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Broadcoms decisions to replace perpetual VMware software licenses with subscriptions and to eliminate point products in favor of an expensive bundle of private cloud tools are driving longtime VMware customers to look for an exit strategy. Its enterprise-grade. Lets talk about platform strategy. Its scalable.
AI and, most recently, generative AI (genAI) have uncovered the true power of automating tasks that previously were tedious to complete or difficult to improve the efficiency of the work within a singular domain of the business. But much more importantly, genAI has also started to drive new levels of business value as it cuts […]
Todays enterprisearchitecture (EA) practices are critical to enable a firms customer-obsessed digital transformations. As more traditional EA practices become commoditized, EnterpriseArchitecture Management Suite (EAMS) vendors that show strong use cases to support real transformations will emerge as market leaders.
Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Ensure security and access controls.
As enterprises evolve their AI from pilot programs to an integral part of their tech strategy, the scope of AI expands from core data science teams to business, software development, enterprisearchitecture, and IT ops teams.
Enterprisearchitecture (EA) has evolved beyond governance and documentation. A centralized EA repository enables enterprise-wide visibility into systems, dependencies, and risks. Governance ensures that EA strategies arent just models on paper but actionable frameworks that drive results. With the right tools.
From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. Today, enterprises are leveraging various types of AI to achieve their goals. To succeed, Operational AI requires a modern data architecture.
In our fast-changing digital world, it’s essential to sync IT strategies with business objectives for lasting success. Effective IT strategy requires not just technical expertise but a focus on adaptability and customer-centricity, enabling organizations to stay ahead in a fast-changing marketplace.
What does excellence in enterprisearchitecture look like? Learn more about the enterprisearchitecturestrategy that won Contact Energy, a New Zealand electricity generator and retailer, this year’s EA Award for the APAC region.
In his best-selling book Patterns of Enterprise Application Architecture, Martin Fowler famously coined the first law of distributed computing—"Don’t distribute your objects"—implying that working with this style of architecture can be challenging. How these strategies can be applied in different size engineering organizations.
With the AI revolution underway which has kicked the wave of digital transformation into high gear it is imperative for enterprises to have their cloud infrastructure built on firm foundations that can enable them to scale AI/ML solutions effectively and efficiently.
Questionable outcomes and a lack of confidence in generative AIs promised benefits are proving to be key barriers to enterprise adoption of the technology. Sastry Durvasula, chief operating, information, and digital officer at TIAA, firmly believes consumption-based pricing is the best model for business organizations AI strategies.
AI is reinvigorating the mainframe and causing enterprises to rethink their plans for mainframe modernization. Hybrid by design The mainframe’s ability to be integrated with and modernized by cloud computing architectures is an integral part of its future role.
As IT professionals and business decision-makers, weve routinely used the term digital transformation for well over a decade now to describe a portfolio of enterprise initiatives that somehow magically enable strategic business capabilities. Ultimately, the intent, however, is generally at odds with measurably useful outcomes.
For starters, generative AI capabilities will improve how enterprise IT teams deploy and manage their SD-WAN architecture. SD-WAN which stands for software-defined wide area network has been around for a decade, pitched to enterprises as a way to cut costs and improve WAN flexibility.
The shifting leadership landscape In a fast-paced, tech-driven world, business strategy and technology are more intertwined than ever. One that integrates business strategy with deep technical knowledge. Architects help organizations remain agile, innovative, and aligned by bridging gaps between strategy and technology.
Zero Trust architecture was created to solve the limitations of legacy security architectures. It’s the opposite of a firewall and VPN architecture, where once on the corporate network everyone and everything is trusted. In today’s digital age, cybersecurity is no longer an option but a necessity.
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Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprisearchitecture. Build up: Databases that have grown in size, complexity, and usage build up the need to rearchitect the model and architecture to support that growth over time.
A recent survey of cybersecurity professionals indicates that 81% of organizations are turning to zero trust as the foundation of their cybersecurity strategies. In fact, the traditional VPN-based architecture emerged as a major point of risk in 2024, with many VPN vulnerabilities being exploited repeatedly.
LeanIX, a privately held enterprisearchitecture (EA) management solution, is set to be acquired by SAP, as announced on September 7, 2023 (click here). SAP has made this strategic acquisition to offer SAP clients access to a complete suite of tools essential for continuous business transformation.
Currently we are seeing this phenomenon with the new chief AI officer role being established in some enterprises. There has also been the establishment of the chief transformation officer , as some enterprises have chosen to give the keys to making change happen to another C-suite executive.
In a move closely watched by enterprise technology leaders, Alphabet CEO Sundar Pichai has reaffirmed Googles commitment to spending $75 billion this year on AI infrastructure and data centers weeks after Microsoft reportedly abandoned many of its data center projects. For enterprises, this changes the calculus.
