Information Week

“Future-Ready Database Estates: Strategies for Modernization and Migration“ Thursday, November 7, 2024 at 1:00pm ET In today’s fast-paced digital landscape, modernizing your database estate is essential for agility, security, and performance. Join us for an informative webinar that delves into the latest strategies and tools for successfully modernizing your databases. We’ll start by exploring how to safely and securely adopt open-source Postgres with EDB, guiding you through the essential steps of the migration journey. Next, Nutanix will share insights on simplifying database operations, streamlining management tasks, and enhancing overall efficiency. Finally, Prolifics will provide expert advice on managing database migration projects, offering tools and best practices to ensure a smooth transition. Whether you’re considering a shift to open-source solutions, seeking to optimize your database operations, or navigating the complexities of migration, this webinar will equip you with the knowledge and resources to modernize your database estate effectively. Don’t miss this opportunity to transform your approach to database management. Speakers:Julian Moffett, VP Strategic Alliances, EDBJulian has 15+ years of experience working in the Financial Services sector in various different roles from: Infrastructure engineering, Product and Service Management to Business Application Development Lead and CTO / Enterprise Architect. Most recently Julian has been responsible for designing and building out enterprise scale Postgres managed services on premise and in cloud and managing an Oracle Exit initiative. In his current role as VP of Strategic Alliances Julian plays a crucial role in fostering and managing partnerships that drive growth and innovation for EDB’s customers.  Academically Julian comes from a Legal background (LLB, LPC) but has worked in technology all his professional career. Julian is TOGAF 9 certified. Jamie Frampton, UKI Sales Lead, Nutanix Database Service (NDB)Jamie is responsible for Nutanix’s Database-as-a-Service solution Nutanix Database Service(NDB) which offers automated database operation across multiple database engines, wherever you need to run them. Jamie has experience with clients running traditional RDBMS solutions such as Oracle and SQL Server, as well as modern Opensource database engines such as Postgres and MongoDB. Jamie has been looking after NDB across UK&I for the last 2 years and has previous experience of document databases working at MongoDB, as well as working with clients at IBM across integration. Peter McCullagh, Sales Executive, ProlificsPeter is a Database Migration and Decision Optimization Specialist. He works with clients on data projects to enhance their business. Typical projects are along the lines of the following:● Database Migrations – Using the Automated Database Agnostic Migrator (ADAM) service from Prolifics, Pete is able to automate a large component of database migrations. This allows Pete to offer lower risk and lower cost migrations. Typically, businesses are doing this to reduce license costs, and/or to facilitate a move to the cloud.● Decision Optimization – Using advanced technologies to assist customers with complex business decisions involving many large data sources, multiple trade-off possibilities and complex constraints.● General Data Services – With over a decade of experience in the data space, Pete is able to advise on nearly all data topics, as well as providing specialist consultants to help clients take their vision from the whiteboard to the metaverse. Moderator:Peter Krass, InformationWeek  Offered Free by: EnterpriseDB See All Resources from: EnterpriseDB source

