IBM Safer Payments recognized as ”Fraud detection and prevention product of the year”

On its 25th anniversary, Risk.net Asia recognized IBM Safer Payments as “Fraud detection and prevention product of the year.” This recognition is a testament to the IBM RegTech team’s commitment to bringing next generation risk and compliance solutions to serve clients across the globe and also to meeting geo-specific industry and business needs. IBM Safer Payments won this award specifically for bringing agility to fraud fighting and for its differentiated capabilities. The solution is also well positioned to serve clients in Asia as the region gears up for disruptions from the proliferation of faster payments and the emergence of challenger banks.

Bringing agility to fraud fighting

Fighting financial crimes and fraud has never been easy. The acceleration of digital transformation and economic uncertainty resulting from the pandemic have added more pressure on fraud management. This calls for more agile fraud management approaches.

◉ IBM Safer Payments enables fraud management teams to use any data science, any machine learning, and artificial intelligence technique – proprietary or open source – to outsmart fraudsters.

◉ The platform supports bring-your-own-model options where users can build externally and then import neural networks, random forests, decision trees, and regressions, using their preferred tools.

◉ Models of different types can be combined into ensembles, to leverage the best of each modeling capability

◉ In addition, Safer Payments includes embedded training facilities for popular machine learning algorithms.

◉ Everything in Safer Payments is user-configurable and allows for adaptation to customer data model and ultra-fast configuration of new data feeds.

This unparalleled flexibility offered by IBM Safer Payments enables fraud management teams to keep pace with new fraud schemes and mount defenses well in advance.

 A truly differentiated fraud platform

Furthermore, IBM Safer Payments does not a necessitate ‘rip and replace’ approach. The solution can integrate with and augment existing fraud detection solutions without impacting operational efficiency. The solution also:

◉ Enables fraud analysts to update models on the fly with little or no vendor dependencies,

◉ Applies machine learning to not just train models, but also to discover new rules that fraud analysts can quickly test and integrate into the current fraud detection engine,

◉ Is proven to reduce false positive ratio down to the range 1:1 to 1:3.

Upholding customer experience in Asia Pacific and across the globe

More than ever, customers demand superior seamless and frictionless experience in their digital interactions. User-centered design in customer experience can be competitive advantage. Successful organizations leverage technology to deliver the highest levels of customer experience and service. For instance, IBM recently announced that digital bank Volt Bank has integrated IBM Safer Payments solution into its online banking platform. This helps Volt give their clients a more seamless and secure banking experience across the company’s entire platform.

Financial services technology leader FIS, looking for real-time decisioning and increased flexibility, chose IBM Safer Payments to help clients counter person-to-person payments fraud in the U.S. 

And Bank of New Zealand announced previously that they selected IBM Safer Payments to deliver cross-channel fraud protection to its customers. The deal supports BNZ’s efforts to provide frictionless and safer payments experience to their customers.

Join the data science revolution

IBM Safer Payments enables your fraud prevention teams to adapt their controls faster to emerging threats and detect fraud with greater speed and accuracy — and without vendor or data scientist dependencies. As part of the IBM RegTech risk and compliance solutions, Safer Payments has the analytics and simulation tools needed to continuously monitor business performance and adapt the decision model to emerging and modified fraud patterns.

Because it has an open platform, customers can leverage their existing detection models and IP all at a low total cost of operation (TCO), as all required components are self-contained and run on commodity hardware.

Source: ibm.com

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Urban Institute and IBM help cities measure gentrification

Cities across the United States are increasingly seeing their local communities impacted because of widespread neighborhood change due to blight or to adverse effects of gentrification. While gentrification can often increase the economic value of a neighborhood, the potential threat it poses to local culture, affordability, and demographics has created significant and time-sensitive concerns for city governments across the country. Many attempts to measure neighborhood change up until now have been backwards-looking and rules-based, which can lead governments and community groups to make decisions based on inaccurate and out-of-date information. That’s why IBM partnered with the Washington D.C.-based nonprofit research organization Urban Institute, which for more than 50 years has led an impressive range of research efforts spanning social, racial, economic and climate issues at the federal, state, and local level.

Measuring neighborhood change as or before it occurs is critical for enabling timely policy action to prevent displacement in gentrifying communities, mitigating depopulation and community decline, and encouraging inclusive growth. The Urban Institute team recognized that many previous efforts to measure neighborhood change relied on nationwide administrative datasets, such as the decennial census or American Community Survey (ACS), which are published at considerable time lags. For that reason, the analysis could only be performed after the change happens, and displacement or blight has already occurred. Last year, the Urban Institute worked with experts in the US Department of Housing and Urban Development’s (HUD) Office of Policy Development and Research on a pilot project to assess whether they could use novel real-time HUD USPS address vacancy and Housing Choice Voucher (HCV) data with machine learning methods to accurately now-cast neighborhood change.

Together, the IBM Data Science and AI Elite and Urban Institute team built on that pilot to develop a new method for predicting local neighborhood change from the latest data across multiple sources, using AI. This new approach began by defining four types of neighborhood change: gentrifying, declining, inclusively growing, and unchanging. IBM and Urban Institute then leveraged data from the US Census, Zillow, and the Housing Choice Voucher program to train individual models across eight different metropolitan core based statistical areas, using model explainability techniques to describe the driving factors for gentrification.

The IBM Data Science and AI Elite team is dedicated to empowering organizations with skills, methods, and tools needed to embrace AI adoption. Their support enabled the teams to surface insights from housing and demographic changes across several metropolitan areas in a collaborative environment, speeding up future analyses in different geographies. The new approach demonstrated a marked improvement over the precision of older rules-based techniques  (from 61% to 74%) as well as the accuracy (from 71% to 74%). The results suggest a strong future for the application of data to improving urban development strategies.

The partnership put an emphasis on developing tools that enabled collaborative work and asset production, so that policymakers and community organizations could leverage the resulting approaches and tailor them to their own communities.

IBM Cloud Pak® for Data as a Service was used to easily share assets, such as Jupyter notebooks, between the IBM and Urban Institute teams. During the engagement with Urban Institute, the teams leveraged AutoAI capabilities in Watson Studio to rapidly establish model performance baselines before moving on to more sophisticated approaches. This capability is especially valuable for smaller data science teams looking to automatically build model pipelines and quickly iterate through feasible models and feature selection, which are highly time-consuming tasks in a typical machine learning lifecycle.

Together, this engagement and collaboration aims to empower the field to use publicly available data to provide a near real-time assessment of communities across the country. In addition to providing insights on existing data, the project can help uncover shortcomings in available data, enabling future field studies to fill the gaps more efficiently.

