Data warehousing has become a generic term that refers to any Business Intelligent System that involves standard and advanced reporting, Data Marts, and OLAP processing. In any event, such systems are primarily composed of three logistics components for implementation: data models, the data itself, and the access application.
IrisLogic has mastered the art of flexible modeling techniques to support decision support systems. The process consists of modeling data identified by reporting and processing needs, and mapping the data to source systems. For true OLAP applications multidimensional models using STAR or SNOWFLAKE schemas with dimensional hierarchies and multiple summaries of measures are done to suit the OLAP tool needs, while less complex schemas are deployed for non-OLAP requirements.
The processes of mapping, extracting, transforming, and loading data from various OLTP source systems has been always very challenging. The backstage automated process to monitor and control quality has always been a priority. Incremental refresh and special design and implementation considerations to handle large volumes of data are also very important. IrisLogic has developed and implemented techniques and standards to address these issues to ensure that high quality data are readily available.
This component refers to the front-end application or tool that accesses the data for reporting and analysis. IrisLogic has expertise in many of the industry standard OLAP and reporting toolsets including DSS Agent, Brio, Crystal Report, and Analysis.