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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. Optimize data flows for agility.
Agentic AI is the next leap forward beyond traditional AI to systems that are capable of handling complex, multi-step activities utilizing components called agents. He believes these agentic systems will make that possible, and he thinks 2025 will be the year that agentic systems finally hit the mainstream. They have no goal.
Enterprise architecture (EA) has evolved beyond governance and documentation. A centralized EA repository enables enterprise-wide visibility into systems, dependencies, and risks. At this stage, EA plays a key role in digital transformation initiatives, enabling business agility, cost optimization and faster time-to-market.
S/4HANA is SAPs latest iteration of its flagship enterprise resource planning (ERP) system. As a result, they called their solution a real-time system, which is what the R in the product name SAP R/1 stood for. The name S/4HANA isnt the only thing that reflects the close integration of the new ERP system with the database.
Particularly well-suited for microservice-oriented architectures and agile workflows, containers help organizations improve developer efficiency, feature velocity, and optimization of resources. Key metrics to monitor when leveraging two container orchestration systems. Containers power many of the applications we use every day.
While the impacts of legacy systems can be quantified, technical debt is also often embedded in subtler ways across the IT ecosystem, making it hard to account for the full list of issues and risks. Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture.
Jenga builder: Enterprise architects piece together both reusable and replaceable components and solutions enabling responsive (adaptable, resilient) architectures that accelerate time-to-market without disrupting other components or the architecture overall (e.g. compromising quality, structure, integrity, goals).
This maximizes the value of their core systems and drives meaningful business outcomes,” the survey stated. According to the IBV researchers, 74% of respondents said that they are integrating AI into mainframe operations to enhance system management and maintenance.
Speed and agility bring in the top transformation prize. But Ari Lightman, professor at Carnegie Mellons Heinz College of Information Systems and Public Policy, says its time to retire that term and the mindset it engenders and instead recognize that the goal is straightforward transformation.
CIOs often have a love-hate relationship with enterprise architecture. In the State of Enterprise Architecture 2023 , only 26% of respondents fully agreed that their enterprise architecture practice delivered strategic benefits, including improved agility, innovation opportunities, improved customer experiences, and faster time to market.
At a time when technology innovation cycles are getting shorter, we will struggle to keep pace if we have to navigate around legacy systems that act as barriers to speed and agility. Over time the speed and agility barriers associated with the ERP spread to other systems as they, in turn, formed an expanding wave of technical debt.
Decisions made in isolation lead to inefficiencies, slower responses to market changes, and a lack of agility that stifles innovation. Architects help organizations remain agile, innovative, and aligned by bridging gaps between strategy and technology. The future of leadership is agile, adaptable and architecturally driven.
Technology leaders in the financial services sector constantly struggle with the daily challenges of balancing cost, performance, and security the constant demand for high availability means that even a minor system outage could lead to significant financial and reputational losses. Architecture complexity. Legacy infrastructure.
Similarly, Voice AI in call centers, integrated with back-office systems, improves customer support through real-time solutions. These metrics might include operational cost savings, improved system reliability, or enhanced scalability.
In todays digital-first economy, enterprise architecture must also evolve from a control function to an enablement platform. This transformation requires a fundamental shift in how we approach technology delivery moving from project-based thinking to product-oriented architecture. The stakes have never been higher.
Smaller models, on the other hand, are more tailored, allowing businesses to create AI systems that are precise, efficient, robust, and built around their unique needs, he adds. Reasoning also helps us use AI as more of a decision support system, he adds. Now, it will evolve again, says Malhotra. Agents are the next phase, he says.
Here, agility is essential, and smart IT leaders are doubling down on efforts to streamline IT, whether that involves reprioritizing projects and realigning the IT portfolio, rationalizing applications and pursuing cloud-native approaches, increasing automation through DevOps or AIOps adoption, or overhauling the structure of IT operations.
In a global economy where innovators increasingly win big, too many enterprises are stymied by legacy application systems. Maintaining, updating, and patching old systems is a complex challenge that increases the risk of operational downtime and security lapse.
Enterprise architecture definition Enterprise architecture (EA) is the practice of analyzing, designing, planning, and implementing enterprise analysis to successfully execute on business strategies. Another main priority with EA is agility and ensuring that your EA strategy has a strong focus on agility and agile adoption.
Technology investments, such as in generative AI, are a priority in addressing the need to meet rising expectations while also driving operational agility and resilience. He advises beginning the new year by revisiting the organizations entire architecture and standards. Are they still fit for purpose?
Rather than discuss “legacy systems,” talk about “revenue bottlenecks,” and replace “technical debt” with “innovation capacity.” For example: Direct costs (principal): “We’re spending 30% more on maintaining outdated systems than our competitors.” So this is the conversation starter that will get the boardroom’s attention.
What companies need to do in order to cope with future challenges is adapt quickly: slim down and become more agile, be more innovative, become more cost-effective, yet be secure in IT terms. Generally speaking, a healthy application and data architecture is at the heart of successful modernisation.
Data is the foundation of innovation, agility and competitive advantage in todays digital economy. Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks. We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems.