For more details on the results, check out our assets which provide an overview of how the different pieces fit together and how to use them. And if you want to dig deeper into the methods, read our white paper.

IBM is committed to advancing tech-for-good efforts, dedicating IBM tools and skills to work on the toughest societal challenges. IBM is pleased to showcase a powerful example of how social sector organizations can harness the power of data and AI to address society’s most critical challenges and create impact for global communities at scale. IBM’s Data and AI team will continue to help nonprofit organizations accelerate their mission and impact by applying data science and machine learning approaches to social impact use cases.

Interested in learning more? Discover how other organizations are using IBM Cloud Pak for Data to drive impact in their business and the world.

Source: ibm.com

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Why QIIB trusts IBM Safer Payments for cross-channel fraud prevention

Fraud prevention is about who you can trust. For financial institutions like Qatar International Islamic Bank (QIIB), it’s about understanding the relative risk of a customer, a merchant and/or a transaction, as well as hundreds of different factors including location, amount, device, etc.

But for customers, both actual fraud attacks as well as incorrectly blocked legitimate transactions represent a breach of that trust. In the former instance, the customer trusted the institution to protect them from such attacks, and the fraud took place anyway. Luckily, most jurisdictions have regulations in place to make a customer whole after such an event. But in the latter case, there is an erosion of trust as well.

When a bank or payment processor blocks a legitimate transaction, it creates doubt in the customer that the organization can be counted on to complete their payment. Why would you choose a financial provider that may or may not be able to execute your transaction? In addition to losing share of wallet, the customer may begin to ask, “Why would I bank with a financial institution that doesn’t even know me?”

Why QIIB trusted IBM Safer Payments

QIIB is one of the Qatar’s leading banks, recently selected IBM to deliver cross-channel fraud prevention to its customers. This supports QIIB’s aim to provide its customers the ability to bank securely while delivering an innovative and positive customer experience.

Many conveniences that customers enjoy with today’s modern banking services carry an increased risk of fraud. Legacy fraud prevention systems were designed to see and stop easily recognizable fraud patterns. However today’s anytime, anywhere banking online and on mobile devices has made fraud detection much more challenging. Banks’ time to respond is also shrinking as real-time payments mean there are just milliseconds to detect and prevent theft before it’s too late.

QIIB understands the importance of providing solutions that meet its customers’ expectations for convenience while also ensuring that state-of-the-art security is in place, capable of withstanding increasingly sophisticated cyber-attacks and large-scale fraud breaches.

To do so, QIIB selected IBM Safer Payments, an advanced fraud payment prevention solution that allows banks to intercept fraudulent activity before it happens, while ensuring customers’ genuine transactions are not stopped in error. IBM Safer Payments uses artificial intelligence and machine learning to analyze behavior and fraudulent patterns. It then builds and adapts predictive models of emerging fraud threats and recommends countermeasure responses.

“QIIB was built on three pillars: trust, family and commitment. Protecting our customers’ trust in us, is key to our success and we put security front and center, so they can be sure their money and personal information is well-protected. With IBM Safer Payments, we are stepping up this protection, analyzing every transaction in real-time, but without sacrificing the customer experience,” said Dr. Abdulbasit Al Shaibei, CEO of QIIB.

Understanding the whole customer

IBM Safer Payments uses both financial and non-financial data together with a customer’s transaction history, to perform rigorous authentication and profiling every transaction. Fraudulent transactions are quickly identified – allowing them to be stopped, or put on hold pending further validation.

“IBM Safer Payments is also PCI PA-DSS certified,” notes Dr. Hesham Mohameden, Chief Information Security Officer. “This implies that the highest standard of data security and data consistence of the payment industry are maintained and ensures that all development and quality assurance processes are in line with the highest standards as well.”

“Facilitating safe, secure and fast transactions while eliminating friction through technological advancements is at the core of what we strive to offer our customers,” said Mohamed Elsir Haguo, the Head of the Fraud Management Department. “IBM Safer Payments delivers efficiencies and speed in identifying fraudulent activity.”

Building for the future of financial services

Trust and innovation have always been the corner stone for QIIB’s business model as the bank is keen on reinforcing this value through the innovative digital and electronic banking services. QIIB Mobile Banking and QIIB Internet Banking are premium services that provide efficient transactional banking and at a glance account information. With IBM Safer Payments, QIIB will ensure this innovation and trust is maintained.

Source: ibm.com

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Kargo reinvents advertising with AI-driven contextual targeting

As a kid, Chris Keune took notes on the commercials that interrupted his Saturday morning cartoons. He noticed a mismatch between many shows and the products advertised during them. Chris shared his notes with his third-grade teacher, looking for insights. “Well,” said his teacher, “it looks like someone is not doing their job.”

Today, Chris has turned his contextual marketing hobby into a career, overseeing data product and insight practices at Kargo. Kargo is a global mobile-first, editorial-led marketplace of unique multi-channel advertising and commerce opportunities for brands. The ad technology company creates and delivers ad campaigns to a large audience of smartphone users, using contextual advertising, without sacrificing brand safety or security against ad fraud.

How Kargo keeps ahead of changes in ad tech

As the ad industry moves away from third-party cookies due to privacy concerns and changing technology, many ad tech companies are scrambling to find new ways to target relevant consumers. Kargo stays ahead by prioritizing data-driven contextual advertising over the cookie approach.

Contextual advertising is nothing new. From newspaper and magazine display ads to TV and web page placements, contextual ads have matched brand messaging to relevant content for decades. But today’s advancements in big data, automation and artificial intelligence have amplified the power of contextual advertising.

With IBM Watson, Kargo can refine contextual signals within the publishers they support, compiling and clustering by customer interests, habits and challenges. Through this approach, Kargo obtains a deeper understanding of the reader, which it uses to build relevant ad experiences. These experiences help with the value exchange by bringing relevant brand messages aligned to their adjacent stories.

Context is key to relevance

Kargo’s holistic data-driven contextual advertising approach requires the company to know what each piece of content is about, and to pair it with a given brand or ad vertical. With this approach, publishers and advertisers don’t have to rely on external vendors. Kargo creates an actionable, first-party data set to inform contextual advertising decisions by analyzing publisher web page content and applying keyword targeting research, sentiment analysis and other analytical tools.

While bringing viewers more relevant ads sounds simple, at scale it requires a deep natural language understanding expertise. Natural language understanding extracts meaning and metadata from unstructured text data.

When Kargo decided to build out its AI capabilities, Chris looked at many technology partners. Based on his parameters, IBM Watson provided the most feature-rich, cost-effective solution. “IBM helped us build our base layer, our contextual advertising data set. It’s taking millions of articles and understanding the content and sentiment embedded within them.”

