Education is changing. In part, this shift is driven by students, who increasingly demand virtual and hybrid learning experiences that better match the ways they like to consume content at home. Meanwhile, virtual education has become an essential element of resilience for educational institutions by ensuring that students don’t fall behind during closures.

In the schools and universities of tomorrow, hybrid and virtual learning will play a central role in enabling inclusive education that’s focused on the unique needs of individual students and better able to drive engagement at all levels. As a result, student outcomes will likely improve. Evidence from corporate training programmes suggest that this could be the case, demonstrating that virtual learning boosts retention rates by 25% to 60% compared to 8% to 10% using traditional methods.

However, as schools and universities make the move to virtual and hybrid learning, many are encountering barriers that are slowing progress considerably.

The key challenge is one of complexity. The average number of edtech tools in schools is over 1,400, and IT teams will likely struggle to ensure the efficacy of such a large number of systems.  There are also questions around the impact on students. With no easy way to monitor student engagement there is no clear path to optimising virtual and hybrid experiences. Similarly, a lack of necessary features and capabilities in many of the tools, such as the ability to combine live, real-time, and video functionality,  mean that institutions can struggle to offer a range of learning experiences, necessary if they’re to tailor virtual learning to the needs of different students. 

Overcoming these barriers is crucial for educators, for the simple reason that doing so unlocks a range of benefits. For one, the curriculum is extended to any location, and schools can benefit from a talent pool of educators that includes anywhere with a good broadband connection. Virtual and hybrid learning creates both global and remote learning and delivers accessibility and localisation for learners.

Of course, there are still some people for whom broadband access is still a problem. But if this gap is closed, then the approach unlocks a 24/7 model for learning for all, where content is always available to students, and they can learn in a self-paced asynchronous manner. Additionally, virtual and hybrid learning can support a range of content formats to support self-serve learners, such as video on demand (VoD). This is a much more tailored approach based on providing personalised learning journeys for students. And of course, virtual experiences are available regardless of whether schools and universities are open or not, helping to build resilience.

Thanks to the cloud, the barriers currently holding institutions back can be overcome. Kaltura’s Video Experience Cloud for Education is a case in point. Kaltura is a cloud company focused on providing compelling video capabilities to organisations.

Kaltura Video Cloud for Education powers real-time, live and video on-demand for online development and virtual learning. Its products include virtual classroom, LMS video, video portal, lecture capture, video messaging, virtual event platform, and other video solutions — all designed to create engaging, personalised, and accessible experiences during class and beyond.

Kaltura content, technology, and data is fully interoperable and seamlessly integrates with all major learning management systems, enabling schools to quickly deploy and get started in transforming learning for their students and staff. The Kaltura Video Cloud for Education helps drive interaction, build community, boost creativity, and improve learning outcomes

Built on the Amazon Web Services (AWS) Cloud, Kaltura provides an elastic, reliable, performant, and secure platform that can enable schools and universities to accelerate their move to virtual and hybrid learning. 

For more information on how to use video to drive student engagement online click here to discover Kaltura’s Video Cloud Experience.

Education and Training Software, Hybrid Cloud, Virtualization

The digital transformation bandwagon is a crowded one, with enterprises of all kinds heeding the call to modernize. The pace has only quickened in a post-pandemic age of enhanced digital collaboration and remote work. Nonetheless, 70% of digital transformation projects fall short of their goals, as organizations struggle to implement complex new technologies across the enterprise.

Fortunately, businesses can leverage AI and automation to better manage the speed, scale, and complexity of the changes that come with digital transformation. In particular, artificial intelligence for IT operations (or AIOps) platforms can be a game changer. AIOps solutions use machine learning to connect and contextualize operational data for decision support or even auto-resolution of issues. This simplifies and streamlines the transformation journey, especially as the enterprise scales up to larger and larger operations.

The benefits of automation and AIOps can only be realized, however, if companies choose solutions that put the power within reach – ones that package up the complexities and make AIOps accessible to users. And even then, teams must decide which business challenges to target with these solutions.  Let’s take a closer look at how to navigate these decisions about the solutions and use cases that can best leverage AI for maximum impact in the digital transformation journey.

Finding the right automation approach

Thousands of organizations in every part of the world see the advantages of AI-driven applications to streamline their IT and business operations. A “machine-first” approach frees staff from large portions of tedious, manual tasks while reducing risk and boosting output.

AIOps for decision support and automated issue resolution in the IT department can further add to the value derived from AI in an organization’s digital transformation.

Yet conversations with customers and prospects invariably touch on a shared complaint: Enterprise leaders know AI is a powerful ally in the digital transformation journey, but the technology can seem overwhelming and takes too long to scope and shop for all the components.  They’re looking for vendors to offer easier “on-ramps” to digital transformation. They want SaaS options and the availability of quick-install packages that feature just the functions that address a specific need or use case to leap into their intelligent automation journey.

Ultimately, a highly effective approach for leveraging AI in digital transformation involves so-called Out of the Box (OOTB) solutions that package up the complexity as pre-built knowledge that’s tailored for specific kinds of use cases that matter most to the organization.

Choosing the right use cases

Digital transformations are paradoxical in that you’re modernizing the whole organization over the course of time, but it’s impossible to “boil the ocean” and do it all at once. That’s why it’s so important to choose highly strategic and impactful use cases to get the ball rolling, demonstrate early wins, and then expand more broadly across the enterprise over time. 

OOTB solutions can help pare down the complexity. But it is just as important to choose the right use cases to apply such solutions. Even companies that know automation and AIOps are necessary to optimize and scale their systems can struggle with exactly where to apply them in the enterprise to reap the most value.

