A Review on Data Warehouse Management

Data warehouse management is a crucial part of industry and business that have been adopted and put into practice with increased complexity of managing pools of data. The architectural layout of data warehousing is composed of a centralized warehouse from which views are generated for needy users. The convention in this case is that the warehouse receives an information injection from individual distributed databases which may as well be not related to the warehouse but hold the raw data needed to justify the existence of warehouse. However, data warehouse management is a relatively complex procedure that needs data updates from distributed databases. The complexity of this procedure relates to anomaly-prone informational transaction between the data source end and the materialized view end. This description supports the critical requirements of data warehouses which are accuracy and timeliness. This review dwells on the assessment of data warehouse literature to verify the dominant strategy employed in data warehouse management and the trade-offs involved. For this purpose various data warehouse management related articles were selected and carefully reviewed. The findings revealed a favor towards Immediate Incremental Management (IIM) of warehouse against Deferred Incremental Management (DIM). It is observed that system availability which constitutes accurate views and real-time updating was the base determining factor. Deferred Incremental Management has been the conventional way but with an increase in data volume that requires a gigabyte transaction rate that defines contemporary business and industry this updating mechanism is quite unsuitable and strips data warehouse management its contextual meaning