BIwTL

Rapidly leveraging information analytics technologies to mine the mounting information in structured and unstructured forms, derive business insights and improve decision making is becoming increasingly critical to today's business successes. One of the key enablers of the analytics technologies is an Information Warehouse Management System (IWMS) that processes different types and forms of information, builds, and maintains the information warehouse (IW) effectively. Although traditional multi-dimensional data warehousing techniques, coupled with the well-known ETL processes (Extract, Transform, Load) may meet some of the requirements in an IWMS, in general, they fall short on several major aspects: 1. They often lack comprehensive support for both structured and unstructured data processing; 2. they are database-centric and require detailed database and data warehouse knowledge to perform IWMS tasks, and hence they are tedious and time-consuming to operate and learn; 3. they are often inflexible and insufficient in coping with a wide variety of on-going IW maintenance tasks, such as adding new dimensions and handling regular and lengthy data updates with potential failures and errors.