Kargo built tools on top of that data. With AI-equipped capabilities, the team achieves a new level of granular analysis that spans data sets. For example, analysis may show that people who read about the Olympics tend to spend on pet care, so Kargo can approach a pet food client with a contextual advertising plan to target pet owners on Olympics-related content. This behavioral advertising association isn’t the sort that a human would be able to intuit, but it’s a straightforward use case for AI.

By combining data from IBM Watson with Kargo’s own data capabilities and augmenting it with key data partnership capabilities, the company has built a new behavioral advertising solution. Cohort Intelligence groups together web user data of people with similar interests to help marketers further amplify their digital marketing efforts.

“Watson was incredibly turnkey,” says Chris. “The interactive demo and their API documentation was so easy to use that we were able to run proof-of-concept the first week. It’s easy to get up and running. And we had constant communication between Watson and the engineering team.”

With Watson’s sentiment analysis capabilities, Kargo can also experiment with different types of creative assets. The team runs tests of contextual ads with different emotional content, and often finds that results can vary greatly between “serious” and “happy” tones. These tests allow Kargo to optimize creative, sometimes even doubling ad performance.

Less is more

While moving away from third-party cookies has challenged the ad tech industry, the adoption of better technology gives data-oriented innovators like Kargo opportunities to create an environment that’s less intrusive and more relevant to digital advertising audiences. And using Watson, Cohort Intelligence is matching or exceeding the performance achieved with cookies.

Looking ahead for Kargo, Chris sees a future where taxonomies are standardized, so that marketers can speak the same language as they build the future of contextual advertising. Kargo is also working on tools that provide more actionable insights on the publisher side, letting editorial outlets know what kinds of relevant content are going to attract advertisers at a more granular level.

“Great publishers and content providers do themselves a disservice by plastering their site with clickbait ads,” says Chris. “It lessens their brand equity and diminishes their value to the reader. My goal is to find new ways to add value through ad relevance: quality over quantity and making sure your ad is there at the right time with the right message.”

Learn more about using deep learning to extract meaning and metadata from unstructured text data with Natural Language Understanding.

Source: ibm.com

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Build a simpler, more resilient hybrid cloud with IBM Storage

It’s clear that businesses are embracing hybrid cloud. Indeed, a recent report from the IBM Institute for Business Value states that 97% of business are piloting, implementing or integrating cloud in their operations.

However, as hybrid cloud environments become the norm, businesses must contend with additional IT complexity, public cloud costs and threats from cyberattack and other data destructive events.

Today, IBM® is announcing new capabilities and integrations designed to help organizations reduce IT complexity, deploy cost-effective solutions and improve data and cyber resilience for hybrid cloud environments.

Extending hybrid cloud storage simplicity to Microsoft Azure

One way to reduce hybrid cloud complexity is to ensure consistent function, APIs, management, and user interface across on-premises and public cloud platforms. This can be accomplished with software-defined storage (SDS). That’s where IBM Spectrum® Virtualize for Public Cloud comes in. It’s the cloud-based counterpart of the software in IBM FlashSystem® and SAN Volume Controller.

IBM Spectrum Virtualize for Public Cloud provides the same storage functionality in the cloud as you find on-premises, which makes it easy to implement hybrid cloud storage scenarios such as disaster recovery, cloud DevOps, and data migration. And since it provides this same function across clouds, it also makes it easy to use multiple clouds or to move from cloud to cloud.

Now we’re extending our cloud support to Microsoft Azure in addition to IBM Cloud® and Amazon Web Services (AWS).

On Azure, IBM Spectrum Virtualize for Public Cloud supports IBM Safeguarded Copy, which automatically creates isolated immutable snapshot copies designed to be inaccessible by software – including malware – and which can be used to recover on-premises or cloud data quickly in the event of a data destructive event.

Expediting Turbonomic integration for automated operations

IBM recently acquired Turbonomic, an Application Resource Management (ARM) and Network Performance Management (NPM) software provider. By acquiring Turbonomic, IBM is the only company that will be able to provide customers with AI-powered automation capabilities that span from AIOps to application and infrastructure observability.

IBM and Turbonomic plan to deliver rapid benefits for customers of IBM FlashSystem by improving application performance awareness and automation.

◉ Turbonomic will collect information from IBM FlashSystem storage including storage capacity, IOPS, and latency for each storage array.

◉ Turbonomic’s analysis engine combines FlashSystem data, virtualization data and application data to continuously automate non-disruptive actions and ensure applications get the storage performance they require.

This can eliminate the need for unnecessary over-provisioning and safely increase density without sacrificing performance. On average, customers can increase density by 30% without any application performance impact.

For environments using Instana®, Red Hat® OpenShift®, or any major hypervisor (such as VMware vSphere) with IBM FlashSystem, Turbonomic will observe the entire stack from application to array. This enables all operations teams to quickly visualize and automate corrective actions to mitigate performance risk caused by resource congestion, while safely increasing density.

Other key storage enhancements

We’re continuing to enhance the data and cyber resilience capabilities of our storage platform to help customers combat the threat of ransomware and other data destructive events. Enhancements include:

◉ IBM Spectrum Protect Plus offers a suite of enhancements specifically designed for Red Hat OpenShift and Kubernetes to support data protection for containerized environments. These include Red Hat certification, support for OpenShift workloads deployed on Azure and direct backup to S3 object storage.

◉ IBM Spectrum Protect now supports replicating backup data to additional data protection servers.Additionally, IBM Spectrum Protect now supports using object storage for long-term data retention to reduce the cost of backup.

◉ IBM Spectrum Scale global data fabric gains a new high-performance S3 object interface. This means that cloud native S3 applications can provide faster results without the typical delay for object storage. Additionally, a new GPU direct storage (GDS) interface enables NVIDIA applications to run up to 100% faster with IBM Spectrum Scale.

◉ IBM Elastic Storage® System 3200 now includes a 38TB IBM FlashCore® Module. This new FlashCore Module is double the size of the previous, largest option, doubling the capacity of an ESS 3200 to 912TB in only 2 rack units.

Source: ibm.com

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Relocation reverberations: How pandemic moves have impacted demand and inventory management

Many people have relocated over the last year, as closed offices and increased remote working options enable more flexible living arrangements. With a shift of population to new places, particularly from large urban city centers to other suburban areas, retailers may be struggling to position their inventory based on historical data trends. For instance, an area that previously may not have performed well, may be over-indexing simply because more people have moved to the area during the pandemic and may be experiencing stockouts since inventory was not positioned for this shift. How can a retailer know how much inventory to position and where, when demographics are rapidly changing as a result of the pandemic?