By way of a cheat sheet, here are four key areas that are ripe for transformation with AI, and where the value of AIOps solutions will shine through most clearly in the form of operational and revenue gains:

IT incident and event managementA robust AIOps solution can prevent outages and enhance event governance via predictive intelligence and autonomous event management. Once implemented, such a solution can render a 360° view of all alerts across all enterprise technology stacks – leveraging machine learning to remove unwanted event noise and autonomously resolve business-critical issues.Business health monitoring – A proactive AI-driven monitoring solution can manage the health of critical processes and business transactions, such as for the retail industry, for enhanced business continuity and revenue assurance. AI-powered diagnosis techniques can continually check the health of retail stores and e-commerce sites and automatically diagnose and resolve unhealthy components. Business SLA predictions – AI can be used to predict delays in business processes, give ahead-of-time notifications, and provide recommendations to prevent outages and Service Level Agreement (SLA) violations. Such a platform can be configured for automated monitoring, with timely anomaly detection and alerts across the entire workload ecosystem.IDoc management for SAP – Intermediate Document (IDoc) management breakdowns can slow progress in transferring data or information from SAP to other systems and vice versa. An AI platform with intelligent automation techniques can identify, prioritize, and then autonomously resolve issues across the entire IDoc landscape – thereby minimizing risk, optimizing supply chain performance, and enhancing business continuity. 


Organizations pursuing digital transformation are increasingly benefiting from enhanced AI-driven capabilities like AIOps that bring new levels of IT and business operations agility to advanced, multi-cloud environments.  As these options become more widespread, enterprises at all stages of the digital journey are learning the basic formula for maximizing the return on these technology investments: They’re solving the complexity problem with SaaS-based, pre-packaged solutions; and they’re becoming more strategic in selecting use cases ideally suited for AIOps and the power of machine learning.

To get up and running fast at any stage of your digital journey, visit Digitate to learn more.

Digital Transformation, IT Leadership

IT organizations are increasingly shifting from project-based organizational structures to product-based methodologies, which involve cross-functional teams. These new building blocks of business include both tech and business pros, and they’re generally led by a product manager, who acts as the point person throughout the product’s lifecycle.

Product managers aren’t a new job category by any means, but this shift means that they’re newly prominent and important to many companies’ strategies. As a result, many corporate leaders who are used to hiring for IT now have to learn what makes a good product manager as they seek to fill these roles.

If that’s a position you find yourself in, don’t panic. We spoke to a host of experts, including product managers and those who supervise, hire, and mentor them, about what you should be looking for if you’re hiring a new PM for your team.

Seth Dobbs, CTO at IT services and consulting firm Bounteous, gives a pretty good thumbnail sketch of what an ideal product manager would look like. “This is absolutely a hybrid role and requires a good mix of skills,” he says. “They need to have enough knowledge in both technology and UX to at least be able to understand technical and experience constraints and tradeoffs, but need to be centered around business and customer value to drive decision-making around tradeoffs.”

Dobbs says he also looks for adaptability given the rapid changes that often evolve in a product-based environment, in addition to the ability to “meet deadlines, budgets, and the overall business strategy as they work through these tradeoffs,” he says. “They also need to have strong interpersonal skills and know how to lean into the experts to leverage their insights in forming a roadmap and plan, but also leverage their skills in getting the work done.”

That’s all easier said than done, of course, and in practice it’ll be hard to find a candidate who can cover all those bases. But our experts gave us some pretty good guidance on specific qualities to look for in a candidate.

Look for great communicators

Almost everyone we spoke to agreed that communications skills are a must when it comes to product management. “I can typically tell within the first 15 minutes of a phone call whether or not I’m going to hire someone,” says Cait Porte, who is chief marketing officer at software development company Digibee and has a background in product management. “The people who can articulate themselves well can translate business and technology wording and phrasing in a way my team will respond well to. Effective communicators can not only articulate themselves well, but serve as translators between business and technology, ensuring that the right solutions are at the top of the priority list.”

Tal Laufer, VP of products at cybersecurity firm Perimeter 81, explains that communication is a must-have in this job because of the role product managers play coordinating various stakeholders. “A product manager serves as a bridge in the organization. Many aspects of their work involve connecting and bridging different teams and disciplines, striving for the success of the entire company,” she says.

Seek out those who go beyond the data

Most businesses, especially in tech, pride themselves on making data-based decisions, and many of the team members a product manager will be working with will be very data-focused. That said, a product manager needs to both be able to understand what hard data is telling them — but also be comfortable making more intuitive and creative decisions. “Being technical is great — it allows you to understand the details — but it can also hold you back at times,” says Luke Gannon, product manager at graph database company Neo4j. “If you can only view things with your developer/computer scientist hat on, you run the risk of being closed off to new, creative ideas and suggestions.”

“Lots of folks are stressing metrics and being data-driven,” says Shane Quinlan, director of product management at software development firm Kion. “But in most cases, you’re starting with a dataset that’s not statistically significant — we’re not all building B2C at crazy scale. Yes, data is important. No, you don’t need to wait on perfect data to make a decision. Take chances. Make mistakes. Get messy.”

Emphasize measurable outcomes

Nothing helps attune a candidate’s intuition like experience. Holly Hester-Reilly, founder and CEO of H2R Product Science, a product management coaching and consulting firm, says that a candidate’s resume should show what they’ve done in the field — and what they’ve achieved. “The first thing a hiring manager should look for is measurable outcomes on their resume,” she says. “It’s not enough to say they’ve gone through the motions of product management. The hiring manager needs to know what tangible improvements were achieved.”

