| | November 20168CIOReviewData Integration for Empowering Cloud-Based AnalyticsBy Jeffrey T. Pollock, VP-Product Management, Oracle [NYSE: ORCL]When a CIO is considering cloud as a platform there are many transformational opportunities for an IT organization to consider. One area in particular that is truly transformational is to shift the IT workload of business analytics to the cloud. However, most CIOs don't have the luxury of simple applications or greenfield analytics; instead, they may have 100's or 1000's of business applications and a very complex data architecture to worry about. It is no easy task to `lift and shift' to the Cloud. This is where data integration in the cloud can provide an enabling role in transforming the organization into a more responsive and lower-cost cloud business. Running analytics in the cloud may be as simple as operating a reporting tool from your cloud provider's infrastructure. Analytics on the cloud could also be far more powerful (and complex) by hosting an expansive big data environment for staging, transforming and auditing business data from the cloud. A wide variety of opportunities exist between these two extremes, but would typically involve doing some kind of reporting, data visualization, advanced statistical analytics (eg; machine learning) in support of a data mart, data warehouse or data lake that's hosted in the cloud. In practice, CIOs find that some of the most difficult aspects of enabling analytics in the cloud surround the data integration and data governance activities. The seemingly simple task of bringing the application data together and keeping track of it is made incredibly difficult by the breadth and complexity of existing application data flows that CIOs already watch out for in their on-premise infrastructure. Therefore, a comprehensive data integration cloud solution must be able to solve for three fundamental use cases:1. Migrating Data from Ground to Cloud ­ Without additional overhead, connect and migrate data continuously from existing application data sources into the cloud2. Integrating Data for Marts and Warehouses ­ Quickly load, ETL and govern data that is used for reporting and enterprise data warehouses3. Data Lifecycle for Big Data Lakes ­ Manage the complete lifecycle of data IN MY OPINIONJeffrey T. Pollock
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