Cloud Based Data Warehousing: Challenges and Criteria

In this digital age, organizations are doing their best to leverage their data for making valuable insights to gain competitive advantage. Cloud Computing has transformed the way organizations store, analyze, and manage their data as it removes the burden of building and maintaining the hardware and software infrastructure needed to manage the data. Moreover, the pay-as-you-go nature of the cloud makes it cost effective as organization pay only for the resources utilized; also, organizations benefit from the vast scalability of the cloud that enables the utilization of more resources at peak workloads. As a result, this research focuses on investigating the Cloud Based Data Warehouse solutions capabilities and challenges. We experiment using a prototypical implementation in the Google BigQuery platform. We propose criteria to evaluate cloud-based Data Warehouses consisting of the ETL process, Data Querying, Data Visualization, Security and Encryption, Access control, Audit logging, Backups, and Disaster Recovery. This research enables the exploration and testing of Cloud Data Warehouse solutions to explain how it can be adopted by organizations.