Frustrations with generative artificial intelligence flaws run high and solutions are in high demand. First came the move from large language models to small language models to curb errors through data and task specializations. Then came mini model versions. Now there are highly specialized autonomous AI agents (bots) that work in teams called multi-agent systems.   “This shift leverages specialized AI agents to handle narrow tasks more accurately and cost-effectively, as each agent doesn’t need to be state-of-the-art but simply good enough for its specific role,” says Jesal Gadhia, head of engineering at Thoughtful AI.   The applications for multi-agents appear limitless but they are not a panacea for all AI use cases.  “It’s worth noting that while agents are an important piece of the AI puzzle, they do not replace some LLM-based GenAI tools, nor do they replace predictive AI/ML tools,” says Paul Harmon, senior manager, data science, at Atrium, a consulting firm for data, CRM, and analytics/AI.   “In some cases, AI-based tools may be better used to augment humans, providing insights and recommendations — in such cases an agent may not be needed. But in cases where AI-driven actions can replace rote tasks, agents can provide some significant productivity gains,” says Harmon, who’s also a distinguished member of the American Society for AI.  Related:The Rise of Autonomous AI Agents Ultimately, the concept is to leverage a blend of AI models and data to create a more powerful and targeted mix of tools to handle even the most complex and delicate tasks. For example, consider multi-agents in a customer care scenario for a telco company.   “Because the care agent and network agents leverage different domain-specific contexts, and may also leverage different underlying models and infrastructure, the outcome will theoretically be the ‘best of both worlds’ in terms of accuracy and speed,” says Anthony Goonetilleke, group president, technology and head of strategy at Amdocs, an Israeli multinational telecommunications technology company. “From an end-user perspective, their experience will be more fulfilling as they will not only simplify their care interaction, but also realize a meaningful outcome from the interaction in significantly faster time.”   So much for the high view, let’s now take a closer look at what all of this means to the rest of us:  1. Seismic shift from application to system integrations   Companies are eager to move beyond using GenAI in improving employee productivity to tackle complex use cases but they’re mostly hitting a wall in the process. It won’t be until most or all of an organization’s technology is fully integrated by AI bots that the real magic will occur, let alone at scale.  Related:Is This the End of Mass Production in Everything From Education To Manufacturing? “Today, the challenge for GenAI is that business operations are integrated, but software systems are not,” says Babak Hodjat, CTO of AI at Cognizant. “Multi-agent architectures create a “system of systems” that allows LLMs to interact with one another. AI agents — generative AI LLMs wrapped around any software, function, module, or app — interact with one another within this network, functioning as a virtual working group that can analyze prompts and draw information from across the business. The result? A comprehensive solution not just for the original requestor, but for other teams as well.”  2. Shift of artificial thinking from one agent to a hive mind  GenAI flaws and limitations are glaringly evident. Among them is difficulty in managing complex tasks and long, complicated inputs. Switching from one GenAI tool or “single agent” approach to a “multi-agent” approach instead enables a collection of AIs to each focus on a single task that they can do well.  “The limitations of single agent AI in handling complex, multifaceted tasks have become apparent,” says Loris Degioanni, founder and CTO at real-time cloud security firm, Sysdig. “This inherent limitation has driven a shift towards agentic AI, where multiple agents work collaboratively, much like human teams. This shift is also fueled by advancements in AI technologies that enable more sophisticated coordination and decision-making across agents, and 2024 has become the year when these systems have gained widespread recognition.”   Related:AI and Quantum Computing: High Risks or Big Boons to Fintech? 3. Multi-agents already exist but largely haven’t joined forces yet  Use them if you’ve got them, right? Multi-agents are “out there” they just aren’t organized yet in bigger systems. It’s not that doing so is necessarily an easy task, it’s just that it would be a terrible waste of potential if no one bothered to do so.  “In some ways, multi-agent architectures are already here,” says Deon Nicholas, CEO of Forethought AI. “Most systems are leveraging dozens of separate prompts under the hood, so in a sense these systems are already multi-agent. Unlike humans where each human has a distinct separate consciousness, it’s all kind of working in concert … For example, at Forethought, we have one agent for resolving customer service issues, and a completely separate agent for evaluating the quality of the conversations. This ‘supervisor’ or ‘evaluator’ agent is being used to check the answers of the first, generate further insights, and even provide policy updates for future training of the model. To the customer, it all appears as one cohesive ‘agentic’ system,” Nicolas says.   4. Multi-agent systems won’t replace single-agent applications  The switch to multi-agent systems will not trash any former investments in single agent applications. For example, if your company has already built a GenAI chatbot for HR and another one for customer service, you get to keep using them. Similarly, any investment made by any stakeholder can be protected and bolstered.  “AI can help optimize or create compromise for data gathering — specifically where satellite vs. drone vs. individually gathered sampling is acceptable or required. It is a complicated space with many views. A multi-agent model can ensure each stakeholder has control over their own reasoning and needs,” says Yvette Kanouff, partner at JC2 Ventures.  Kanouff points to the use of AI in land reclamation for mines, oil, and gas

Zoom Workplace vs. Microsoft Teams: Which is best for your organization? source

As financial institutions explore the potential efficiencies of in-house AI deployment, the trend could change the role fintech startups play as purveyors of innovation. The nimble, boundary-pushing nature of startups often means they dabble in novel ideas before incumbents. The more that organizations great and small inject AI into their ecosystems, does it reduce the interest on startups to drive new efficiencies and concepts? In this episode of DOS Won’t Hunt, Angela Friend, vice president of data science and AI with DailyPay; Adnan Masood, chief AI architect with UST; and John Lin, investor with F-Prime Capital, discuss how the spread of AI among incumbent financial institutions might affect their pursuit of innovation through startups. As efficiencies of AI continue to be touted, do incumbent financial institutions still need smaller, nimble startups to catalyze innovation? What are some common pain points financial institutions want to solve via technology? And how might startups try to speak to those pain points in ways large incumbents cannot? Listen to the full podcast here. source