And while there may be a stereotype of fresh-faced product managers with little real-world experience, many companies will choose candidates with in-depth knowledge of the business domain in which they’ll be working, according to Stephanie White, director and head of product, technology, and professional at fintech recruiting company EC1. “Product managers who our clients hire have to be domain experts, understand how the product is being used commercially, as well as understand end-to-end product build technologically,” she says. “This is so that they can attend client meetings and sell the user experience, as an extension to the sales and propositions teams.”

Charles Paumelle, chief product officer and co-founder of Microshare, a smart building data solutions company, agrees. “Business and technical acumen is needed to answer the questions ‘Why will customers spend money on our product?’ and ‘How can our organization deliver a cost-effective solution to the customer’s needs?’” he says.

Look beyond certs and education

On the flipside, many of the experts we spoke to held formal training and education in less esteem. “Certifications are not the key to becoming a PM,” says Kion’s Quinlan. “I don’t care how many classes your previous employer paid $5,000 for, if you can’t explain simply how a website works, talk about a product that inspires you, and prioritize work with some level of objectivity, you won’t cut it.”

Digibee’s Porte goes even further than that. “Historically, jobs for product managers were reserved for MBA graduates,” she says. “As someone who both served as a hiring manager and obtained her MBA, I believe it shouldn’t be a qualification as a product manager.” It’s not that having such as degree is a bad thing per se, she says, but “people naturally think an MBA is enough of a qualification. In reality, it’s so much more than that.”

Understand your specific product-based needs

If you’re worried about finding someone who fits all of these bills perfectly, good news: In all probability you’re going to have more than one product manager at your company, and different specific roles and experience levels may be called for.

“In terms of experience, sometimes you are looking for someone who has experience in a certain market or with a certain technology, but other times you are ready to invest in someone who has the attitude and aptitude without the experience,” says Trisha Price, chief product officer at software development company Pendo. “There is no one-size-fits-all, because diverse teams with diverse experiences are what drive the best outcomes and create the best cultures.”

“There are different ‘flavors’ of PMs in practice,” says Kion’s Quinlan. “There are startup PMs, go-to-market PMs, scale PMs, design PMs, platform PMs, data PMs, and more. Someone who’s awesome at one flavor may not be the best at others (or there’ll be an adjustment period). Understanding your problem is key to hiring the right product manager. That’ll inform how you rate them on specific skills — more technical, more business-oriented, more design-oriented, a jack-of-all-trades.”

“I consider is a candidate’s ability and aspiration to be more of a ‘pioneer,’ a ‘settler’ or a ‘farmer,’” says Microshare’s Paumelle. “Product management ranges from pure innovation and R&D to create brand new products (the ‘pioneer’ heading into the unknown), to the productization of alpha products into a mainstream market (the ‘settler’ who establishes a community and builds the first structures), to the optimization of established products (the ‘farmer’ who increases the yield year after year).”

Tailor your interview process

You might be able to suss out some of this via resumes and email exchanges, but a lot of your hiring decision will come down to the interview and how the candidate does in the room (or on the Zoom, as the case may be). Our experts had plenty of advice on how to assess a candidate in an interview:

“Something we do as part of our interview process is a bit of role playing,” says Mona Ghadiri, director of product management at cybersecurity firm BlueVoyant. “Part of that is to see how they respond to role playing in general; putting yourself in someone else’s shoes is so critical as a product manager. It is also critical to see how they answer the questions and think on their feet when a problem statement is in front of them, because we are in front of customers and our peers presenting information frequently. We also ask about how they have prioritized work in the past. We’re not so much looking for them to rattle off frameworks like RICE [reach, impact, confidence, and effort] or WSJF [weighted shortest job first], but seeing if they were able to use those frameworks in a practical application.”“I ask for good, detailed examples of how they make tradeoffs against business need, user desire, and technical feasibility, and how they successfully navigate the different stakeholders to get to agreement,” says Bounteous’s Dobbs. “I’ll also typically ask them to walk me through a high-level strategy or roadmap for a product they have managed in the past. Overall, I try to understand how they think, how they have reacted in various scenarios, and how they drive things forward.”“Don’t show up unprepared,” says Kion’s Quinlan. “JIRA does not make a PM. I don’t care that you’re a wizard in JIRA. Show me you understand problems. Show me you’re thinking about ways of working. Show me you can lead a small team.”“No matter what level they are interviewing for, from entry level to senior director, I always look for a passion for solving problems for the customer,” says Dan Ciruli, VP of product management at software services provider D2iQ. “That is the number one thing I want out of a product manager. One of my favorite interview questions is, ‘Tell me about your favorite customer.’ Their answer tells me everything I need to know about how they work with customers, what inspires them, and whether or not they are truly problem solvers.”

Don’t lose sight of the intangibles

“I’m a big fan of finding the ‘raw talent’ that would make a great PM,” says Kion’s Quinlan. “For an associate product manager, the day-to-day skills can be taught, but you can’t fake or learn interest in the problem and empathy with your peers and users.” In the end, most of our experts agreed, it’s that interest in solving problems that’s the most important quality to find in a candidate for product manager.

“I went into product management coming from a hardware development background,” explains Perimeter 81’s Laufer. “Even as an engineer, I was always curious about the full picture. What do customers want? What is the market like? How can we build a better product for our customers? This curiosity and my love for working with people led me to a product focused role. I had to learn about a lot of subjects, all at once, but I had (and still have!) a blast doing so.”

She adds: “I love that part of the job, teaching young PMs how to do things right.” We hope that the product managers you find go down this same successful path.

Hiring, Project Management

Huawei kicked off its Huawei Connect 2022 tour in Bangkok as it embarks on a world tour. The massive exhibition brings together ICT leaders, experts, and partners to unleash digital productivity, build stronger digital ecosystems, and promote the digital economy.

