Proposal of methodology for a data WareHousing process: Use case: Generation of indicators of academic productivity of a university)

The article describes the methodology developed for a data warehousing process developed in a Chilean University. The purpose of the process is to generate indicators of academic productivity. For this a methodology is elaborated integrating diverse approaches techniques and methodologies such as: specification of information requirements relational modeling combined development model of Kimball and Hefesto proposals process of extraction-transformation-load (ETL) with a validation phase of indicators and integrated and interactive visualizations for the multidimensional analysis of the indicators with the use of dashboards. In this process three elements incorporated that in the opinion of the development team favored the success and effectiveness of the development of the solution. Firstly how to specify key performance indicators (KPI) in detail through the development of a template based on those used to specify information requirements in a software process. Second to explain the incorporation of a validation phase of the KPI obtained in the ETL process based on SQL (Structured Query Language) and the comparison with the data of the operational systems. Also in this ETL process is established as necessary and sufficient the use of a temporary repository as an area for data integration through a relational database. Thirdly integrated visualizations configured with an On-Line Analytical Processing (OLAP) tool which interactively display the related indicators for the same activity under analysis. Because of this data warehousing process you get a business intelligence platform based on a DataMart model with two schemes one star and another snowflake. The first contains the indicators of teacher productivity and the second those of scientific productivity which satisfy the specifications of the KPI and defined in agreement with the end users.