The cloud skills gap is one of the most significant challenges facing the tech industry today. IT leaders are grappling with a shortage of cloud-competent professionals, which is slowing down innovation and preventing organizations from fully leveraging cloud technologies.   To remain competitive in a rapidly evolving landscape, it’s critical for IT leaders to address this gap by prioritizing upskilling initiatives that equip their teams with the expertise needed to meet cloud demands.  Recent data shows that roughly 90% of tech workers under the age of 25 are considering new career opportunities, underscoring the need for skilled cloud professionals. Without strategic intervention, organizations risk missing out on the talent and innovation required to thrive in today’s cloud-driven world.  The Case for Cloud-Focused Upskilling  By providing both new and current employees with the skills to take advantage of emerging IT practices, upskilling can help bridge the cloud skills gap. Importantly, the prioritization of upskilling helps IT leaders meet cloud demands while supporting the growth of the next generation of tech workers.  But despite the clear need for upskilling, fewer than 20% of company leaders report progress on these initiatives. Many struggle due to limited resources, insufficient buy-in from leadership, and low employee motivation. Combined with the rapid evolution of cloud technologies, this creates a bottleneck in cloud deployments, making it even more difficult to meet demand.  Related:2024 InformationWeek US IT Salary Report: Profits, Layoffs, and the Continued Rise of AI The solution lies in making upskilling a higher priority. IT leaders must advocate for the value of upskilling, not just as a means of solving the skills gap, but as a driver of future growth and innovation.  Champion Upskilling to Strengthen Your Organization  Building a successful upskilling program takes more than just providing training — it requires a cultural shift within the organization that embraces continuous learning and development. Here’s how to get started.  1. Educate your organization on upskilling benefits  To gain internal support, it’s crucial to highlight the long-term benefits of upskilling to employees and leadership alike. Upskilling can lead to improved efficiency, stronger data security, and more seamless cloud integration — advantages that can keep your organization ahead of the curve in the competitive tech landscape.  By showcasing how upskilling empowers teams to leverage cloud technology more effectively, you can make a compelling case for prioritizing training initiatives.  Related:Forrester Speaker Sneak Peek: Analyst Jayesh Chaurasia to Talk AI Data Readiness 2. Secure C-suite buy-in for cloud upskilling programs  The key to any successful initiative is leadership buy-in. Demonstrating the potential return on investment of upskilling initiatives can help secure the support you need from the C-suite.   Focus on how upskilling can lower operational costs, boost productivity, and create a more agile workforce capable of driving innovation. Citing success stories from organizations that have benefited from upskilling can also provide valuable examples of its impact.  3. Focus on Gen Z talent to drive cloud innovation  Gen Z professionals bring a unique advantage to cloud upskilling initiatives — they are the first generation to have grown up with digital technologies and are naturally more adaptable to new tools and platforms.   Engaging younger workers through upskilling programs not only helps close the cloud skills gap but also ensures your organization is nurturing the next generation of tech leaders.  4. Develop a supportive work culture for upskilling  Gen Z professionals are drawn to organizations that prioritize growth and development. Offering clear pathways for cloud-related upskilling not only enhances employee engagement but also ensures your organization retains the talent needed to stay competitive in a cloud-first world.  Related:The Impact of AI Skills on Hiring and Career Advancement Embrace a Cloud-First Future With Upskilling  Closing the cloud skills gap is no small task, but with a clear focus on upskilling, IT leaders can equip their teams with the expertise needed to thrive in a cloud-first world. By prioritizing training initiatives and fostering a supportive work environment, organizations can bridge the gap, drive innovation, and ensure sustainable growth in the ever-evolving tech landscape.  source

