Performance analysis of sanitation indicators using data science
Sanitation indicators, SNIS, data science, data analysis
Basic sanitation companies keep important information about consumer behavior and service provision in Georeferenced Information Systems - GIS. These databases, if well explored, can show patterns of service provision that can contribute to decision-making in a concise and assertive manner. The indicators monitored by the SNIS have information gaps, since some companies fail to provide important data and there is still the generalization of some indicators due to the impossibility of monitoring important information. This research aims to seek efficiency improvements in the use of sanitation indicators from the information available in the information databases of sanitation companies, using data science to perform the exploration of information databases, evaluating ignored patterns that can be useful for the day to day of the companies. The research also aims to evaluate the sanitation indicators used today, in order to identify whether or not they are being underutilized and whether or not they make use of data that are actually relevant for the identification of results. Open programming languages will be used for data analysis and it is hoped to obtain information that can be useful for improving sanitation indicators.