CIO Editor Andrea Benito visited the exhibition and sat down with Derek Hao, President of Global Marketing, Huawei Enterprise Business Group, on why the key to accelerating digital transformation is matching the right technologies to the right scenarios.

Asia Pacific is leading the shift toward digital-first business process and will generate more than 30% of revenue from digital products and services by 2023, IDC predicts.

It’s not hard to see why; the degree of uncertainty created by the pandemic around workforce availability, and customer preference shifting towards online has created a set of powerful catalysts for change.

Connecting technology with transformation

Huawei Connect 2022, themed “Unleash Digital”, kicked off in Bangkok in September. The key message from Huawei was that to ensure successful digital transformation, the right technology must be selected for each scenario.

During the second day keynote on Innovative Digital Infrastructure Accelerates Digital Transformation, Bob Chen, Vice President of Huawei Enterprise Business Group, emphasised the importance of finding the right technology for the right scenario, further citing how “data is at the core of digital transformation and Huawei provides full-stack products and product portfolios to support end-to-end data processing.”

Data the key to deeper digital transformation

During our conversation, Derek Hao, President of Global Marketing, Huawei Enterprise Business Group shared that while many businesses have implemented basic workflow in a digital equivalent, fewer have taken full advantage of the data available to them to inform their processes.

According to Hao, data is key to deeper transformation and a cornerstone of Huawei’s strategy to help customers more comprehensively transform their business processes.

“Huawei believes that the way to deepen digital transformation and drive continuous innovation of industries is to ‘find technologies for scenarios’, which requires combining technologies. Data is, after all, the core of digital transformation. That’s why intelligent industry upgrades must be based on data,” Hao observes.

“To meet the requirements of different industries and specific scenarios, Huawei provides customers with a wide range of full-stack products and portfolios, covering full-stack data ingestion, transmission, storage, computing, analysis, and more, which effectively support E2E data processing,” he says.

Sector-specific solutions on display

Huawei has developed initiatives to help specific industries digitise and will be in showcasing them at Huawei Connect 2022. In the Bangkok edition, the exhibition demonstrated digital transformation cases across different industry sectors, divided into three key zones:

Industrial Digital Transformation showcased innovative applications and industry solutions in different scenarios including Education, Ports, Roads, and Electricity.

Innovative Digital Infrastructure showcased Huawei’s latest innovations across data centres, campuses, digital sites, and WANs, four types of product portfolio solutions provided by Huawei.

HUAWEI CLOUD and Eco-partners showcased HUAWEI CLOUD’s successful practices in technological innovation and ecosystem development.

Understanding customers’ challenges

According to Huawei, one of its key focuses is to work closely with customers to first understand their unique challenges, which will allow its technology subject matter experts to match the right technology solutions for different scenarios.

Huawei recently worked closely with a municipal government in an Asia Pacific country to understand its problem space and identify a series of issues in its environment, including isolated IT systems, lack of virtualised management rules, inefficient O&M, and slow response.

This enabled Huawei to build a centralised cloud platform for the customer, leveraging the HUAWEI CLOUD stack, which migrates multiple services to one cloud and ensures resources can be requested by multiple departments at the same time, improving office efficiency.

Huawei was also able to deploy a multi-data centre disaster recovery and backup system to ensure service continuity.

The result has been much-improved efficiency and stability for the systems, allowing the government workforce to improve its productivity.

Go digital in the changing environment

To assist partners with solution design, Huawei has developed more than 100 scenario-based solutions with partners covering over 10 industries.

While the pandemic is slowly resolving, the world remains a very different place from what it was before COVID-19. A set of fundamental assumptions that underpinned global trade and economies have shifted. As the world charts the uncertain path ahead, one thing is certain: businesses will have to comprehensively transform their processes toward digital to survive and thrive.

“We look forward to working with more customers and partners to dive deep into scenarios and jointly innovate to upgrade infrastructure, unleash digital, and build a fully connected, intelligent world. In the future, we are still confident in the digital development of the Asia Pacific,” says Hao.

Register today to visit Huawei Connect 2022 Dubai

Digital Transformation

Ryan Ding, President of Huawei Enterprise BG, says deeper digital transformation can help companies better deal with uncertainties.

From the rise of remote work to constant innovations in emerging technologies, the breakneck pace of global disruptions is spurring Asia Pacific’s digital growth. Take for instance the internet economy in Southeast Asia, which is expected to double to US$363 billion by 2025. This has created a clear opportunity for businesses, allowing them to ride on this wave of digitalization for seizing greater growth opportunities—as long as they play their cards right.

“The number of companies that have a digital transformation strategy was up 42% from two years ago,” says Ryan Ding, President of Huawei Enterprise BG, “Enterprise direct investment in digital transformation is set to grow at 16.5% per year over 2022 to 2024. Deeper digital transformation can help companies better deal with uncertainties.”

Bob Chen points out that data ingestion, transmission, storage, and analysis are key steps in digital transformation


“We are entering the fourth industrial revolution, where menial office tasks will be carried out by machines. The huge potential of AI in labour will play a vital role in creating wealth,” says Bob Chen, Vice President of Huawei Enterprise BG,. “Tapping into this potential will be key for an enterprise to stay competitive and for a country to develop its digital economy.”

Deepening digital transformation through scenario-based approach

This is why as digitalization continues to sweep the region, industry leaders are looking to leverage cutting-edge technologies, such as artificial intelligence (AI), 5G and the cloud, to bolster their digital transformation efforts. But this requires a marked shift away from the one-size-fits-all approach in adopting new innovations. Instead, businesses have to identify the most suitable technologies for specific scenarios, even if it means tapping on multiple solutions to address their precise needs. This is key to driving continuous, long-term innovation.

