Security Issues in Data Warehouse

Data Warehouse (DWH) provides storage for huge amounts of historical data from heterogeneous operational sources in the form of multidimensional views, thus supplying sensitive and useful information which help decision-makers to improve the organization’s business processes. A data warehouse environment must ensure that data collected and stored in one big repository are not vulnerable. A review of security approaches specifically for data warehouse environment and issues concerning each type of security approach have been provided in this paper

Security Issues in Data Warehouse: A Systematic Review

AbstractAs Data Warehouse store huge amount of data with the span of more than decades, the security of this huge information base is crucial for the sustainability and reliability of data warehouse. Since its advent the data warehouse has gone through various technological changes, which has prompted changes in the security strategies as well. This article, is taking a deep look at the various changes in the security mechanisms of the Data Warehouse, along with the changes in the strategies for the data warehouse development. It helps in understanding the various security aspects related to Data Warehouse, in coherence with the different methodologies employed for its development and functioning

A Dementia Care Mapping (DCM) data warehouse as a resource for improving the quality of dementia care. Exploring requirements for secondary use of DCM data using a user-driven approach and discussing their implications for a data warehouse

The secondary use of Dementia Care Mapping (DCM) data, if that data were held in a data warehouse, could contribute to global efforts in monitoring and improving dementia care quality. This qualitative study identifies requirements for the secondary use of DCM data within a data warehouse using a user-driven approach. The thesis critically analyses various technical methodologies and then argues the use and further demonstrates the applicability of a modified grounded theory as a user-driven methodology for a data warehouse. Interviews were conducted with 29 DCM researchers, trainers and practitioners in three phases. 19 interviews were face to face with the others on Skype and telephone with an average length of individual interview 45-60 minutes. The interview data was systematically analysed using open, axial and selective coding techniques and constant comparison methods. The study data highlighted benchmarking, mappers’ support and research as three perceived potential secondary uses of DCM data within a data warehouse. DCM researchers identified concerns regarding the quality and security of DCM data for secondary uses, which led to identifying the requirements for additional provenance, ethical and contextual data to be included in a warehouse alongside DCM data to meet requirements for secondary uses of this data for research. The study data was also used to extrapolate three main factors such as an individual mapper, the organization and an electronic data management that can influence the quality and availability of DCM data for secondary uses. The study makes further recommendations for designing a future DCM data warehouse