The wide-scale introduction of artificial intelligence sent shockwaves through every industry, as it disrupted the way we live, work, and even learn. In the education sphere specifically, it’s caused traditional educators to experience a “Gutenberg printing press shock,” as much of their skills have essentially become obsolete overnight. AI’s quick rise has raised fear of risks such as plagiarism and lessened student engagement, causing many learning institutions to restrict or in some cases even ban the technology from classrooms. While we acknowledge and understand the potential risks associated with AI, I believe there is a lot more opportunity for the good of humanity than harm — if harnessed properly and responsibly, this groundbreaking technology has the potential to support and augment students’ learning exponentially — much like the printed book, the calculator, or the computer has done for previous generations. So, the question is not if we should harness AI, but how we should harness AI. It’s clear the technology needs guardrails. In fact, many groups from government officials and business leaders to celebrities like Tom Hanks have joined the debate on AI regulation. Yet, world leaders have been slow to act, and efforts have been restricted to national and regional spheres Related:The Blinking of ChatGPT Why the reluctance and the emphasis on local perspectives? Even during the peak of the Cold War, opposing factions aimed for international consensus, especially on ethical norms or ‘red lines’ related to nuclear weapon usage. Some theorize that this hesitancy toward AI regulation stems largely from their insufficient grasp of the technology and its ramifications. Why wouldn’t we engage the generation that seamlessly integrates AI into their daily routines? Undoubtedly, they not only have viewpoints on the matter but can also provide a more expansive and insightful perspective on the ethics of the technology. A proactive group of international students aged 13 to 18 from Institut auf dem Rosenberg decided to take the initiative and developed a 13-point charter to govern AI, calling for world leaders to promptly regulate AI development and usage through an international treaty and regulatory agency. A selection of the students’ proposed guardrails as a seed for global accord include: Control input and output. All organizations, whether private or state, engaged in designing, engineering, and/or distributing AI products, shall be held unequivocally accountable for the information generated by AI systems. These organizations must establish specialized departments amalgamating human oversight and automated technologies grounded in machine learning to guarantee the responsible utilization of AI. An external, impartial global agency shall meticulously oversee and ensure strict adherence to proper AI usage, conferring AI-Safe-Use approval badges exclusively upon organizations that diligently comply with AI standards. Transparent tracing of sources. Complete transparency in acknowledging the entities responsible for AI processes is imperative. Therefore, all AI-processed information must be transparently traceable to its origins, specifically attributing it to the entities conducting the information processing using AI. Users shall enjoy unrestricted access to all original input data employed by AI systems. Violations of source tracing obligations will be met with resolute legal enforcement. Regulation of deepfakes. Mandatory watermarks or detectable patterns are recommended for all deepfake or artificially created content. We advocate increased investment in deepfake detection technologies. Unethical deepfake actions, including defamation and identity theft, must be unequivocally prosecutable offenses. AI systems shall rigorously maintain accessible interaction histories, with AI software manufacturers being legally accountable for verifying the origin of disseminated information. Prevention of monopolies and duopolies. In the pursuit of equitable AI development and access, signatory parties solemnly pledge to actively champion diversity and counteract monopolies, duopolies, or oligopolies within the AI creative sphere. This commitment aims to foster innovation, fairness, and global collaboration. Support for cultural and academic endeavors. AI programs must be designed exclusively to support cultural and academic creators, refraining from autonomous generation of cultural and academic content. The excerpts provided are just a glimpse into the thorough work of our students. The question about ethics in AI is one that has the potential to bring together a polarized world for the greater good of all mankind — it is an opportunity that we should give the next generation. For a detailed insight into the Rosenberg AI Charter and this significant project, please visit here. source