Aside from population-based demand changes, retailers also have been tasked with anticipating demand shifts from increased online shopping, decreased brand loyalty, and other shopping trends. Inventory allocation has never been easy, but a less clear picture of demand makes forecasting, planning and allocation increasingly complicated.

What is demand planning?

Demand planning is a critical process for supply chain management during which a company projects future demand, and therefore shifts output to meet those projections. With accurate forecasting of customer demand and sales, they can better plan for how much inventory to order or produce, as well as where to allocate that inventory across locations to ensure they can meet demand. Accuracy is necessary to efficiently balance inventory. By situating inventory where it is needed most, retailers can meet demand without excess carrying costs, or disappointing customers with backorders or out-of-stock situations.

How has the demand picture gotten more complicated since 2020?

A significant number of US offices remain closed for in-person work during the pandemic, with 41.8% of the American workforce currently working remotely. Without a need to be in person for work, many employees in the US have discovered that they can be anywhere and still get the job done. In addition, with financial challenges and unexpected layoffs, many reconsidered their city lifestyle and made the shift to more affordable suburban areas. In the second quarter of 2020, 51% of Realtor.com’s property searches from city residents in the 100 largest U.S. metro areas were for homes in the suburbs of those areas, a record high for the site. There has been a noticeable “urban shuffle”, with people leaving big, densely populated areas in favor of suburbs and smaller communities across the country.

On top of that, the flow of people into core US metro areas showed a net decrease – indicating not only that people were moving out, but that fewer residents were moving in. According to Bloomberg, 82% of urban centers saw more people move out than in, with 91% of suburban counties seeing the opposite. And, based on USPS address change requests, over 15.9 million people have moved since February 2020.

Discover how Sterling Order Management helped JOANN Stores manage unexpected demand during COVID-19

Demand forecasts and inventory allocation directly impact stock and availability across different retail locations around the country. However, with shifting populations, previous demand estimates using historical data may no longer be enough to efficiently situate inventory. For instance, in New York City (NYC), some residents took the pandemic as an opportunity to move out of the city center and into neighboring suburbs within commuting distance of the city or even to warmer areas across the country. In total, 320,000 people left NYC in 2020, a 237% increase from the year before. A retailer who allocated significant inventory in NYC may face excess carrying costs if their inventory allocation didn’t consider pandemic-related population and demand shifts.

To complicate inventory management further, previously forecasted demand for in-store sales has been dramatically impacted by the growth of eCommerce. In late 2020, 23% of consumers reported that they were doing all or most of their shopping online, and that this was a change from their pre-COVID shopping patterns. With rising online demand that may be here to stay, estimating in-store demand and inventory gets challenging. In addition, in-store cart conversion is now impacted by online inventory availability. Customers are taking another step before purchasing in store: checking in-store availability online. Retailers must provide accurate inventory estimations online to keep customers coming to stores, since 33% of US adults are less likely to visit a store at all if they can’t confirm online first that what they want to buy is available in-store.

What does this mean for retailers?

As the pandemic exposed flaws across many supply chains, retailers are emerging with a strong focus on resilience and building smarter, more dynamic supply chains that can react quickly to disruptions and better match supply to demand. With volatile and unpredictable customer demand at store locations, the best thing retailers can do is become more agile to react when change happens, and to establish best practices to keep customers satisfied.

A real-time view of inventory across store locations, warehouses, and in-transit enables retailers to identify mismatches between demand and inventory availability faster. Today, modern inventory management solutions alert users instantly when inventory is over-stock or below safety stock thresholds, helping retailers take immediate action to rebalance. And, with demand shifting across store locations, retailers can monitor inventory levels and reallocate inventory to locations where demand may be higher.

Using AI technology for order management and fulfillment ensures retailers are optimizing inventory and using it at its most profitable price point, continuously learning and improving outcomes for omnichannel fulfillment. With a combination of AI and an enterprise-wide inventory view, retailers can easily identify inventory in stores where inventory is obsolete or slow moving, and prioritize it to fulfill eCommerce demand to improve inventory sell-through. With full use of enterprise-wide inventory, retailers can ensure they are meeting demand in the most profitable way, no matter how demand shifts have impacted their retail locations.

Regardless of demand shifts, retailer indication of available in-store inventory online is becoming a pre-requisite for brick-and-mortar sales. To better stabilize in-store demand, retailers must meet the modern customers’ changing needs for transparency and certainty in shopping experiences. Retailers should look to increase online transparency of inventory availability for all omnichannel touchpoints like curbside pickup, in-store purchasing, or delivery, using intelligent promising software. With sophisticated inventory promising software, retailers can improve in-store sales, as well as digital conversions, while increasing profitability.

Source: ibm.com

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Develop your skillset: hands-on training for IBM PowerVC 2.0 and Red Hat Ansible

IBM PowerVC 2.0 hit the market in fourth quarter of 2020. Since then, IBM has produced incremental updates to the software. The IBM PowerVC product development team worked hard to bring modern design and open-source JavaScript frameworks to cloud management on IBM Power. After having tried it for several months, I can’t recommend it more. If you’re using IBM Power servers, you should be running IBM PowerVC to manage them.

I’ve spoken with several new IBM Power administrators who are looking to test drive the product without having to worry about obtaining and managing licenses. There’s a button on the official product page that lets you download a trial version of the software, which you can then use to install in your own environment. But what if you wanted more? For example, everything from understanding the basics of IBM Power virtualization to the latest advanced VM management capabilities of IBM Power.

PowerVC 2.0 Workshop

IBM and our Global Training Partners now have an official IBM PowerVC 2.0 workshop! This gives you several days of access to systems in our IBM data center. You can touch and feel the product from the comfort of your home or office – everything from installation to advanced private cloud management. You can also get an official IBM-approved instructor to deliver the content to your organization.

That’s easily said. But, behind the scenes, IBM has dedicated pools of IBM Power servers in an IBM managed data center. They had to be specifically configured to automate everything from giving you access to a virtual machine that connects you to our network, to setting up a bunch of virtual partitions, virtual Hardware Management Consoles (HMC) and IBM PowerVC NovaLink related configurations. All that happens automatically when you book our workshop.

The PowerVC 2.0 workshop shows you how to set up IBM PowerVC 2.0.1 in both HMC and IBM PowerVM Novalink managed environments. It covers every single major administrative task. That includes a lot of information on OpenStack. We’ll manage Red Hat Enterprise Linux and IBM AIX partitions. Automation with Cloud-init and the implications of running your own Infrastructure as a Service cloud are discussed in detail.

