Improving the Data Management: ETL Implementation on Data Warehouse at Indonesian Vehicle Insurance Industry

Abstract

Unknowingly, risk is an essential part of an individual's life. Every day individuals have the potential to be threatened by possibilities that can produce something that has fatal social, human, and financial consequences. Insurance can help individuals to relieve the financial burden caused by unwanted things by transferring individual losses to insurance companies. This transfer of losses will distinguish individuals from possible bankruptcy and financial security. Automotive insurance is a liability for loss or damage to motorized vehicles. This time we will take the example of an insurance company specializing in automotive insurance, namely Top Gear Insurance (TGI). This company uses customer data storage using an ordinary manual database that does not yet use a data warehouse system. This ordinary manual database makes it difficult for TGI to retrieve data for reprocessing and makes data inaccessible from anywhere, asynchronous, concise, and inefficient. There is a solution to the TGI problem of creating a data warehouse with a star schema approach for storing and processing data. The data warehouse is likely to make the data within the company more accessible, efficient, simple, and understandable so that TGI can develop its business through data analysis from the data it already has. Datawarehouse has many business advantages, such as increasing Business Intelligence, data quality and consistency, saving time, and supporting historical data analysis and queries. The data warehouse consists of datamart, OLTP, OLAP, and Star Schema. Using Mondrian as a visualization showed that TGI can get information about customer data, policies, and claims easily, quickly, and concisely. That can also help TGI create customer profiles and targeted marketing and company evaluation based on the visualization provided.