The insights that may be derived from mainframe knowledge signify an enormous alternative for companies. It may very well be a retail retailer trying to rework outdated processes and enhance the client expertise, or a healthcare community hoping to get a deal with on its safety posture with enhanced fraud detection.

Regardless of the meant end result, organizations that perceive the potential of mainframe knowledge and actively gather, analyze, and apply its insights at scale have a singular benefit. That benefit can instill confidence amongst decision-makers and leaders, guaranteeing they’re geared up with the most effective real-time insights when trying to innovate.

For leaders looking for methods to maximise the worth of their mainframe knowledge, quite a few advances in areas together with synthetic intelligence (AI), cloud computing, and data management  can assist make leveraging knowledge simpler. These instruments and applied sciences give knowledge and analytics leaders a robust means to enhance operations, increase efficiencies, and remodel experiences.  

The trail to superior analytics runs by way of mainframe knowledge

The hype behind AI is nothing new, and it has proven loads of promise in its capability to rework operations end-to-end inside IT programs and improve buyer experiences. In a survey performed by Rocket Software, respondents recognized a number of advantages that motivated them to pursue AI initiatives. These embrace enhancements to operational effectivity (56%), bolstering threat administration (53%), and elevating decision-making (51%). Of these high motivators, 85% of respondents stated they had been centered on enterprise optimization, pushed by a need to spice up operational effectivity or enhance their threat administration. And general, 96% of respondents had considered one of these three components of their high three motivations for investing in AI.

However earlier than companies can reap the advantages of AI investments, they should guarantee they’ve entry to dependable, correct, and well timed knowledge. That is the place mainframe knowledge, an often-under-leveraged useful resource, comes into play. A majority of organizations have relied on mainframe programs in some kind or one other to deal with huge quantities of transactional knowledge — a lot of which have been round for many years. That historic context and big knowledge set make mainframe knowledge ripe for the choosing in the case of AI and analytics — two issues that rely on knowledge to feed fashions and generate insights. When thought-about throughout the context of AI initiatives, 42% of surveyed leaders stated they thought-about mainframe knowledge to be a viable choice for enriching insights.

So, what about placing mainframe knowledge into follow? These leaders recognized the power to construct out new analytical capabilities as the highest use case for this knowledge. However efficiently constructing these new capabilities and producing new alternatives means having an efficient modernization technique, in addition to an skilled expertise associate to help that transformation.

Constructing the correct technique to maximise mainframe knowledge

Rocket Software program’s survey discovered 56% of decision-makers recognized safety, compliance, and knowledge privateness as a high impediment to truly using mainframe knowledge. Getting previous that hurdle is all about hanging the correct steadiness between leveraging knowledge whereas additionally guaranteeing its use is consistent with present insurance policies and pointers. Attaining this requires a sturdy set of safety and compliance options to assist bridge the hole and allow persistently safe use of mainframe knowledge in broader AI efforts.

For instance, the correct knowledge integration options, like these within the Rocket® DataEdge suite, present a broad set of instruments to assist organizations guarantee all their knowledge might be simply accessed, managed, and interpreted whereas nonetheless adhering to essential laws like GDPR and HIPAA. Organizations also needs to embrace a complete content material administration resolution, like Rocket Mobius, as a part of their portfolio to ship stronger knowledge governance.

Past safety, an efficient technique additionally wants to make sure that a corporation’s knowledge pipelines and the processes that exist throughout the mainframe and different infrastructures are simply scalable. Scalability, nonetheless, has confirmed to be a ache level for a lot of leaders. Of these surveyed by Rocket Software program, almost a 3rd (31%) recognized scalability as a difficulty. As organizations look to ascertain methods that embrace mainframe knowledge, they should incorporate options that assist faucet into the most effective of each cloud environments and the mainframe, like Rocket Software program’s Hybrid Cloud Data Suite. Doing so provides organizations the power to create a simplified view of information — structured and unstructured — spanning on-premises infrastructure and the cloud.

Mainframe knowledge is stuffed with alternative for development, new alternatives, and extra impactful AI and analytics. Correctly leveraging mainframe knowledge brings forth deeper analytical insights that may remodel the way in which companies leverage AI. However quite a few challenges stand in the way in which as organizations look to entry that knowledge securely and use it at scale. With the correct expertise options and a trusted associate, leaders can convey mainframe knowledge to their modernization technique, enhance operations, and successfully leverage AI and superior analytics.

Learn more about how your group can faucet into the facility of mainframe knowledge.