Virtual TechU

At the virtual IBM TechU 2021, I will present on something similar. I have sessions on IBM PowerVC and Red Hat Ansible. The idea is to leverage the systems and automation software we’ve created in our data center to showcase our latest capabilities. I have a hands-on session on how to get started with IBM PowerVC to manage your operating systems and perform virtual machine lifecycle tasks. My second hands-on session is on how to get started with Ansible on Linux and run Playbooks to perform configuration management on IBM Power. I will showcase how to implement Ansible on AIX in a third hands-on session. I will also present a demo, on running Ansible on a Linux partition on IBM Power. These Red Hat Ansible sessions are now part of an official IBM training course too, which you can enroll in here. I will also present a general interest hands-on session on using Git and GitHub efficiently to perform source code management tasks.

I’m excited about the new training opportunities that will help you, our clients, to better utilize the IBM solutions critical to running your business. I hope to see you at TechU or a workshop soon.

Source: ibm.com

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Accelerate application development with Red Hat and IBM Z

How can you accelerate the development and deployment of applications, and then manage them at scale?

This is the challenge businesses are facing around the world in the era of hybrid cloud – including organizations who depend on IBM Z or LinuxONE for their IT infrastructure and are looking to modernize their applications in place.

Back in August, we discussed Red Hat OpenShift’s great momentum on IBM Z and LinuxONE. And the recent announcement of Red Hat OpenShift 4.9 is an excellent opportunity to reflect on what’s been happening in the Red Hat OpenShift ecosystem for IBM Z and LinuxONE over the past few months. An ecosystem that includes not only Red Hat and IBM software, but a wide range of open-source projects and ISV applications.

Next steps

Red Hat OpenShift continues to expand and gain new features. One of the most interesting developments in OpenShift is its transformation from just x86 to multi-architecture diversity. This includes IBM Z and LinuxONE, but also Arm and IBM Power which are increasingly important for the emerging edge computing market as well as the cloud and datacenter.

Red Hat OpenShift 4.9 for IBM Z and LinuxONE includes support for multiple network interface cards (Multi-NIC) which can improve performance internally and externally, provide separation of networks, and enhance the fail-over capability.

One of the strengths of IBM Z and LinuxONE is advanced security features, with the IBM Crypto Express card providing fast hardware cryptography, as well as protecting keys in a Hardware Security Module. Red Hat OpenShift support for the Crypto Express card is planned to be provided through a Red Hat certified container, available later this year. The unique combination of Red Hat OpenShift plus the IBM Z cryptographic hardware creates a highly differentiated, security-rich solution.

Data and AI

The latest version of IBM Cloud Pak for Data on IBM Z and LinuxONE, available from October, includes IBM Watson Studio. This enables machine learning models to be built and deployed on IBM Z and LinuxONE. Introducing artificial intelligence and machine learning capabilities to OpenShift applications on Z and LinuxONE is a major step forward and can help organizations to reduce fraud and unlock the value of their data.

Red Hat OpenShift Data Foundation for IBM Z and LinuxONE 4.8, available from September, provides persistent storage and other data services such as object storage, dynamic provisioning, disconnected install, and DASD support for cloud-native mission-critical workloads on IBM Z and LinuxONE.

Integration

IBM Cloud Pak for Integration has been updated to the latest version (2021.3.1) and includes updated support for IBM Z and LinuxONE.  Building on Red Hat OpenShift, this enables applications to connect asynchronously using technologies such as IBM MQ and MQ Advanced, Platform Navigator, App Connect, Aspera High Speed Transfer Server, and the Kafka-based Event Streams.

Management

As OpenShift workloads on Z and LinuxONE scale, the need increases for management tools which can also scale.

Red Hat Advanced Cluster Management for Kubernetes has been able to manage clusters and containers on IBM Z in “manage-to” mode since version 2.2 – meaning that the management console would run on an x86 system. Now with Red Hat Advanced Cluster Management 2.4 (aligned with Red Hat OpenShift 4.9) the management console can run on IBM Z as well, adding “manage-from” mode. This helps enable seamless hybrid cloud management, with Red Hat Advanced Cluster Management on IBM Z managing OpenShift clusters running on x86, IBM Power, and public cloud infrastructures, as well as on IBM Z.

Complementing this, IBM Cloud Pak for Multi Cloud Management provides a consistent management experience across multiple clouds for managing virtual machines and enabling cloud automation on IBM Z and LinuxONE in “manage-to” mode.

Instana, IBM’s recent acquisition for discoverability and management of applications, now supports IBM Z and provides Observability from Mobile to Enterprise. Instana can monitor OpenShift applications running on IBM Z or LinuxONE, also in “manage-to” mode.

Finally, IBM Cloud Infrastructure Center, which manages the IBM Z and LinuxONE infrastructure for both traditional and cloud workloads, can now use IBM Spectrum Scale for block storage provisioning, as well as introducing fabric zoning support for IBM z/VM virtual machines.

Ecosystem

The ecosystem of Independent Software Vendors (ISVs) and application providers supporting Red Hat OpenShift running on IBM Z and LinuxONE continues to expand.

This includes Temenos, who announced the availability earlier this year of their next-generation core banking solution, Temenos Transact, on OpenShift on IBM Z and LinuxONE. By combining Red Hat OpenShift on IBM Z and LinuxONE, banks can deliver new services to their customers while leveraging existing infrastructure.

Several other solution partners applications are also enabled on Red Hat OpenShift for IBM Z and LinuxONE, including:

◉ Core banking applications such as Technisys and Infosys Finacle

◉ Digital banking engagement applications including Backbase

◉ Relationship-based pricing and product applications such as Zafin and SunTec Xelerate

◉ Payments applications including Vestigo and Fiorano

◉ Database management applications such as Fujitsu Enterprise Postgres

Source: ibm.com

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IBM Power Systems Virtual Server: designed to drive performance, security and automation

The more innovative and modernized enterprises become, the more critical the need is for security that doesn’t compromise performance. In the past year, the market has seen large-scale ransomware attacks make reputable businesses suffer from operational shutdowns, compromised data and even lawsuits — all costing millions of dollars. Worse than taking months to recover financially, these attacks can have lasting impacts on customer perception.

Read More: C2010-825: IBM Rational Team Concert V6

End-to-end security continues to be a key aspect of IBM® Power® servers as well as our latest virtualized offering, IBM Power Systems Virtual Server. In this second installment of our blog series about IBM Power Systems Virtual Server, we’re looking at how large and small businesses that are new to Power solutions can benefit from this robust offering.

Multilayered security and uptime

It’s essential to approach your enterprise’s security with a proactive mindset. For many generations, IBM Power Systems has delivered renowned end-to-end security for on-premises environments, an approach that protects each layer of your IT hardware and software stack from both internal and external threats.

