IBM z14

New IBM z14 Supports Machine Learning Everywhere

In more ways than one, IBM’s Z mainframe resembles Doctor Who’s Tardis in being “bigger on the inside than it is on the outside.” That isn’t mere rhetoric. Along with a physical presence that tends to make even the most robust 42U enterprise systems look somewhat puny is the “virtual scale” the IBM Z’s massive physical memory storage capacities and its equally impressive transactional capabilities.

Size, however, isn’t everything. The continuing vitality of the mainframe also reflects IBM’s ability to fundamentally reinvent and reinvigorate the Z system and customer experience. Just as it has since the first mainframe solutions were launched over fifty years ago, those same qualities imbue the newest z14 offerings announced this week. Those include acting as a trusted, secure, continuously intelligent repository of a business’ information heart and soul.

That point gains even more weight when you consider the critical role the z14 will play in supporting customers’ advanced analytics initiatives and machine learning processes.

Secure data and you secure the business

Why does mainframe remain the platform for thousands of global enterprises? For three specific reasons. First is its cost-effective pervasiveness. According to IBM, Z mainframes handle over two thirds (68 percent) of the world’s production workloads but account for just 6 percent of total IT costs.

Second is its impressive, reliable transaction capabilities, which make it the system of choice for global banks, the world’s largest insurers, three-fourths of the market’s biggest retailers and 90 percent of the world’s airlines. How impressive? IBM Z solutions support over 30B business transactions per day, 87 percent of all credit card charges (totaling some $8T per year), $5B a day in ATM visits (and 29B ATM transactions annually) and 4B airline passenger bookings per year.

Third, due to its success and longevity, IBM Z mainframes support an estimated 80 percent of all current and historical global enterprise data. That’s an impressive number, but since that information resides behind enterprise firewalls on private infrastructures it is also more or less unsearchable by conventional means.

The journey to machine learning everywhere

That point opens opportunities for the IBM z14 to provide customers dramatic new insights. Why is that the case? Strategically, many or even most analytics efforts compare/contrast current events with relevant historical data. By doing so, organizations can detect longer term trends and pinpoint anomalous occurrences or behavior.

For example, in healthcare scenarios advanced analytics can be used to monitor the condition of patient groups or specific individuals, and alert caregivers to cases where caution or intervention might be wise. Similarly, a financial institution might leverage analytics to gauge customers’ financial health and determine whether those seeking loans are risk-worthy.

Similarly, insurance companies could use such tools to vet policy holders, watch out for and gain insight into anomalies, and head off potentially fraudulent claims. Analytics can also benefit numerous IT scenarios, from monitoring and managing systems to analyzing IT infrastructures and enhancing operational performance.

All good stuff but practical issues sometimes delay or even subvert analytics efforts. For instance, standalone big data appliances and solutions typically require the data being analyzed to be transferred and loaded into the system. That can be a time-consuming and costly, and potentially exposes a client’s data to theft and other security threats.

How does the new IBM z14 address these issues? By serving as both a trusted repository of an organization’s information assets and its core computing platform. Rather than moving data to a specialized analytics engine, the z14’s innovative advanced analytics and machine learning capabilities can be leveraged across both information at rest in the system and live transactional data as it arrives.

IBM is also working to ensure that these analytics capabilities are available to interested individuals and groups across the business. One example; the company’s Machine Learning for z/OS can perform federated analytics across a variety of structured and non-structured data from both Z and non-Z sources. The z14 supports all the steps in the full machine-learning lifecycle and can also be managed by anyone, anywhere with a single dashboard UI.

The single-dashboard also underscores IBM’s efforts to open machine learning and analytics to new stakeholders, including security and compliance officers, database administrators, enterprise architects and systems administrators. In turn, they can use machine learning to gain new insights and speed decision-making in key business processes and use cases.

Final analysis

IBM has added key improvements over previous generation z13 systems that impacts the z14’s machine learning and advanced analytics performance. Those include its tripling of memory resources (to 32TB), 3X faster I/O and accelerated transaction processing, and a halving of application response time. In fact, these points provide the well-defined technical muscle beneath the z14’s go-to-market strategy.

But the broader point behind IBM’s z14 efforts is to transform the ways that organizations think about and use their data assets and investments. Often that regard is all too passive, especially when advanced analytics and big data technologies are available to open up myriad benefits and possibilities residing in customers’ business information.

However, the cost and complexity of dedicated analytics solutions can be sizable stumbling blocks for many interested parties. Reducing or eliminating those barriers has long been a key goal for IBM, as can be seen in many of the company’s strategies and initiatives. That includes the z14 which demonstrates how IBM is bringing its vision to life for enterprise customers via the market’s most powerful, reliable and secure transactional solution.

Through its “machine learning everywhere” initiative, IBM is essentially democratizing the access to and analysis of critical business information, thus helping to ensure that customers get the full benefit of their z14 investments. But at its heart, supporting “machine learning everywhere” really translates into providing intelligence access for everyone.

Is it any wonder that, three years after its 50th anniversary, IBM’s Z mainframe continues to be golden?

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