Abstract: A services platform acts as an intermediary between an existing enterprise analytic environment, and one or more underlying cloud service providers. The platform provides enterprise “big data-as-a-service,” by which an enterprise can seamlessly and easily provision new capacity for processing its analytic workload, and migrate data sources (e.g., data warehouse marts, enterprise data warehouses, analytic sandboxes, and the like) to the cloud for processing. The platform provides end-to-end enterprise class manageability of enterprise data assets, from data collection, aggregation, movement, staging and processing, all while providing service levels, security, access and governance. The platform integrates directly but seamlessly into the enterprise analytic stack, and existing analytics applications work as normal. The platform provides a way for the enterprise to translate its workloads into clusters of compute resources that meet its service level requirements.

Abstract: A services platform acts as an intermediary between an existing enterprise analytic environment, and one or more underlying cloud service providers. The platform provides enterprise “big data-as-a-service,” by which an enterprise can seamlessly and easily provision new capacity for processing its analytic workload, and migrate data sources (e.g., data warehouse marts, enterprise data warehouses, analytic sandboxes, and the like) to the cloud for processing. The platform provides end-to-end enterprise class manageability of enterprise data assets, from data collection, aggregation, movement, staging and processing, all while providing service levels, security, access and governance. The platform integrates directly but seamlessly into the enterprise analytic stack, and existing analytics applications work as normal. The platform provides a way for the enterprise to translate its workloads into clusters of compute resources that meet its service level requirements.

Abstract: A services platform acts as an intermediary between an existing enterprise analytic environment, and one or more underlying cloud service providers. The platform provides enterprise “big data-as-a-service,” by which an enterprise can seamlessly and easily provision new capacity for processing its analytic workload, and migrate data sources (e.g., data warehouse marts, enterprise data warehouses, analytic sandboxes, and the like) to the cloud for processing. The platform provides end-to-end enterprise class manageability of enterprise data assets, from data collection, aggregation, movement, staging and processing, all while providing service levels, security, access and governance. The platform integrates directly but seamlessly into the enterprise analytic stack, and existing analytics applications work as normal. The platform provides a way for the enterprise to translate its workloads into clusters of compute resources that meet its service level requirements.

Abstract: A services platform acts as an intermediary between an existing enterprise analytic environment, and one or more underlying cloud service providers. The platform provides enterprise “big data-as-a-service,” by which an enterprise can seamlessly and easily provision new capacity for processing its analytic workload, and migrate data sources (e.g., data warehouse marts, enterprise data warehouses, analytic sandboxes, and the like) to the cloud for processing. The platform provides end-to-end enterprise class manageability of enterprise data assets, from data collection, aggregation, movement, staging and processing, all while providing service levels, security, access and governance. The platform integrates directly but seamlessly into the enterprise analytic stack, and existing analytics applications work as normal. The platform provides a way for the enterprise to translate its workloads into clusters of compute resources that meet its service level requirements.

Abstract: A services platform acts as an intermediary between an existing enterprise analytic environment, and one or more underlying cloud service providers. The platform provides enterprise “big data-as-a-service,” by which an enterprise can seamlessly and easily provision new capacity for processing its analytic workload, and migrate data sources (e.g., data warehouse marts, enterprise data warehouses, analytic sandboxes, and the like) to the cloud for processing. The platform provides end-to-end enterprise class manageability of enterprise data assets, from data collection, aggregation, movement, staging and processing, all while providing service levels, security, access and governance. The platform integrates directly but seamlessly into the enterprise analytic stack, and existing analytics applications work as normal. The platform provides a way for the enterprise to translate its workloads into clusters of compute resources that meet its service level requirements.

Abstract: Various embodiments of the invention provide solutions to facilitate the management and/or automation of various database tasks, in particular system tasks. Merely by way of example, some embodiments provide methods systems and/or software products that can facilitate automation of such tasks. In accordance with certain embodiments, a maintenance window may be defined. The maintenance window can provide an opportunity for system tasks (and/or other tasks, especially those that consume significant database resources) to execute without significantly impacting the usability of the database. In particular embodiments, a maintenance window may be defined to coincide with a period of relatively low user activity. In some cases, a maintenance window may be implemented in conjunction with a job scheduler and/or a resource manager.

Abstract: Various embodiments of the invention provide solutions to facilitate the management and/or automation of various database tasks, in particular system tasks. Merely by way of example, some embodiments provide methods systems and/or software products that can facilitate automation of such tasks. In accordance with certain embodiments, a maintenance window may be defined. The maintenance window can provide an opportunity for system tasks (and/or other tasks, especially those that consume significant database resources) to execute without significantly impacting the usability of the database. In particular embodiments, a maintenance window may be defined to coincide with a period of relatively low user activity. In some cases, a maintenance window may be implemented in conjunction with a job scheduler and/or a resource manager.