IBM Power Systems Virtual Server technology is a continuation of our commitment to deliver the security that today’s enterprises need in an ever-demanding online environment. We combined the security and isolation of an on-premises system with a virtualized environment’s reliability and innovation.

IBM Power System Virtual Server is powered by Power S Class and E Class enterprise systems that run IBM PowerVM® server virtualization which gives users the reliability and resilience that they require. We’ve designed this solution to help enterprises remain operational even during storms and disasters thanks to 14 global data centers across 7 countries, with even more locations coming. By incorporating both reliability and resilience into PowerVM® technology, high availability (HA) and disaster recovery (DR) are on a different level of performance for these virtualized machines. This is most clearly illustrated by the findings in the US National Institute of Standards and Technology (NIST). If you search its database for vulnerabilities found in the PowerVM server virtualization feature or PowerVM hypervisor, you’ll get zero results. This is the peace of mind we would like to offer to all our clients.

Develop cloud native applications with Red Hat OpenShift

Containerized workloads are changing the way we develop, deploy and manage applications for enterprises. When you combine this innovation with the power of open-source technology like Red Hat OpenShift, you have a solution designed to deliver game-changing results. We’re excited that our clients can provision Red Hat OpenShift clusters on IBM Power Systems Virtual Server, offering robust capabilities for application modernization and cloud native development. Utilizing a combination of tools and helper scripts, we have simplified the User Provisioned Install process to help you get a Red Hat OpenShift cluster up and running on IBM Power Systems Virtual Server in as little as a few hours. Red Hat OpenShift on Power supports a rich ecosystem of applications and middleware, including over 15,000 open-source software packages, Red Hat Application Services, IBM Cloud Pak® and ISV applications.

The obvious choice for SAP workloads

For enterprises with SAP workloads, the clock is ticking. Users must migrate to the SAP S/4 HANA system by 2027. When you consider this deadline alongside the ever-growing need to implement a hybrid strategy, it’s essential to go with IBM Power Systems Virtual Server — the only on-premises and off-premises certified Power solution for SAP HANA and SAP NetWeaver platform workloads, providing a truly hybrid cloud experience end to end.

Additionally, uptime for SAP workloads is a critical consideration. According to the ITIC 2020 survey, 88% of enterprises indicate that unplanned downtime costs USD 300,000 per hour — or USD 4,998 per minute, per server. Now, users are modernizing their SAP applications, provisioning workloads and maximizing uptime with the help of IBM Power Systems Virtual Server.

Smaller HANA t-shirt sizes will be made available on IBM Power Systems Virtual Server later this year, which means there will be over 50 SAP-certified HANA instances. These smaller instances range from 128GB in memory to 768GB with 4 cores. Power is developed to provide the flexibility to address the needs of our customers.

IBM Cloud connection

We are excited to provide an automated way to connect IBM Power Systems Virtual Server instances to IBM Cloud® resources that include classic and VPC networks. Cloud connections create a Direct Link Connect (2.0) instance to connect your IBM Power Systems Virtual Server instances to IBM Cloud resources. The IBM Power Systems Virtual Server 10Gb/s Direct Link Connect 2.0 is designed to enable access to IBM Cloud resources with much higher performance and in a streamlined, user-friendly way.

Multitenant environments

Achieve high levels of performance without wasting resources. Enterprises can run IBM AIX® and IBM i workloads. On the Linux® side of workloads, our clients have the freedom to provision both SAP SUSE Linux Enterprise Server (SLES) 12 and 15 OVA boot images and Red Hat Enterprise Linux (RHEL) 8.1 and 8.2 capabilities. These workloads can run with as little as a quarter of a core, allowing the ability to scale and to run workloads on-premises and off-premises — lowering cost while increasing application modernization.

Versatile payment options

Pay-as-you-go and savings plan subscription options enable you to pay however best fits your enterprise’s needs. For the pay-as-you-go option, enterprises have the flexibility to use data center capacities and resources as needed. Meanwhile, savings plans offer up to a 30% discount for 1-year commitments and up to 45% discounts for 3-year commitments.

Low infrastructure maintenance

Your focus should be on your mission-critical workloads. That’s why IBM takes the task of infrastructure management and maintenance off our clients’ hands. We can also help you achieve modernization and expansion to hybrid cloud with IBM Systems Lab Services and IBM Garage™.

Developing and testing

We know that the availability of non-production configuration is essential for enterprises as they strive toward innovation. The scalability of IBM Power Systems Virtual Server allows our clients to run multiple sandbox environments simultaneously without larger capital budgets. They can also spin logical partitions (LPARs) up and down as needed, and use bursting capabilities during needed periods.

A look at our roadmap

If you’re new to Power servers, there hasn’t been a more robust offering that will drive change for your business — nor a better time to get started. Here are some things that our clients will experience soon.

◉ Updates focused on ISO27k standards for privacy

◉ SOC 2 amenability

◉ Payment Card Industry (PCI) amenability

◉ Virtual private network as a service (VPNaaS)

◉ IBM Cloud credit management

◉ Network automation features

◉ Backup and restore services

IBM Power Systems Virtual Server in action

A client of ours is one of the largest logistics operators in Spain, Portugal and beyond that delivers goods for clients in verticals, including automotive, pharmaceutical, healthcare and electronics. When the COVID-19 pandemic caused a spike in demand on the online shopping front, the client needed an environment that allowed for the drastic scalability it was experiencing without putting more stress on its IT team, which was already struggling with bandwidth. With IBM Power Systems Virtual Server, the client achieved this scalability and easily managed the spike in traffic. The best part — our client can now focus on providing great results for its customers across the globe while we manage its infrastructure.

Source: ibm.com

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The next step in homomorphic encryption for Linux on IBM Z and LinuxONE

101 billion. That’s the number of data records compromised in 2020. This made 2020 a record-breaking year for data breaches – the cost per breach also hitting a record high with an average of $4.24 million per incident.

Modern cryptography has enabled sensitive data to be encrypted at rest and in transit – table stakes for the encryption world. The more challenging area to address is encrypting data while it is in use or being processed in memory. Whether it’s a third party, like a cloud service provider, or your own employee that is processing the data, data in this state can be particularly vulnerable because it must be decrypted to be processed. This missing link of end-to-end encryption can create a window of vulnerability for hackers to exploit and steal data.

Fully Homomorphic Encryption (FHE) is an emerging security technology that allows computations to be performed directly on encrypted data without decrypting it, marking a new paradigm shift for data security. FHE can help support a zero trust strategy by keeping your data, the models that process the data (typically hosted in a cloud or third-party environment) and the results generated encrypted; only the data owner has access to the private key and has the privilege to decrypt. This advanced security approach can help protect your data against external attacks, insider threats stealing intellectual property intentionally or inadvertently and can help provide long-term data protection against quantum attacks.