For Ryan Ding, identifying what these needs can lead to substantial results. “Using Huawei’s connectivity, and cloud technologies, we are working with our partners to drive ongoing industry innovation and multi-tech synergy, creating scenario-based solutions for diverse customer need. Together, we will create greater value and unleash the power of digital”

“In the past, power line inspectors had to walk dozens of kilometres a day with 10kg backpacks. At one power grid, their engineers inspect nearly one million kilometres of power lines each year, equivalent to walking 25 times around the earth,” he says. “To support their work, Huawei uses a combination of technologies, including solar-powered systems, optical ground wires, microwave, and Wi-Fi. Now engineers can inspect power lines remotely without leaving the office. With these technologies, power line inspection is 80 times faster, and the engineers can work more safely.”

At the same time, data remains the core of digital transformation, and the fuel behind any technology adoption strategy. If data is the new oil, then the 100 exabyte of data that’s being generated daily needs to be refined, before it can power any digitalization efforts. In other words, the data have to be collected, transmitted, stored, analysed, and processed before it’s usable. What’s more is that any improvement in this data processing cycle, no matter how small, can make great strides in helping businesses unlock new opportunities.

This philosophy is a cornerstone of Huawei’s approach to digital transformation. “Data is at the core of digital transformation, and data ingestion, transmission, storage, and analysis are key steps,” says Chen “Huawei provides full-stack data collection, transmission, storage, computing, and analysis solutions to effectively support end-to-end closed-loop data processing.”

Huawei provides full-stack data collection, transmission, storage, computing, and analysis solutions to effectively support end-to-end closed-loop data processing


By combining both data and scenario-based technologies, traditional industries can also realize their digital transformation initiatives. One example is the marine logistics and global supply chain industries, which are now embracing Fifth Generation Fixed Network (F5G)-enabled, ship-to-shore cranes to free operators from tedious, manual tasks. Engineers in the power and energy industries, too, can inspect power lines without putting their lives on the line, while carrying out their responsibilities more efficiently than before. Then there are smart solutions, which can be applied in compute-intensive scenarios, such as in medical image processing and reading, as well as network traffic security in tunnelling protocols, that can enhance key features, such as predictive capabilities and deep learning techniques.

Finding the right technology for the right scenario makes the path forward for deeper digital transformation across multiple industries.


Partnership is a key ingredient to growth

Digital technology may has redefined how industries operate, but the journey of digital growth isn’t meant to be embarked alone. Instead, partnerships are crucial to building a collaborative ecosystem that thrives on shared success, with businesses able to tap on a diversity of services at their disposal.

To better support businesses, Huawei is working with their partners to build three capabilities: consulting and planning around digital transformation, product and portfolio expertise, and solution development. “Huawei offers support to our partners on enablement, platforms, funding, and talent. Over the next three years, we will invest US$300 million to support our partners and train more talent through our ICT Academies and Huawei Authorized Learning Partners,” says Ding.

Enabling new business models through data

More than just technical innovation, digital technologies have the capacity to unlock the hidden potential for organizations across any industry. This can lead to growth across several aspects of their business, be it improved employee confidence or greater customer satisfaction. Thus by examining the unique requirements of their most complex scenarios and processes, businesses can discover the right solution against today’s rapidly changing disruptions.

These topics and more will be discussed at Huawei Connect 2022. Under the theme of “Unleash Digital”, the annual event has taken place in Bangkok on September 19, and will head to three more cities in Dubai, Paris, and Shenzhen. Several ICT products, portfolios, and solutions designed to address a variety of industry scenarios will be introduced. Through a series of summits, broadcasts and exhibitions, there will be previews of new, ground-breaking innovations, as well as best practices and results from our work with customers and partners around the world.

“Deeper digital transformation will help companies better adapt to an ever-changing world. Huawei is working closely with our partners to find the right technology for the right scenario,” says Ryan Ding, “we will support customers in furthering their digital transformation and unleash the power of digital.”

Find out more about Huawei Connect 2022 here.

Digital Transformation

As recently spotlighted at VMware Explore US, Sovereign Cloud continues to gain momentum.​ Sovereign Cloud business estimated TAM is $60B by 2025, in no small part due to the rapid increase of data privacy laws (currently 145 countries have data privacy laws) and the complexity of compliance in highly regulated industries.​

As the need to monetize data grow and nations seek to realize the true value of data, VMware is delivering on our Sovereign Cloud position: Sovereign Security, Sovereign Compliance, Sovereign Control, Sovereign Autonomy, and Sovereign Innovation.

Previously, we looked at what data sovereignty is and how it impacts business operations when it comes to personal, sensitive or classified data. Now let’s look at how an organization can better comply with data sovereignty laws by choosing the right cloud architecture.

Most businesses have moved to cloud computing for at least some of their data. Cloud provides greater flexibility, scale, and computational power than traditional on-premises data centers. While public clouds are popular for their high capacity and low costs, some organizations have started moving data out of them to comply with regulations. 81% of decision-makers in regulated industries have repatriated some or all data and workloads from public clouds.1 Some have moved data back on-premises, whereas others are using a mix of public and private clouds.  Ultimately, protecting and realizing national data has never been a more important factor in building a cloud.  From the combination of increasing country regulations:  compliance with the US Cloud Act, EU’s GDPR, China’s Personal Information protection law with data privacy laws in 132 countries and with an annual increase of ~10%, choosing the right Data Sovereignty solution has become a hot topic.

