Mainframe data is critical to enterprise-wide strategies

Ultra fast computers, or “big iron” has a critical role to play in big data analytics for enterprise-wide strategies

Mainframe enterprise

'The mainframe is no longer the isolated black box it once was, and more organisations are realising the immense benefits of performing analysis off the mainframe for real-time results'

Syncsort’s annual survey has uncovered four key 2017 trends that highlight the increasingly large role of mainframe application and log data in enterprise-wide business and operational intelligence strategies that leverage modern data architectures for big data analytics.

The study, which polled over 220 respondents from a wide range of IT disciplines including executives, architects, system programmers, application analysts, database administrators, operations managers and security professionals, identified four trends that reflect the vital role mainframe data plays in supporting business and operational intelligence initiatives.

1. Organisations will move mainframe application and log data to next-generation big data analytics platforms.

60% of respondents indicated that they plan to move mainframe data off-platform for analytics.

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A growing number of large organisations are now looking to leverage modern data architectures like Hadoop, Spark and Splunk to analyse mainframe application and log data at scale and at the speed of business.

2. Security and compliance mandates will be key drivers for technology evaluations and mainframe data analytics.

66% of respondents ranked the ability to do big data analytics for operations and/or security across the entire enterprise as important.

Mainframes host some of the most sensitive business and operations information for large enterprises.

For this reason, mainframe application and log data are also emerging as critical data sources for security and compliance initiatives, which were ranked as the top initiatives for IT executives and IT organisations.

3. Technologies that enhance and monitor data movement between platforms will rise in importance.

62% of respondents don’t feel they are able to effectively track data in motion.

Organisations are looking for tools to monitor data movement across a variety of platforms and let them know what data is being moved, by whom, when and where.

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4. Big data analytics for operational intelligence, security and compliance will continue to grow and emerge as a critical project in many organisations.

48.6% of respondents indicate it is desirable for their organisation to have access to log, SMF or other data on the mainframe for correlation with distributed data in big data and analytics platforms (Splunk, Hadoop, etc.).

This reflects an emerging trend in how z/OS operational data can be used on advanced analytics platforms to gain valuable business insights, driven by the limitations of the static nature of the display capabilities of existing mainframe tools.

The survey also confirmed mainframe’s continuing role as the predominant platform for performing large-scale transaction processing on mission-critical applications.

Given mainframe’s critical part in their IT strategy, many organisations (over a third in the study) are concerned over their ability to staff mainframe operations adequately as traditional mainframe experts retire.

For 2017, this means newer technologies that help address the diminishing pool of experienced mainframe talent and expertise will rise in importance.

>See also: 7 tricks to get millennials working on the mainframe

“Companies still rely on the mainframe to process their most important transactional data, but we’re seeing an increased focus on integrating this data within big data analytics platforms to provide a complete enterprise-wide view of data for intelligence on business-critical operations, security breaches and compliance audits,” said David Hodgson, General Manager of Syncsort’s Mainframe business.

“The mainframe is no longer the isolated black box it once was, and more organisations are realising the immense benefits of performing analysis off the mainframe for real-time results, while investing in solutions that simplify data movement between platforms to bring together key enterprise-wide business information.”

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