What’s new?

Last year, we introduced FHE to Linux on Z with our FHE Toolkit. Today, we are announcing the availability of the next evolution of the FHE Toolkit called IBM HElayers, a software development kit (SDK) for the practical and efficient execution of encrypted workloads using fully homomorphic encrypted data. HElayers is designed to enable application developers and data scientists to seamlessly apply advanced privacy preserving techniques without requiring specialized skills in cryptography – all while working in newly integrated Python and C++ environments. The images for the Python and C++ kits are provided under a community edition license for non-commercial use. Customers who want to access advanced features and plan for commercial-grade deployment using HElayers can engage through the Premium Edition Program by contacting the IBM FHE team at FHEstart@us.ibm.com.

HElayers is engineered to support a wide selection of analytics such as linear regression, logistic regression, and neural networks so that application developers and data scientists can use the power of FHE. It is delivered as an open platform that is capable of using the latest FHE schemes and libraries and ships with a multitude of tutorials and sample applications that highlight the basics of FHE and how to use this technology in a practical way. Sample applications include credit card fraud detection, encrypted database search, text classification, and various examples from the healthcare industry.

Try it for yourself

It seems daily that we see news about data breaches and inadvertent disclosures of information. In a real sense, data privacy has gone from something discussed in a company boardroom to something that is now discussed at the dinner table with family and friends. Today, our goal is to make HElayers accessible to anyone with an internet connection. Try HElayers for yourself including tutorials, sample applications and documentation for Linux on Z by downloading the images from Docker Hub using the following links:

◉ Python kit with Jupyter Notebook IDE
◉ C++ kit with Visual Studio Code IDE

Take a look at our in-depth walkthrough video on how to download and get started with HElayers.

Source: ibm.com

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Cloud Pak for Data on IBM Z: extending the reach of AI

Artificial intelligence (AI) can be a highly transformative technology and is becoming an essential part of the technology industry impacting everything from our personal lives to the way we conduct business. But as AI computing becomes standard practice, enterprises are looking to differentiate themselves by utilizing tools that will allow them to get the most value and insight from their AI. One such tool is IBM Cloud Pak® for Data and in this blog I will explain how it provides organizations with an end-to-end enterprise insights platform for their data and AI needs and how IBM Z® can also play a vital role.

IBM Cloud Pak for Data, Watson® Machine Learning for z/OS® and open-source technologies are a part of a comprehensive software and hardware strategy that solidifies IBM Z as a first-class AI platform. IBM recently publicly discussed the new Telum processor which features on-chip acceleration specifically for AI deep learning processing.

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To get the most value from their AI efforts, organizations need to establish an information architecture. At many large enterprises, data resides in different formats across multiple platforms. Because of this complex data landscape, many organizations have found it difficult to collect and structure data in a form useful for AI. The lack of an information architecture within these complex environments can be a primary factor in impeding AI implementation. To help establish an information architecture that can unlock the value of data and accelerate the journey to AI, IBM has developed a prescribed approach we call the “AI Ladder.” It features four sequential steps; collect, organize and analyze data so that AI models can be infused within business processes.

IBM Cloud Pak for Data

IBM Cloud Pak for Data addresses the challenges of delivering analytics and AI using a single, open platform to infuse AI into business applications. Cloud native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. It helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to successfully implement AI. Core to an enterprise insights platform is the ability to store and manage data in support of analytics and AI. Modernizing your data infrastructure via a cloud native, containerized approach, such as with IBM Cloud Pak for Data, can significantly simplify your data management efforts. And leveraging existing IBM Z infrastructure and skills can help you reduce implementation risk, complexity, and cost.

IBM Cloud Pak for Data on IBM Z and IBM Watson Studio

IBM Cloud Pak for Data on IBM Z debuted in November 2020 with a focus on modernizing data infrastructure in support of analytics and AI. It brings the capabilities of IBM Cloud Pak for Data including the Red Hat® OpenShift® Container Platform and pre-integrated, certified software to your existing IBM Z infrastructure. The initial release included IBM Cloud Pak foundational services, IBM Db2® Management Console and IBM Db2 Warehouse. Also available are IBM Db2 Advanced Enterprise Server Edition and IBM Db2 for z/OS® Data Gate.

IBM is now incorporating IBM Watson® Studio within IBM Cloud Pak for Data 4.0.2 on IBM Z so that organizations can build AI models where data often originates. IBM Watson Studio is designed to empower data scientists, developers, and analysts to build, run and manage AI models, and optimize decisions anywhere IBM Cloud Pak® for Data runs.

These recent enhancements help organizations to confidently leverage their IBM Z platform and enterprise data to build and deploy ML/AI models on Linux® on IBM Z and LinuxONE. Organizations can also build AI models on IBM Cloud Pak for Data on IBM Z and deploy those models within the z/OS environment through Watson Machine Learning for z/OS. By unlocking the value of their IBM Z data in new ways, organizations can drive additional revenue, control costs, help reduce fraud, and improve customer satisfaction while making minimal changes to their core business applications.

Source: ibm.com

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Don’t let the shipping container crisis ruin Christmas this year

By now we’ve all heard the rumblings (and the roars!) about how myriad challenges – backlogged ports, factory shutdowns, and shipping delays – are going to impact Christmas shopping this year. According to Business Insider, the cargo ships waiting off the coast of California are creating record backlog. We don’t want to minimize the serious impact of these substantial roadblocks – especially as the retail industry enters the eight-week holiday shopping window that accounts for a big portion of many businesses’ annual sales – but we also want to acknowledge that there are steps you can take to prepare for and successfully work around the issues.

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1. Be up-front with your customers

Chances are, your customers have heard about many of these issues and have concerns they might not be able to buy the gifts and goods they want for the holidays. Address their concerns directly, through touchpoints like social media, advertisements and emails. They want to hear from you, and they want to know the steps you’re taking. For instance, encourage customers to shop early, to sign up to be notified when an out-of-stock item is back in stock, etc.

2. Kick-off the holidays earlier than usual

NBC News is reporting early holiday shopping is anticipated this year. Additionally, 27% of holiday shoppers plan to start Christmas shopping by the end of September. If your customers are concerned that supplies are limited, it makes sense that they will shop early, hoping to avoid out-of-stock disappointment. Be ready for them by taking steps like adding extra staff to handle increased sales volume.