To better understand why a business may choose one cloud model over another, let’s look at the common types of cloud architectures:

Public – on-demand computing services and infrastructure managed by a third-party provider and shared with multiple organizations using the public Internet. Public clouds are usually multi-tenant, meaning multiple customers share the same server, although it’s partitioned to prevent unauthorized access. Public clouds offer large scale at low cost.Private – infrastructure is dedicated to a single user organization. A private cloud can be hosted either in an organization’s own data center, at a third-party facility, or via a private cloud provider. Private clouds are generally more secure than public due to limited access and can meet regulatory requirements such as data privacy and sovereignty. However, they require more resources to set up and maintain.Community – shared cloud that is integrated to connect multiple organizations or employees for collaboration. This can be multiple private clouds connected together to facilitate the exchange of data. These are frequently used by regulated industries where public clouds are not compliant, but they are complicated to set up due to having multiple groups involved.Government – a type of private or community cloud designed specifically for government bodies to maintain sovereignty and controlMulti-cloud – using multiple public clouds to take advantage of different features. An organization may host some services in one cloud and others with a different provider. This model has the highest level of security risk due to the volume of data and access.Hybrid – a mix of public and private clouds. The term is sometimes also used to refer to a mix of public cloud and on-premises private data centers.

While public clouds are suitable for public information that isn’t subject to data sovereignty laws, a hybrid or other more private solution is needed for overall compliance. Private clouds can meet data sovereignty requirements, but they need dedicated data centers, operated either by the organization itself or via a provider using dedicated hardware. This can be expensive and time-consuming.  The quickest or off the shelf solution may not include the level of security or compliance necessary to be sovereign.  Key factors in consideration are jurisdictional control, local oversight, data portability and customizability to name a few.

Sovereign cloud is an option designed specifically to meet data sovereignty requirements. Think of this as a semi-private cloud, combining some of the best features of public and private. They are operated by experienced cloud providers that are smaller, local, multi-tenant operations. A sovereign cloud provides the data sovereignty benefits of a private cloud without the IT headaches.

Sovereign cloud can be used in conjunction with public cloud as part of a hybrid cloud architecture. Data and services subject to data sovereignty laws would live in the sovereign cloud while non-sensitive data and services might live in the public cloud. The exchange of data between these clouds must be carefully controlled to ensure compliance.

When it comes to finding a sovereign cloud provider, customizability, flexibility and frictionless implementation is critical. You need to be able to audit operations and access to make sure compliance is maintained. Local, self-attested sovereign cloud providers can follow implement and build residency requirements correctly so that data residency and sovereignty requirements are met. Cross-border restrictions and jurisdictional control must also be understood addressing privacy concerns with no remote processing of data.  At the end of the day, true sovereignty ensures that other jurisdictions are unable to assets authority over data stored beyond national borders; fostering national data interest and growth.

True Sovereign Clouds require a higher level of protection and risk management for data and metadata than a typical public cloud. Metadata, or information about the data such as IP addresses or host names, must be protected along with the data itself.  VMware Sovereign Cloud providers  offer transparency around security measures, both cybersecurity protections and physical security in the data center.

VMware Sovereign Cloud providers  are…

trusted approved partners in providing best in class IaaS Security and complianceexperts in local platform builds as well as local data protection lawsable to provide solutions for data choice and control, cost efficient (TCO) solutions that are flexible and customizableable to grow with customer needs providing a complete solution that is future proof  

Customers requiring sovereign solutions demand the expertise and transparency offered by VMware Sovereign Cloud providers…ensuring  security and compliance with local data privacy and sovereignty laws. This expertise and transparency becomes invaluable, enabling  data  security and compliance.

Find your Sovereign Cloud provider today, check out the latest VMware Sovereign Cloud Infographic or join the conversation via our Linkedin community at  VMware Sovereign Cloud | Groups | LinkedIn

Source: IDC, commissioned by VMware, Deploying the Right Data to the Right Cloud in Regulated Industries, June 2021

Cloud Computing, Data Management, IT Leadership

To make a profit, manufacturers need more visibility into the cost of goods to sell at a price that reflects the value to customers. And that transparency has been lacking to date. From flour to fuel – and now baby formula – the cost of commodities has skyrocketed while availability has plummeted and no one knows when things will turn around.

Clearly, things have gotten out of control. So the leaders at Clariant International, a leading specialty chemical company, decided to build a tool that would monitor and analyze future price changes on finished goods instantly so they could make pricing decisions that pass-through costs to the value chain.

What does a specialty chemical company make?

Modern chemistry delvers solutions and revolutionary products, and Clariant supports global production in everything from home care to vehicles, energy, electronics, mining, agriculture, and cosmetics – even your kid’s brightly colored toys (with safe, stable paint) to the stain-trapping polymers that protect their favorite Star Wars t-shirts.

Plus, to feed a hungry world with higher crop yields, there are “adjuvants” – biological enhancers of herbicides and pesticides that increase effectiveness and sustainability by preventing wind drift in farmers’ fields.

Development is a cause for celebration but getting revolutionary products into the market quickly is another. Here’s how Clariant — an SAP Innovation Award Winner — built a cost forecasting tool that simulates costs end-to-end from procurement and operations, to finance and sales.

In the chemical production industry, nothing stands still

Clariant’s legacy solution for pricing simulation allowed only a single, manual simulation that took several weeks to process making it outdated by the time it reached the business decision makers.

The need for real-time pricing forecasts was driven by the costing complexity of bills of materials (BOMs) and finished products from multiple group companies – not to mention currencies based on tens of thousands of raw materials operating in volatile markets around the world.

Clariant required a robust product costing solution that could simulate finished goods costs for multiple scenarios using data from a wide array of sources. It also needed to offer intuitive reporting and analytics that procurement teams could apply instantly to resolve the many challenges they were facing.

