Optimizing the Management and Visualization of Veterinary Clinical Results Through Business Intelligence
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Abstract
Managing laboratory results is a critical aspect of veterinary clinical practice, since scattering information across individual files limits timely access and patient follow-up. This study aimed to optimize the management and visualization of laboratory results at a veterinary clinic through a prototype based on Business Intelligence (BI). The prototype was developed using the Kimball methodology, which involved identifying analytical requirements, designing a snowflake-schema dimensional model, implementing an Extract, Transform, Load (ETL) process with Python and Pentaho, storing the data in a Data Warehouse built in MySQL, and creating interactive dashboards in Power BI. The result was four dashboards that allow users to filter information by patient, type of test, indicators, and dates. The prototype was evaluated with five employees of the Petit’s veterinary clinic (Popayán, Colombia) using two performance indicators. Compared with the traditional manual search method, it showed an average improvement of 50.04% in query time (Time-on-Task) and 66.29% in the reduction of steps in the initial workflow (RPFI). It is concluded that incorporating Business Intelligence tools into the veterinary setting increases operational efficiency, facilitates access to clinical information, and supports decision-making, establishing it as a scalable alternative for modernizing data management in veterinary medicine.
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