The most focused and aggressive of the large CSPs Nvidias architecture is highly sought after, but expensive and difficult to come by. It has been the most focused and aggressive of the large CSPs in chasing the enterprise AI market with its own silicon. For Amazon, thats the Trainium, the Graviton processor, and the Inferentia chip.
Network-as-a-service startup Nile has added an AI-based tool aimed at helping enterprise customers provision and operatethe vendors Campus Network-as-a-Service deployments. The app verifies each devices status and ensures the necessary software versions are running before provisioning and activation.
Zero-trust security is essential to enterprises that are converging operational technology (OT) with IT infrastructure. New research from Enterprise Management Associates (EMA) identified how this convergence influences zero-trust strategy and implementation. Companies often need new security solutions to protect OT.
CEO Jensen Huang announced two new generations of GPU architecture stretching into 2028. Nvidia is evolving from being just the parts provider to a full stack offering, says Anshel Sag, principal analyst with Moor Insights and Strategy. Previously hes only given one year of advanced generational preview.
Bank, and finalists Rockwell Automation and Takeda Pharmaceuticals have used outcome-driven enterprisearchitecture for business success. Learn how our winner, U.S.
The Chinese government is supporting and subsidizing local manufacturers to produce ARM-based chips, explained Lidice Fernandez, group VP for IDCs worldwide enterprise infrastructure trackers. Will it lead to shortages?
More organizations than ever have adopted some sort of enterprisearchitecture framework, which provides important rules and structure that connect technology and the business. Choose the right framework There are plenty of differences among the dozens of EA frameworks available.
Poor resource management and optimization Excessive enterprise cloud costs are typically the result of inefficient resource management and a lack of optimization. Many enterprises also overestimate the resources required, leading to larger, more expensive instances being provisioned than necessary, causing overprovisioning.
SONiC remains a cornerstone of Aviz’s strategy Shukla highlighted the growing demand for SONiC, particularly in data centers and GPU fabrics, driven by the need for new infrastructure to support the increasing use of GPUs and inferencing networks. The new funding follows a $10 million round announced in December 2023.
The built-in elasticity in serverless computing architecture makes it particularly appealing for unpredictable workloads and amplifies developers productivity by letting developers focus on writing code and optimizing application design industry benchmarks , providing additional justification for this hypothesis. Architecture complexity.
VMware by Broadcom has unveiled a new networking architecture that it says will improve the performance and security of distributed artificial intelligence (AI) — using AI and machine learning (ML) to do so. The company said it has identified a need for more intelligent edge networking and computing. That’s where VeloRAIN will come in.
AI, once viewed as a novel innovation, is now mainstream, impacting just about facet of the enterprise. To keep ahead of the curve, CIOs should continuously evaluate their business and technology strategies, adjusting them as necessary to address rapidly evolving technology, business, and economic practices.
We may look back at 2024 as the year when LLMs became mainstream, every enterprise SaaS added copilot or virtual assistant capabilities, and many organizations got their first taste of agentic AI. AI at Wharton reports enterprises increased their gen AI investments in 2024 by 2.3
Data centers this year will face several challenges as the demand for artificial intelligence introduces an evolution in AI hardware, on-premises and cloud-based strategies for training and inference, and innovations in power distributionsall while opposition to new data center developments continues to grow.
The deal, which sees Oracle and Carlyle selling their stakes in Ampere, strengthens SoftBanks position in the growing market for AI-optimized processors as major cloud providers increasingly look beyond traditional x86 architecture.
An effective roadmap involves not only evaluating current system architecture, skills availability and cost of ownership, but also considering future business needs. When your existing enterprise system is stable, robust and tailored to your needs, replacing it with new technology can introduce unnecessary risk.
I aim to outline pragmatic strategies to elevate data quality into an enterprise-wide capability. Key recommendations include investing in AI-powered cleansing tools and adopting federated governance models that empower domains while ensuring enterprise alignment. Inconsistent business definitions are equally problematic.
[i] CIOs face mounting pressure to optimize their data strategy, manage vendors effectively, and accelerate digital transformation. We share three common mistakes that hinder data strategies and how they can be fixed. Companies collect on average 100+ data points per consumer, with at least 22% becoming obsolete each year. [ii]
Our research shows 52% of organizations are increasing AI investments through 2025 even though, along with enterprise applications, AI is the primary contributor to tech debt. If they’re going to benefit from AI strategies, companies must address this foundation before they can effectively scale their gen AI initiatives.
Jayesh Chaurasia, analyst, and Sudha Maheshwari, VP and research director, wrote in a blog post that businesses were drawn to AI implementations via the allure of quick wins and immediate ROI, but that led many to overlook the need for a comprehensive, long-term business strategy and effective data management practices.
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