while the APIs are being configured. In addition to this, a proper way of monitoring the APIs that have been deployed is neglected for the most parts. The main objective of this research study is to find a proper way of using the data to create visualizations in an APIM for a CIO of the company. Likewise, to achieve the main objective further studies which include understanding the roles and responsibilities of a CIO, understand which visualizations (components) are needed in a dashboard should be achieved. A prototype dashboard was designed in this research study which was presented to a CIO and their feedback was collected. This prototype was revamped according to the CIO’s feedback. The first version of the prototype dashboard was a rigid. In other words, in the first version, the applications were grouped together and shown together in a single component. It was suggested that the visualizations must be broken down into application levels as it will help the CIO to find the problem easily which has been done in the second version of the prototype dashboard. A four-step process has also been developed and included in this study to help prepare dashboards in a proper way. Similarly, Techberry’s Hyper Integration Tool, has been used to fetch the data and transport it to Elastic. Similarly, the ‘K’ from ELK Stack, Kibana, has been used to implement the prototype dashboard. In conclusion, the CIOs need a dashboard where the visualizations should have summary of each application. Doing this, the percentage of error, usage, or performance can be seen in a graph divided into all available applications where they can go into each one of them to dig-deep to solve any issue. |
| Year | 2022 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Data Science and Artificial Intelligence (DSAI) |
| Chairperson(s) | Chutiporn Anutariya |
| Examination Committee(s) | Vatcharaporn Esichaikul;Puttaporn Saengratanadej |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Research Studies Project Report (M. Sc.) - Asian Institute of Technology, 2022 |