Getinge North America
Precisely Connect allows Getinge North America users to query, report on and analyze real-time data, without impacting transaction response times
As a major health care and life sciences company, Getinge North America needs to leverage as much value as possible from its data. However, reporting and data analytics workloads can consume considerable processing power and overwhelm storage I/O channels.
Getinge needed a way to mine value from their data, without degrading operational response times.
No user wants to sit and wait for a response from an application, particularly when a customer is waiting for a transaction to be processed or when it is holding up the employee’s other work. Consequently, Getinge North America, a leading supplier of equipment and services for cleaning, disinfection and sterilization of medical instruments, always strives to maintain superior performance on its transaction processing systems.
This presents a challenge. Companies prosper most by accessing and analyzing their data to better understand business processes and customers’ behaviors, as well as identify any issues that might arise. However, because queries, reports and analytics access a lot of data very quickly, they can put a heavy strain on disk I/O channels, slowing down access for other applications. Furthermore, analytics typically requires considerable processing power, competing heavily with transactional applications for CPU resources if they share a single server.
Adding to that challenge, Getinge’s platform of choice for operational applications, Power Systems, IBM i and Db2 for i, was not the platform of choice for queries, reporting and analytics. Getinge prefers to use Windows-based servers running Microsoft SQL Server for that purpose. Getinge needed a way to allow users to query, report on and analyze realtime data, without negatively impacting transaction response times.
Precisely’s data replication solution, Connect helps Getinge to successfully meet these challenges. Connect allows organizations to replicate data in near real-time between most common hardware, operating system and database platforms, including from one type of platform to another.