The insights that may be derived from mainframe knowledge symbolize an enormous alternative for companies. It may very well be a retail retailer trying to rework outdated processes and enhance the shopper expertise, or a healthcare community hoping to get a deal with on its safety posture with enhanced fraud detection.
Irrespective of the supposed consequence, organizations that perceive the potential of mainframe knowledge and actively acquire, analyze, and apply its insights at scale have a novel benefit. That benefit can instill confidence amongst decision-makers and leaders, guaranteeing they’re outfitted with the most effective real-time insights when trying to innovate.
For leaders trying to find methods to maximise the worth of their mainframe knowledge, quite a lot of advances in areas together with synthetic intelligence (AI), cloud computing, and data management will help make leveraging knowledge simpler. These instruments and applied sciences give knowledge and analytics leaders a strong means to enhance operations, enhance efficiencies, and rework experiences.
The trail to superior analytics runs by mainframe knowledge
The hype behind AI is nothing new, and it has proven loads of promise in its skill to rework operations end-to-end inside IT methods and improve buyer experiences. In a survey carried out by Rocket Software, respondents recognized a number of advantages that motivated them to pursue AI initiatives. These embrace enhancements to operational effectivity (56%), bolstering danger administration (53%), and elevating decision-making (51%). Of these high motivators, 85% of respondents stated they have been targeted on enterprise optimization, pushed by a need to spice up operational effectivity or enhance their danger administration. And total, 96% of respondents had one among these three elements 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 methods in some kind or one other to deal with huge quantities of transactional knowledge — lots of which have been round for many years. That historic context and big knowledge set make mainframe knowledge ripe for the selecting relating to AI and analytics — two issues that rely on knowledge to feed fashions and generate insights. When thought of inside the context of AI initiatives, 42% of surveyed leaders stated they thought of mainframe knowledge to be a viable possibility 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 know-how accomplice to help that transformation.
Constructing the appropriate 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 really using mainframe knowledge. Getting previous that hurdle is all about hanging the appropriate steadiness between leveraging knowledge whereas additionally guaranteeing its use is according to current insurance policies and tips. Attaining this requires a sturdy set of safety and compliance options to assist bridge the hole and allow constantly safe use of mainframe knowledge in broader AI efforts.
For instance, the appropriate knowledge integration options, like these within the Rocket® DataEdge suite, present a broad set of instruments to assist organizations guarantee all their knowledge could be simply accessed, managed, and interpreted whereas nonetheless adhering to essential laws like GDPR and HIPAA. Organizations must also embrace a complete content material administration answer, 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, nevertheless, 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 determine 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 knowledge — 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 rework the way in which companies leverage AI. However quite a lot of challenges stand in the way in which as organizations look to entry that knowledge securely and use it at scale. With the appropriate know-how options and a trusted accomplice, 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 ability of mainframe knowledge.
