Big Iron Plays Critical Role in Big Data Analytics, Operational Intelligence, Security and Compliance
Since the introduction of the IBM System/360 in the mid-1960s, “Big Iron” (aka mainframes) has played an important role in information processing in many global organizations. By the 1990’s client server technologies emerged and the proliferation of UNIX, Windows, and Linux servers exploded in many organizations. These platforms were perceived to be cheaper and easier to deploy and maintain, leading to many false predictions of the “death of the mainframe.” Fast forward to 2017 – the mainframe didn’t die, and IBM z Systems are still playing a significant, albeit evolving, role within most large organizations.
We recently completed our State of the Mainframe annual survey of IT professionals to take the mainframe pulse and determine the general health of mainframes within organizations. Respondents were from a wide range of IT disciplines including executives, architects, system programmers, application analysts, database administrators, operations managers, and security professionals.
Some results were expected, and some were a bit surprising.
- On the expected side: The IBM z/OS mainframe isn’t going away in the near term. (Maybe that’s still a shock to some open systems folks!) Big Iron’s z/OS mainframes are still the predominant platform for performing large-scale transaction processing on mission-critical applications – but organizations struggle to maintain mainframe expertise.
- On the surprising side: “Big Data” analytics for operational intelligence and to meet security & compliance requirements is on the rise for mainframes. As part of this analytics wave, organizations are focused on accessing and leveraging mainframe logs, SMF, and other z/OS information sources for correlation with data from open systems using analytics platforms such as Hadoop and Splunk. The mainframe is no longer the isolated “black box,” and its ability to integrate with distributed platforms, both for multi-platform application support and for enterprise-wide analytics, is key for many organizations.
4 Key Trends to Watch for in 2017
Four key trends in how organizations will be leveraging Big Iron data as a critical component of enterprise-wide business intelligence to support operational analytics as well as security and compliance initiatives reflect the vital role of mainframe data and the necessity for integrating it with distributed data within analytics platforms and technologies:
1. Organizations will move Big Iron 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. A growing number of large organizations are now looking to leverage modern data architectures like Hadoop, Spark and Splunk to analyze 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. Big Iron hosts 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 organizations.
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. Organizations 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.
4.Big Data analytics for operational intelligence, security and compliance will continue to grow and emerge as a critical project in many organizations.
48.6% of respondents indicate it is desirable for their organization 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 Big Iron’s 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.
For more information and details on our mainframe survey, read our eBook.