Extract, Transform and Load (ETL) – Insurance companies store mountains of transactional data related to the processing of their policies and claims and financials. Typically this data has its source in multiple systems that are different in terms of their content, granularity, operating system platform and age. This operational data is also different in terms of its overall quality. While textual fields input without benefits of edits work for operational activity, they create challenges for analytical purposes.

In order for any BI initiative to be successful, the “single source of data” desired must be of impeccable quality. Its reliability, if questioned, can cause project failure. In order to achieve this elusive goal, Millbrook’s ETL process has been refined to maximize the success potential. Millbrook’s processes respect that each company will have different source systems and ETL challenges, but the processes bring with them an unparalleled experience with predominant vendors and with the intricacies of insurance data. This experience brings a rich knowledge that is built into our source ETL routines and activities.



Millbrook supports multiple ETL products and practices as is required by the industry, but has chosen its own standard tools (Data Integrator) where a customer expresses no preference. The ETL process is fully supported by meta data regarding methodology, profiling, transformation, data cleansing and data load.