But the biggest drawback for the forecasters was the cumbersome, labor demanding, and error-prone calculation required for 20,000 finished goods, 50,000 materials used, 18 production levels, 67 production sites, and 18 months of forecast simulation.

To move this mountain, Clariant built an end-to-end cost simulation forecasting tool with full visibility to enable proactive pricing and margin management across a variety of factors.

100X Faster –Value-Driven ROI in minutes instead of days

The company based its end-to-end forecasting tool on a production benchmarking and simulation engine from MIBCON NDC built on SAP S/4HANA and SAP Analytics Cloud with robust data processing, system stability, and user-friendly dashboard reporting and analytics. The return on investment for the entire project was realized in just three weeks!

From one manual simulation per quarter to instant forecasting, Clariant’s pricing simulations are 100 times faster than before.

“We can run forecasts almost immediately and provide updated pricing quickly,” says Markus Mirgeler, head of procurement, Clariant. “This shows up in higher margins and better product volume, differentiating us from the competition.”

Instant transparency

The ability to analyze the full production portfolio instantly, based on detailed bills of materials (BOMs) ensures accuracy. Plus, identifying products that require given raw materials, and the systematic collection of future raw material prices, any time, affords flexibility as things change.

Now, sales can rely on a single source of truth for global pricing forecasts that support the bottom line while significantly reducing the possibility of error. With less time needed to obtain the actual and input data as well as for planning and preparation, and empowered by self-service reporting and advanced visualizations, sales can analyze the value chain with pricing simulations and produce reports in minutes instead of days. 

And last but not least, the transparency of cost changes is passed onto customers so they can see the value.

To learn more about the challenges Clariant faced, and the actions the company took that placed them as a winner of the SAP Innovation Awards, read their Innovation Awards pitch deck

Digital Transformation

Integrating a new network after an acquisition can be a sizable headache for any CIO. But for Koch Industries, a $125 billion global conglomerate that has acquired five companies in two years, including Infor for $13 billion in 2020, connecting those acquisitions’ networks to its own sprawling network has been a challenge of another magnitude.

Traditionally, to integrate its acquisitions, Koch would flatten the acquired company’s core network, says Matt Hoag, CTO of business solutions at Koch. While this approach makes connecting the network easier, it is a slow, arduous endeavor that gets more complex as more companies are acquired, he says.

Moreover, Koch itself is in the middle of a digital transformation that adds cloud networking to the mix, further complicating the challenge. Cloud networking comprises three layers: first from on-premises data centers to the cloud, then within a cloud that has multiple accounts or virtual private clouds, and finally, between individual clouds in a multicloud environment. It’s more complicated than standard networking, Hoag says.

“Cloud deployments typically come in the form of multiple accounts, including multiple LAN segments that need to be connected. This encompasses not only VMs but also many other services offered by the cloud provider,” he says.

The major tasks involved range from deploying core IP routing, to enabling connections among virtual workloads within a multitenant cloud, to connecting multiple clouds, to ensuring remote users can connect to the company’s cloud estate. It’s the kind of challenge few, if any, enterprises can take on without a partner today, analysts contend.

Laying the foundation

Koch Industries began its migration to Amazon Web Services in 2015, when it also started on the first layer of its cloud networking strategy.

Matt Hoag, CTO of business solutions, Koch Industries

Koch Industries

Leased lines and direct connects would remain in the data center as part of this strategy, but Hoag did not want to route users through the data center to access data on the cloud. Instead, Koch’s engineering team set about virtualizing the physical transports to build the SD-LAN and firewall within the cloud rather than in the data center.

The company invested a hefty amount of time — roughly 18 months — and engineering resources just to bring on-premises networking to the cloud. “It was more of a challenge than I thought it was going to be in the early days,” Hoag says.

For the second two layers of Koch’s cloud network infrastructure, Hoag partnered up with a specialist.

IDC analyst Brad Casemore notes that there are several multicloud networking suppliers, including Aviatrix, Alkira, F5 Networks, and Prosimo, as well as established datacenter SDN suppliers such as VMware, Cisco, and Juniper. Co-location providers that offer interconnection-oriented architectures — such as Equinix, Digital Realty, and CoreSite — partner with many of these suppliers.

Hoag brought in Alkira to help tackle the challenge.

When building out one portion of a transport construct, the CTO recalls an ‘aha’ moment that he had one afternoon in a conference room in Reno, Nev., with Alkira: Using a third-party platform to handle the abstraction of networking into a software service would vastly reduce the complexity for his own IT team.

Alkira’s network segmentation and resource sharing approach would enable Koch to unify its on-premises and multicloud networks with a few clicks of the mouse, Hoag says. So his team set about migrating the first layer of cloud networking it built from scratch to work within Alkira’s platform.

“Prior to Alkira, anytime we acquired a new company, it would take 12 to 24 months to integrate their network due to the massive complexity,” Hoag says. “Now, we can set policy and have the entire network abide within 24 hours.”

Modernizing the network

Hybrid and multicloud networking, such as Koch’s, represents the next level of cloud maturity, says IDC’s Casemore, who adds that it’s a category in which most enterprises are woefully behind.

“While compute and storage infrastructure have largely aligned with cloud principles and the needs of multicloud environments,” Casemore says, “the network has not kept pace. ”

For Casemore, network modernization is indispensable to multicloud success: “Enterprises often are not fully cognizant of their networks’ multicloud deficiencies and limitations until they experience them firsthand. By then, the network’s inability to accommodate new requirements has often compromised the realization of an organization’s digital business strategy,” he says.

