[Webinar] Protect Your Most Trusted Mainframe Data Across the World in an Age of Heightened Cyber-security

WATCH ON DEMAND

3 Important Trends IT & Business Leaders Should Pay Attention to in 2022

Gil Peleg

|

Jan 24, 2022

Companies achieve a major competitive edge when they can harness cloud-based analytics and apply them to mission-critical data from both systems of record and systems of engagement. That’s why enterprises are pushing hard to get high-value data into the cloud – using it in the cloud to energize business systems across the organization with the powerful insights that result.

Below, we look at 3 important trends that IT & Business leaders should pay attention to in 2022.

1) The importance of managing mainframe data in the cloud for the purposes of cyber resiliency will increase

With some 37 percent of companies reporting they were struck by ransomware attacks in 2020, IT security is top-of-mind for many organizations. The worsening cyber challenges are driving organizations to seek cloud-based, air-gapped solutions, so that they can have data that is well protected, and so they can quickly recover from attacks and even have the option of bare metal recovery if needed.

Immutable, object storage versions of your most important data and a bare metal “recovery-from-anywhere” option—things provided easily, cost-effectively, and reliably in the cloud—dramatically boosts corporate resiliency by ensuring that data used in systems of engagement and even systems of record, vulnerable to phishing attacks, malware, and even internal threat actors, have a further backup.

This fact, combined with a Gartner-identified trend to move substantial amounts of mainframe storage to the cloud, suggests that 2022 will see organizations embracing this even more than they already do.

IT leaders have already identified that having data in the cloud and at the ready, or at least easily movable to the cloud when needed, is a big competitive advantage. However, the challenge of moving massive amounts of legacy data to the cloud will present itself as a top issue for continued cloud adoption, one that must be addressed if organizations are to succeed in this crucial mission.

2) Adoption of more efficient data transformation technology adds more and more enterprise mainframe data to data lakes

Getting all relevant data into data lakes that feed cloud-based analytics applications has become a strategic priority for IT leaders. The problem is highly valuable data stored away in environments that require a little more effort to get at–such as the mainframe–often get left out.

A recent Information Age article, Data Storage & Data Lakes, noted, “If an organization excludes difficult-to-access legacy data stores, such as mainframes, as they build the data lake, there is a big missed opportunity.”

This kind of large-scale data movement from the mainframe into the cloud has traditionally used a painful ETL (extract, transform, load) process to transform mainframe formatted data into the open formats and then load it into the cloud.

But a new ELT (extract, load, transform) process extracts data from wherever it currently resides, loads it to cloud storage while still in mainframe form, and only then transforms it to the open formats required by cloud-based analytics applications.

ELT makes it significantly easier to get mainframe data into the cloud. Given the strategic importance of data lakes, we expect to see more and more IT leaders using ELT as an opportunity to execute on them fully.

3) Mainframe data backup, archive, and storage goes cloud

IT and business leaders are moving to cloud storage (either public or hybrid), prioritizing the need to make mission-critical data more accessible, and learning about new data transformation possibilities. Together, this means legacy mainframe storage is primed for massive disruption in 2022.

Tired of the cost, complexity, and limitations of VTL and tape, IT leaders are finding software-only cloud data management for mainframe provides an ideal alternative to siloing mainframe data away from cloud-based analytics.

Cloud data management for mainframe allows companies to implement cloud backup and DR directly from the mainframe to any cloud or on-premises storage system, consolidate multiple backup and tape management software products into a single solution, take advantage of cloud scalability and flexibility (such as tiered storage) for their mainframe data, and reduce costs in power, facilities, personnel, equipment and software maintenance. 

Conclusion

It’s been years in the making, and the global pandemic has acted as an accelerant, so now the big story of 2022 will be the rush to provide robust cloud connections for mainframes. Better data management and data movement options and the low-cost and instant availability of cloud have changed the IT equation.

Problems or challenges identified today can now be addressed today – immediately, in the cloud.  Leading cloud providers such as AWS and Microsoft Azure offer easy-on-and-easy-off operations.  Get the data to the cloud and preconfigured or easily customizable tools can begin to yield results rapidly. Or, simply put, your data in the cloud because it makes economic sense and thereby becomes safely air-gapped.

The cloud is here and it’s where data and analytics belong. The year ahead will prove the point.

About the author

Gil Peleg | CEO
Gil has over two decades of hands-on experience in mainframe system programming and data management, as well as a deep understanding of methods of operation, components, and diagnostic tools. Gil previously worked at IBM in the US and in Israel in mainframe storage development and data management practices as well as at Infinidat and XIV. He is the co-author of eight IBM Redbooks on z/OS implementation.

Stay up-to-date with Model9 news!

Related posts

Register for a Demo