While hype over artificial intelligence may be spurring organizations to hire professionals with matching skills to maintain a competitive edge, many businesses have more fundamental IT talent gaps.    An April survey of 1,400 executives and IT professionals found skills gaps throughout cybersecurity, cloud, and software development — along with interest in skill development for these areas for 2025.   In fact, understanding tech skills gaps is something many organizations struggle with — just a third of executives surveyed said they completely understand their organization’s skills gaps, and 68% of technologists say that business leaders aren’t aware of their IT skills gaps.   Chris Herbert, chief content officer at Pluralsight, says to combat this lack of knowledge, business leaders need a data-driven approach to uncovering skills gaps.  “This can be in the form of tech skills assessments, which can benchmark where technologists fall on a sliding scale of expertise in a given tech skill,” he says.  He adds that it can be useful to survey tech teams internally in areas where they feel they need to deepen their skills. Creating a culture of learning always starts at the executive level, he says.  “Business leaders need to be vigilant about the areas where their tech teams are falling behind and set up systems and initiatives that will help enable direct managers to assess their team’s skills on a consistent basis,” Herbert says.   Related:2024 InformationWeek US IT Salary Report: Profits, Layoffs, and the Continued Rise of AI Anant Adya, executive vice president and head of Americas delivery at Infosys, says that businesses are moving away from hiring or training workers based on expertise in a single technology and towards cultivating talent proficiency across many disciplines.  “Building diverse talent pipelines and offering opportunities to build both hard technical skills and soft communication skills are effective strategies,” he says.  Adya adds there is great value in investing in “data readiness” and fostering a culture of responsible experimentation as part of upskilling.  Continued Demand for IT Pros   According to CompTIA’s State of the Tech Workforce 2024 report, tech occupation employment over the next decade is expected to grow at about twice the rate of overall employment across the economy.  Projected growth rates for several tech occupations are well above the national rate, most notably for data scientists and data analysts and cybersecurity analysts and engineers.   Tim Herbert, chief research officer at CompTIA, explains AI is “undoubtedly” the wildcard factor on the minds of many employers and workers.  Related:Forrester Speaker Sneak Peek: Analyst Jayesh Chaurasia to Talk AI Data Readiness “While some of the AI hype has moderated, there continues to be plenty of experimentation and anticipation for what comes next,” he says via email.   According to CompTIA analysis of Lightcast data, AI job postings account for 10-12% of all tech job postings in recent months.   “Every industry is hiring technology professionals,” he says. “There really aren’t high-tech or low-tech industries anymore”  He lists infrastructure, software, cybersecurity, and data as the four big buckets, with help desk and support in another category.  “Increasingly, the problems become less technology problems and more related to the industry — compliance and privacy, for example,” he says. “You have to know the drivers and priorities within the industry.”  He notes that there are also more and more jobs that require technology professionals to interact with other teams and to understand more about the business and the problems they are trying to solve.   Power of Programmatic Upskilling  The Pluralsight survey indicated upskilling employees is proving to be more cost-effective and timelier than hiring new talent.  While hiring can cost over $23,000 and take up to 10 weeks, upskilling costs around $5,000 per employee and can be implemented faster.  Related:The Impact of AI Skills on Hiring and Career Advancement Despite these advantages, time constraints remain a major barrier to successful upskilling programs, as reported by organizations over the past three years.  Pluralsight’s Herbert says it is crucial to make upskilling within the organization “programmatic,” which involves mapping your technologists’ skill-building journey to business needs.  “This is where developing a culture of learning comes in,” he says. “If upskilling is integrated as a core business competency, tech teams will have the nimbleness needed to switch focus from one skill area to the next as business needs ebb and flow.”  Steve Watt, CIO at Hyland, says that CIOs should also provide robust upskilling opportunities to show IT professionals they’re dedicated to their growth and career interests.  “The job market for IT professionals is being swayed by the demands of AI but security and cloud professionals have invaluable skills that are still very much in need,” he explains.  By offering opportunities for IT professionals to sharpen their core skills in their roles, companies are helping strengthen their own business while showing talent they’re committed to their long-term success and interests.  Adya says that training must balance skills required for basic infrastructure with those needed for swiftly emerging technologies.   “For cloud in particular, programs should be self-paced, in collaboration with academic institutions, specialized for local hiring, and grounded in digital reskilling,” he says.  The program should additionally incorporate hands-on experiences and input from cross-functional teams.  “Companies should additionally create incentives, necessary infrastructure and support to properly add employees to the process,” he says.   Top IT Talent Desire Flexibility   Watt says remote work flexibility continues to be a key differentiator as well.  “Because IT and security are ubiquitous across every industry and skills transfer almost regardless of vertical markets, these workers have a lot of options when picking a company or industry to work in,” he says.  Being inflexible — especially with IT and security staff when it comes to remote work — can significantly hinder the ability to attract and retain top talent.  “I recently spoke with another CIO who had commented that after a rollout of a mandatory three-day-in-office policy they lost 20% of their IT staff in about 4 months,” he says. “They rolled that policy back specifically for IT very quickly.”  source

“Digital Resilience: Merging IT Growth with Environmental Responsibility“ Building Resilient IT Infrastructures for Sustainable Digital Growth The white paper titled “Digital Resilience and IT Growth” by Chatsworth Products explores the critical aspects of building resilient IT infrastructures in the face of rapid digital transformation. It delves into strategies for enhancing data center reliability, scalability, and efficiency to support growing digital demands. The paper emphasizes the importance of integrating advanced technologies and best practices to mitigate risks, improve operational continuity, and ensure robust performance. By adopting these strategies, organizations can effectively manage IT growth, protect vital data, and maintain a competitive edge in an increasingly digital landscape. Download this whitepaper to learn more.  Offered Free by: Chatsworth Products, Inc. See All Resources from: Chatsworth Products, Inc. Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. Thank you This download should complete shortly. If the resource doesn’t automatically download, please, click here. source

Over the last 15 years, the tech professional community has identified a small number of core cybersecurity capabilities that offer a high payoff: preventing known cyberattacks while supporting compliance requirements. Are these 8 core capabilities in your cybersecurity toolkit? source

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