Here, Hoag says, partnering can be beneficial, as third-party specialists such as Alkira have a deep understanding of cloud providers’ obscure but significant technical differences. Working with a partner can also vastly reduce maintenance and troubleshooting, Hoag says, adding that to date Koch is enjoying similar data transfer speeds in all three layers of its cloud networking architecture.

Koch’s partnership with Alkira has also enabled the CTO to build up his team’s cloud networking skills.

“There is a talent war going on,” Hoag says. “This helps us move our team up the talent chain so they can focus on working with applications teams in the company and produce much better business outcomes.”

Enterprise Management Associates analyst Shamus McGillicuddy agrees that most enterprise CIOs will need to tap a specialist to achieve seamless cloud networking — one of the final phases of their digital infrastructure.

“Building a network across multiple cloud providers and one or more private data centers is too complex because network and security teams have to use different tools depending on which cloud or data center they’re working with,” McGillicuddy says. “This solution is an overlay that removes this complexity.”

By abstracting the various networking and security features different cloud providers offer, enterprises “can manage everything from one place, with one set of design parameters, one set of network and security policies, and one console for operational monitoring and management,” he says.

One day, setting up cloud networking may be as easy as using a credit card to set up a cloud instance, Hoag says. But not now. “When you start to have the kind of user needs to potentially have connectivity between different clouds, that’s more difficult,” the CTO says.

Cloud Computing, Hybrid Cloud, Multi Cloud, Networking

Great teams incorporate a variety of skill sets. For example, a football team consisting of 11 quarterbacks would get crushed in a game against talented linemen, running backs and receivers. It’s no different when building a team for an enterprise AI project; you can’t just throw a bunch of data scientists into a room and expect them to come up with a revenue-generating or efficiency-improving project without support from other members of the enterprise.

Interestingly, many companies do just that, creating a disconnect between data science teams and IT/DevOps when it comes to AI development. This gap is a significant reason why AI pilot projects fail.

“AI projects are a team sport and should include a multidisciplinary team spanning business analysts, data engineering, data science, application development, and IT operations and security,” according to  Moor Insights & Strategy in a September 2021 report titled “Hybrid Cloud is the Right Infrastructure for Scaling Enterprise AI.”

The biggest divide between data scientists and IT often centers around the tools necessary to develop AI models.

“Many IT organizations try to build a killer, one-stop solution that fits all needs,” says Michael Balint, principal product architect at NVIDIA. For example, many prefer to develop with deep learning frameworks such as PyTorch on a dedicated system, while others schedule their work using Slurm or Kubeflow. IT is often left scratching their heads about how they can consolidate everything into one solution.”

Yet, this can be a disaster when it comes to AI projects, Balint warns. “This is such a nascent area that if you’re in IT and you try to pull the trigger on one solution, you might be missing out on functionality that a data scientist or data engineer might need to get their job done. Data scientists would really love to just build models and do real core data science. They get frustrated when they don’t have the tools to do that, and the blame gets put on IT.”

MLOps to the rescue

The better approach is to have IT work with the data science groups on bridging the gap through processes and tools such as MLOps. These can provide enterprises with governance, security and collaboration through features such as tracking and repeatability. MLOps platforms can orchestrate the collection of artifacts, compute infrastructure and processes that are needed to deploy and maintain AI-based models. Many MLOps systems can also evaluate the accuracy of models in order to retrain and redeploy as needed.

“Organizations can increase the percentage of models that are successfully deployed in production by implementing MLOps tooling, which aids in managing data science users, data, model versions, and experiments,” says Moor Insights. “The tooling should also allow IT teams to manage the develop-to-deploy cycle with the same DevOps rigor as traditional enterprise apps.”

This approach can help companies bridge the divide between the data and IT sides.

“A few years ago there was emphasis on deep learning engineers and data scientists as the heroes of the industry,” says Balint. “I think the unsung heroes are the DevOps and MLOps engineers that sit in the IT group, because you need to build the right solutions and stacks for everybody else to do their job. If you don’t have that, you can’t move very quickly.”

Go here to get more information about AI model development using DGXTM-Ready Software on NVIDIA DGX Systems, powered by DGX A100 Tensor core GPUs and AMD EPYCTM CPUs.

Artificial Intelligence, IT Leadership

Halkbank, founded in 1993, is one of the largest banks in Türkiye, offering corporate and retail banking, investor relations, and SME and commercial services to over 15 million customers. But during the pandemic lockdowns, customers were forced to switch to the bank’s digital channels, and mobile app users quickly soared from one million to 2.5 million.

Since the pandemic, however, this increase in digital customers hasn’t been entirely smooth. The bank recognized the need to scale its mobile banking platform to handle more than double the volume of traffic.

Namik Kemal Uçkan, head of IT operations at Halkbank, lists challenges created in different areas, including prioritizing network availability when traffic volumes surge; making services in high demand available during peaks; ensuring speedy resolution and identification of network issues; having a sufficient capacity of network monitoring solutions; and ensuring faster incident resolutions and troubleshooting across the networks.

As a result, increasing complexity inside the enterprise IT ecosystem has been constant, and managing networks that support it, while always important, have become critical to address.

Over the last 10 years, Halkbank has been using Riverbed SteelHead across more than 1,000 branches for WAN optimization, and network and application performance. Riverbed’s solutions have helped to ensure Halkbank’s business critical applications are always available for its business users.

“Riverbed SteelHead has been used to accelerate the performance of the internal banking applications that are utilized by its own employees,” says Mena Migally, regional VP, META, at Riverbed. “By deploying this solution, they’ve reduced the latency for applications at branch offices while also realizing bandwidth savings.”

Banking, CIO, Digital Transformation