Currently, many enterprises still focus on tower-based security (that is, securing the “home”)—securing networks, datacenter, databases, endpoints, applications and middleware and then applying horizontal security solutions for rights management, policy, access management and authentication. The overarching framework creates a secure environment, but fails to prevent breaches by insiders or by external threat actors that have seized credentials or exploited the hundreds of vulnerabilities in every domain at any given time. The crown jewels—specifically data representing client information, contracts, legal documents, employee information, KYC files and other pertinent information—must remain secure and private, even if the credentials are breached, or vulnerabilities lead to breach in the networks, data centers or endpoints. Particularly in this era of increased cyber risk, along with growing reliance on data across every industry, enterprise leaders should consider this level of security and privacy, and this ease of access, as non-negotiable for keeping their valuable data and digital assets safe.

The European Commission will now carry out an in-depth investigation into whether Microsoft may have breached EU competition rules by tying or bundling Microsoft Teams to its Office 365 and Microsoft 365 productivity suites. “Remote communication and collaboration tools like Teams have become indispensable for many businesses in Europe,” explains Margrethe Vestager, executive vice-president in charge of competition policy at the European Commission. “We must therefore ensure that the markets for these products remain competitive, and companies are free to choose the products that best meet their needs. This is why we are investigating whether Microsoft’s tying of its productivity suites with Teams may be in breach of EU competition rules.” Microsoft has responded to the EU’s complaint. “We respect the European Commission’s work on this case and take our own responsibilities very seriously,” says Microsoft spokesperson Robin Koch, in a statement to The Verge.

You might think that your software stack has nothing to do with your build system; However, the build configurations you select may dictate how your software is organized. After all, building to simulate your application code shouldn’t include low-level target drivers. In fact, you may find that even the middleware you use is entirely different! Defining your ideal build configurations may impact your software stack and vice versa. A modern embedded software stack will include several layers of independent software that are glued together through HALs and API’s. ... Today, are you using your ideal build system? Do you even know what that ideal build system looks like and the benefits it creates for your team? I highly recommend that you take a few minutes to answer these questions. If you don’t have an ideal build system you’re trying to reach, you can easily define your ideal system in 30 minutes or less. Once you have your ideal build system, look at where your build system is today. If it’s not your ideal system, don’t fret! Define some simple goals with deadlines and work on creating your ideal build system.

Data centers and the Cloud grew up on a single, monolithic approach to computing — one size fits all. That worked in the days when workloads were relatively few and very straightforward. But as cloud adoption exploded, so too have the number and types of workloads that users require. A one-size-fits-all environment just isn’t flexible enough for users to be able to run the types of workloads they want in the most effective and cost-efficient manner. Today, technologies have emerged to overthrow the old paradigm and give developers and cloud providers what they need: flexibility and choice. One of its manifestations is multi-architecture, the ability of a cloud platform or service to support more than one legacy architecture and offer developers the flexibility to choose. Flexibility to run workloads on the architecture of your choice is important for organizations for two reasons: better price performance and — a reason that is far downstream from data centers but nevertheless important — laptops and mobile devices. 

AI-driven coders learn from existing code repositories. They often need a more contextual understanding of the code generated. They produce code that works but may need help to comprehend or maintain. This hinders developers’ control over their software and often causes mistakes when fixing or changing applications. Moreover, the generated code must meet style conventions or best practices and include appropriate error handling. This can make debugging, maintenance, and collaboration difficult. Remember that AI-driven code generation focuses on learning from existing code patterns to generate net-new code. Generative AI coders have a “monkey see, monkey do” approach to development, whereas the coding approaches are learned from the vast amount of code used as training data. This approach is helpful for repetitive or standard tasks, which is much of what developers do, but enterprises may require more creativity and innovation for complex or unique problems.

"We have seen a belated -- but much required -- resurgence in the interest in data quality and supporting capabilities," Ghai said. "Generative AI may be one of the factors. But also organizations are realizing that their data is the only sustainable moat, and without data quality, this moat is not that strong." Tied in with data quality and observability, which fall under the purview of data governance, Ghai added that data privacy continues to gain importance. "There's a growing focus on building analytics with strong privacy protection via techniques like confidential computing and differential privacy," he said. ... Like Ghai, Petrie noted that many organizations are prioritizing data quality -- and overall data governance -- as their data volume grows and fuels new use cases, including generative AI. "AI creates exciting possibilities," he said. "But without accurate and governed data, it will not generate the expected business results. I believe this realization will prompt companies to renew their investments in product categories such as data observability, master data management and data governance platforms."

Where the head of the enterprise design sits in the organizational hierarchy depends on various factors, Heiligenthal said. Company size and maturity play a role, but typically, she said, it starts in marketing and lands within product, digital and technology groups. “Organizations can be matrixed or hierarchically structured, and success depends on visibility within the organization. The further the design organization is buried, the harder it is to receive buy-in and get work done,” she explained. A struggle that many enterprises come up against, she said, is how and where the design organization sits. “Is it centralized, decentralized or embedded within products?” Each setup has its own benefits and drawbacks, but what’s worked for her is a centralized partnership; one with a distinct, centralized design team that shares a sense of purpose with various product and business teams. “It’s a hub-and-spoke model that centralizes design teams (the hub) and gives us freedom to execute across the organization (the spokes) based on north-star alignment across the business.”

When implemented strategically and with the needs of an organisation at the forefront, intelligent automation can support collaboration, communication and new, modern ways of working, not only contributing to increased efficiency and cost-effectiveness, but also boosting employee experience. In particular, the elimination of repetitive, manual and time-intensive administrative work – which is often cited as one of the main factors of public sector job dissatisfaction – can help with retaining key talent within the sector. Along with meeting employee expectations, strategic deployment of automation also helps public bodies to keep pace with the expectations of the general public. Automation allows citizens to access support more effectively, without the need for human intervention, especially in the case of adult social services, being resource-intensive centres that manage access to help and support across many key areas such as pensions, healthcare and benefits. 

Cloud Computing Services: Revolutionizing Data Management in Telecommunications

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Quote for the day:

"Leaders are the ones who keep faith with the past, keep step with the present, and keep the promise to posterity." -- Harold J. Seymour

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