3. Rethink promotions

As the price for goods – and for shipping and delivering goods – goes up, it leaves less room for discounts and sales, two traditions during past holiday seasons. This year, rather than offering big discounts or slashing prices, consider promotions that encourage loyalty (after all, repeat customers are your best customers), offer bundles (combining two or more items), and consider high-value, low-cost freebies with purchase.

4. Prepare for more in-person shopping

Ed Desmond, Executive Vice President of the Toy Association, says that more in-person shopping is expected this year than compared to the 2020 holidays, when the country was in the middle of a deadly winter surge of the coronavirus. Again, be ready for in-person shoppers by taking steps like creating plans for how to keep the shelves stocked when inventory is low. Well-designed visual merchandising and signage will entice shoppers to stop in and quickly drive up sales by displaying the most popular items in windows and high traffic areas. Give shoppers more time during the busiest time of year, especially the procrastinators and last-minute shoppers, by extending your store hours.

5. Hone in on your most popular items

With so much in flux, some companies are finding solace (and sales) in the classics. In addition to stocking up on your customers traditional favorites, consider including less variation than you might normally offer. For instance, if a cotton v-neck tee is your signature item, offer it in your best-selling colors and top-selling sizes, without taking too many chances by including unique or unusual hues, or sizing too far beyond either side of what’s standard.

6. Consider supplier alternatives

If the clogged ports and shipping delays have you rethinking some of your vendors, and your company is in a position to get your products from other sources, consider finding local or USA-based suppliers. This reduces delivery time and allows you to market the products as “local”. There are also huge benefits here in regards to reducing carbon footprint which is a major consideration for 32% of US consumers who are prioritizing companies that are actively reducing their impact on the environment.

7. Find shipping alternatives

As national shipping carriers face staffing issues and major backlogs, look for local and regional alternatives. If you can, consider building up your own delivery services, even at a local level, to help relieve some of the shipping pressures.

8. Embrace technology

The retail market is moving quickly. To stay competitive, your technology needs to be adaptable, scalable and on-point this holiday season. Worldwide eCommerce retail sales in 2020 were 4.28 trillion USD and are projected to grow to 5.4 trillion dollars in 2022. Customers are expecting a fluid experience from end-to-end, and you can shape their overall experience to increase conversions and build brand loyalty. IBM experts can help you successfully navigate a sea of challenges with eCommerce. It’s always the right time to get on board with our offerings, or to add-on to the IBM solutions you currently employ. Here’s a trio of ways we can help:

Dynamic inventory – Avoid lost revenue from out-of-stock goods with dynamic inventory. You can combine inventory intelligence with real-time data and be proactive about store transfers to optimize your safety stock. Keeping a minimal amount of safety stock is a balance of the right amount of extra stock while keeping reasonable inventory costs.

Intelligent promising – Improve eCommerce conversions and reduce cart abandonment with intelligent promising. Make and manage order promises with accurate delivery dates for customers, and easily support even the most complex scenarios, including orders that from third-party services and multi-brand orders.

Fulfillment optimization – Handle rising fulfillment costs from growing complexity and heightened customer expectations with fulfillment optimization. With advanced data science to achieve multiple objectives, you can optimize profitability by balancing various business goals while delivering the best customer experience, from discovery to delivery.

Preserve brand trust by providing shoppers with greater certainty, choice and transparency across their buying journey this holiday season. Explore how to improve digital conversions and in-store sales while increasing omnichannel profitability with IBM Sterling Intelligent Promising.

Source: ibm.com

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Keys to accelerating IT innovation: technology and collaboration

Technology is helping organizations to deliver on their mission and become smarter and more efficient to differentiate themselves from the competition. It is also helping to shape the world, as we depend on it to assist with basic demands such as food, living space, health, safety, mobility, communication, education, entertainment, as well as governmental and financial services. In parallel, we are also living in an era of information technology in which we are still witnessing exponential efficiency gains in basic capabilities like compute, storage, and networking. Data is fueling innovation and it has become clearer than ever the true value of data.

Read More: C1000-026: IBM Security QRadar SIEM V7.3.2 Fundamental Administration

Many outcomes of technology innovation start as small agile projects. Some of them scale to large impact. There are so many ways to innovate, which leads organizations to question where to start and how to approach it. Co-Creation and Design Thinking have proven to be the right concepts for innovation because they focus on jointly understanding an area of business and implementing a change, doing something more intelligently, efficiently. Experts of different areas are working together to design and implement a solution as a minimum viable product, which can be augmented and scaled over time to generate big impact.

It is important that an understanding of a specific industry or industry opportunity is in place. Many innovations are specific to an industry, but they can also disrupt existing business operations in that industry, if for example, a manual task is automated or an analog asset is digitalized.

It is not only about having experts from different areas working together, but it is also key to have diversity in the agile teams. This includes the diversity of age. Collaboration of experienced baby boomers with early professionals from Generation Y or Z can do magic. It is valuable to nurture diversity, openness, and respect.

When it comes to technology decisions, the value comes from the ecosystem that is behind a solution. An open hybrid cloud and AI platform approach backed by open source is an incredible foundation. But the largest value is gained when this system is simultaneously backed by professional services and an ecosystem of additional software. Red Hat OpenShift plays a big role here because this open and secure, enterprise ready Kubernetes platform enables teams to develop once and deploy everywhere. It avoids lock-in into a single technology stack. It opens the doors to deployments in private data centers, at the edge or in public cloud or collocation sites.

Data and AI will be ingredients of nearly every innovative solution. It’s crucial to have the ability to use AI and to train AI models, but also to use the trained models at the edge which means close to the device where the data lives. The opportunity to apply AI models to existing or future data is huge.

But as data becomes more valuable, so too does the risk of cyber-attacks as hackers are eager to get their share of the value. In the 2021 X-Force Threat Intelligence Index report, based on billions of data points from clients and public sources, a major finding was that ransomware was the most popular attack method in 2020, making up 23% of all incidents IBM Security X-Force responded to and helped remediate. Innovation needs to go hand in hand with handling increasing cyber risks.

And the efficiency gains in technology might slow down in the decade to come. Information Technology is reaching more and more the atomic scope which will limit the ability to scale compute, storage, and networking hardware further down to deliver more outcome with less resources. The future of computing will need to combine new computing concepts to create the systems needed to tackle challenges with more efficiency. This will include Quantum computers, AI hardware and optimized scaling for traditional semiconductors.

All these important elements of innovation will be highlighted at this year’s IBM TechU where I will be hosting the “Architecting the Future” track. Participants at this year’s TechU will get a complete picture of drivers and ingredients for innovating your business with IBM Z, LinuxONE, Power and Storage and beyond from a range of technical leaders; Eight hosted live sessions will inspire you about what’s next.

Source: ibm.com

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