It’s the burning question for many companies reliant on enterprise systems: how do I extend my mainframe data to cloud, mobile and analytics applications?
And there’s no question they need to do this. The majority of core mission-critical workloads are still running on mainframes and that continues to grow. Most consumer and business transactions – banking via ATMs, credit card transactions, airline flights, etc. – are processed on mainframes. And mainframes ensure 24/7 support across police and fire departments, utilities, garbage collection, parks and hospitals.
Data integration is undergoing transformative change driven by key business and social drivers. Roughly 72 percent of all enterprises say the greatest value will come from analyzing transactional data and 55 percent of enterprise applications need mainframes to complete transactions. Customers and business demand real-time information, driven by the maturity and wide-spread adoption of business analytics, the growth of mobile technologies, and the need to manage and exploit Big Data. This requires streamlined integration with cloud for faster time-to-delivery for new business services.
But there are challenges to connecting these systems of record (mainframes) with systems of engagement (cloud, mobile, analytics). Data and transactions are still distributed across multiple operational systems where they originate. The growth and diversity of data sources are making it impossible to consolidate enterprise data into physical data warehouse. Bulk data movement adds complexity, cost, and latency. Data replication introduces the risk of data inconsistency and security breaches. And point-to-point data consumption has scalability issues, adds complexity, and is difficult to maintain and change in real time.
The answer largely lies in data virtualization, which enables data structures that were designed independently to be leveraged together, in real-time, without data movement. This effectively turns data into a service and hides the complexity of back-end data structures behind a standard information interface. This creates the ability to use a single tool to access data no matter where it is located, what system it runs on or what interface is required to access it. And it eliminates the need to create a data warehouse or data mart to deliver an integrated view of data.
The IBM Bluemix Secure Gateway service and Rocket Mainframe Data Service provide a solution, enabling enterprises to securely connect Bluemix apps to remote locations, either on premises or in the cloud. It provides secure connectivity and establishes a tunnel between the Bluemix organization and the remote location it connects to. And it can be configured to create a secure gateway by using the Bluemix user interface or an API package.
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