Merchants had to navigate complex toll systems imposed by regional rulers, much as cloud providers impose egress fees that make it costly to move data between platforms. However, as companies expand their operations and adopt multi-cloud architectures, they are faced with an invisible but powerful challenge: Data gravity.
Pre-COVID, agility became an aspiration and rallying cry for organizations seeking to embrace emerging technologies and pursue technology-enabled innovation, often to stave off digital disruption in their industries. This goes beyond implementing agile methodology. Balance control with agility. Think a step ahead.
As enterprises scale their digital transformation journeys, they face the dual challenge of managing vast, complex datasets while maintaining agility and security. With the rise in hybrid and multi-cloud environments, businesses will increasingly need to secure sensitive data across diverse systems.
Here, agility is essential, and smart IT leaders are doubling down on efforts to streamline IT, whether that involves reprioritizing projects and realigning the IT portfolio, rationalizing applications and pursuing cloud-native approaches, increasing automation through DevOps or AIOps adoption, or overhauling the structure of IT operations.
More organizations than ever have adopted some sort of enterprise architecture framework, which provides important rules and structure that connect technology and the business. The results of this company’s enterprise architecture journey are detailed in IDC PeerScape: Practices for Enterprise Architecture Frameworks (September 2024).
The data is spread out across your different storage systems, and you don’t know what is where. This means that the infrastructure needs to provide seamless data mobility and management across these systems. How NetApp supports AI workloads today Today, NetApp is a recognized leader in AI infrastructure.
Legacy systems and technical debt Barrier: Legacy systems, often deeply embedded in an organization’s operations, pose a significant challenge to IT modernization. These outdated systems are not only costly to maintain but also hinder the integration of new technologies, agility, and business value delivery.
How these sweeping transformations affect the digital organization stem from major changes to the system landscape in all areas of operation. Altehed also says that Volvo’s systems span five decades, starting with mainframe environments from the 1970s and into modern technologies and tools recently launched.
Nimesh Mehta likens decommissioning legacy systems to going on an archeological dig: There are systems that still have a lot of value; its just a matter of unearthing them, taking out what isnt needed, and building new processes on top.
Pursue cryptographic agility Once companies have figured out which assets and communications they need to protect first, how do they actually go about switching to quantum-safe cryptography? Instead, Horvath and other experts recommend that enterprises pursue quantum agility. It seems easy to do but its actually catastrophic.
However, a significant challenge persists: harmonizing data systems to fully harness the power of AI. According to a recent Salesforce study, 62% of large enterprises are not well-positioned to achieve this harmony, with 80% grappling with data silos and 72% facing the complexities of overly interdependent systems.
The Open Group Architecture Framework (TOGAF) is an enterprise architecture methodology that offers a high-level framework for enterprise software development. TOGAF 10 brings a stronger focus to organizations using the agile methodology, making it easier to apply the framework to an organization’s specific needs.
Since these technology solutions can’t scale without a modular, well-architected foundation of platform services, she’s set her sights on moving from a set of customized and packaged software to a more modern architecture. We need our architecture to help deliver on that intent.” My team is very proactive and customer-focused.
As your business grows, your unique needs may diverge from what your vendor’s monolithic platform can offer, resulting in a system that does many things but excels at none. In the realm of systems, this translates to leveraging architectural patterns that prioritize modularity, scalability, and adaptability.
In todays fast-paced digital landscape, the cloud has emerged as a cornerstone of modern business infrastructure, offering unparalleled scalability, agility, and cost-efficiency. Technology modernization strategy : Evaluate the overall IT landscape through the lens of enterprise architecture and assess IT applications through a 7R framework.
Without the right cloud architecture, enterprises can be crushed under a mass of operational disruption that impedes their digital transformation. What’s getting in the way of transformation journeys for enterprises? Imagine not only being able to preserve existing systems but using them to lever digital transformation.
Scaled Agile Framework (SAFe) certifications are becoming valuable in larger organizations looking for efficient project delivery, reduced time-to-market, and ways to provide better stakeholder value. Scaled Agile: Scaled Agile is a key provider of agile training, courses, and certification, including SAFe.
What companies need to do in order to cope with future challenges is adapt quickly: slim down and become more agile, be more innovative, become more cost-effective, yet be secure in IT terms. Generally speaking, a healthy application and data architecture is at the heart of successful modernisation.
Artificial intelligence for IT operations (AIOps) solutions help manage the complexity of IT systems and drive outcomes like increasing system reliability and resilience, improving service uptime, and proactively detecting and/or preventing issues from happening in the first place.
Agile content management systems (CMSes) build on the momentum of nearly 30 years of delivering modern, digital, internet-powered experiences. With a nod to both developers and practitioners, agile CMS seeks to enable collaborative, iterative approaches to content and experiences that satisfy both sides of the house.
The first is to foster a culture of agility, collaboration, and AI-driven innovation, driven in part by our new Office of AI. And third, systems consolidation and modernization focuses on building a cloud-based, scalable infrastructure for integration speed, security, flexibility, and growth. Its a three-pronged effort.
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