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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. Ensure security and access controls.
To fully benefit from AI, organizations must take bold steps to accelerate the time to value for these applications. Just as DevOps has become an effective model for organizing application teams, a similar approach can be applied here through machine learning operations, or “MLOps,” which automates machine learning workflows and deployments.
In a global economy where innovators increasingly win big, too many enterprises are stymied by legacy application systems. Modernising with GenAI Modernising the application stack is therefore critical and, increasingly, businesses see GenAI as the key to success. The solutionGenAIis also the beneficiary.
After all, a low-risk annoyance in a key application can become a sizable boulder when the app requires modernization to support a digital transformation initiative. Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture.
Enterprise architecture (EA) has evolved beyond governance and documentation. A well-structured EA foundation provides the clarity, governance and visibility necessary to deliver sustainable long-term impact. Governance ensures that EA strategies arent just models on paper but actionable frameworks that drive results.
The evolution of cloud-first strategies, real-time integration and AI-driven automation has set a new benchmark for data systems and heightened concerns over data privacy, regulatory compliance and ethical AI governance demand advanced solutions that are both robust and adaptive.
With the rapid advancement and deployment of AI technologies comes a threat as inclusion has surpassed many organizations governance policies. Governance is also seen as a roadblock to the agility needed to quickly deploy into production. Leaving 55% saying that their organization had not yet implemented an AI governance framework.
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.
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 latest stage — the intelligent edge — is on the brink of rapid adoption.
Legacy platforms meaning IT applications and platforms that businesses implemented decades ago, and which still power production workloads are what you might call the third rail of IT estates. Compatibility issues : Migrating to a newer platform could break compatibility between legacy technologies and other applications or services.
It prevents vendor lock-in, gives a lever for strong negotiation, enables business flexibility in strategy execution owing to complicated architecture or regional limitations in terms of security and legal compliance if and when they rise and promotes portability from an applicationarchitecture perspective.
5 key findings: AI usage and threat trends The ThreatLabz research team analyzed activity from over 800 known AI/ML applications between February and December 2024. The surge was fueled by ChatGPT, Microsoft Copilot, Grammarly, and other generative AI tools, which accounted for the majority of AI-related traffic from known applications.
CIOs feeling the pressure will likely seek more pragmatic AI applications, platform simplifications, and risk management practices that have short-term benefits while becoming force multipliers to longer-term financial returns. Placing an AI bet on marketing is often a force multiplier as it can drive data governance and security investments.
Modern Application Development Services Defined Clients want more autonomy to better control their own innovation and development capabilities to build modern and up-to-date custom applications.
Yet most of the responsibility falls on customers to leverage those tools and practices effectively while addressing cost optimization practices through governance, leadership support, and policy implementation. Optimizing resources based on application needs is essential to avoid setting up oversized resources, he states.
So as a CIO, how should you reign in the chaos and implement a suitable level of governance and control? The challenge is reminiscent of the 1990s when CIOs reigned in application silos by moving to ERP systems, and in the 2010s when CIOs had to contain mobile devices through BYOD policies. Todays challenge is perhaps far greater.
Watsonx is Big Blues core enterprise-grade AI platform and developer studio that will let organizations implement monitoring and governance of Nvidia NIM microservices across any hosting environment, IBM stated. CAS will be embedded in the next update of IBM Fusion, which is planned for the second quarter of this year.
The fact is that within enterprises, existing architecture is overly complex, often including new digital systems interconnected with legacy systems. This hybrid architecture is a combination of best and bad practice. For most enterprises stuck in this hybrid state, the way forward is to be more discipline around architecture.
Enterprise architecture definition Enterprise architecture (EA) is the practice of analyzing, designing, planning, and implementing enterprise analysis to successfully execute on business strategies. Making it easier to evaluate existing architecture against long-term goals.
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).
Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. Data governance framework Data governance may best be thought of as a function that supports an organization’s overarching data management strategy.
All industries and modern applications are undergoing rapid transformation powered by advances in accelerated computing, deep learning, and artificial intelligence. That’s why we’re introducing a new disaggregated architecture that will enable our customers to continue pushing the boundaries of performance and scale.
Most companies have transitioned to become more software-centric, and with this transformation, application programming interfaces (APIs) have proliferated. If companies want to input, leverage, and embed these digital brains into their business, they’ll need an API to connect the LLM to various business applications,” he says.
In IDCs April 2024 CIO Poll Survey of 105 senior IT professionals and CIOs, developing better IT governance and enterprise architecture emerged as one of the top priorities for 2024, ranking fourth. Without well-functioning IT governance, how can you progress on competing priorities?
40% of highly regulated enterprises will combine data and AI governance. AI governance is already a complex issue due to rapid innovation and the absence of universal templates, standards, or certifications. Forrester believes these pressures will cause highly regulated enterprises to unify their data and AI governance frameworks.
The US government has already accused the governments of China, Russia, and Iran of attempting to weaponize AI for those purposes.” To address the misalignment of those business units, MMTech developed a core platform with built-in governance and robust security services on which to build and run applications quickly.
AI and machine learning are poised to drive innovation across multiple sectors, particularly government, healthcare, and finance. Governments will prioritize investments in technology to enhance public sector services, focusing on improving citizen engagement, e-governance, and digital education.
Its a step forward in terms of governance, trying to make sure AI is being used in a socially beneficial way. Agents will begin replacing services Software has evolved from big, monolithic systems running on mainframes, to desktop apps, to distributed, service-based architectures, web applications, and mobile apps.
CIOs must take an active role in educating their C-suite counterparts about the strategic applications of technologies like, for example, artificial intelligence, augmented reality, blockchain, and cloud computing. Now, he focuses on strategic business technology strategy through architectural excellence.
The Open Group Architecture Framework (TOGAF) is an enterprise architecture methodology that offers a high-level framework for enterprise software development. TOGAF helps organizations implement software technology in a structured and organized way, with a focus on governance and meeting business objectives. TOGAF definition.
We really liked [NetSuite’s] architecture and that it’s in the cloud, and it hit the vast majority of our business requirements,” Shannon notes. HGA is a longtime Microsoft shop so Stanton and Haunfelder performed the upgrade using Microsoft Fabric while also implementing a data governance structure.
GRC certifications validate the skills, knowledge, and abilities IT professionals have to manage governance, risk, and compliance (GRC) in the enterprise. Enter the need for competent governance, risk and compliance (GRC) professionals. What are GRC certifications? Why are GRC certifications important?
Theres no denying that AI will be a disruptive force, potentially inverting unit economics for the application layer and catalyzing a shift toward AI-powered services and embedded AI. This approach allows businesses to build custom applications by assembling pre-built, modular components.
Our digital transformation has coincided with the strengthening of the B2C online sales activity and, from an architectural point of view, with a strong migration to the cloud,” says Vibram global DTC director Alessandro Pacetti. For example, IT builds an application that allows you to sell a company service or product.
With this in mind, we embarked on a digital transformation that enables us to better meet customer needs now and in the future by adopting a lightweight, microservices architecture. We found that being architecturally led elevates the customer and their needs so we can design the right solution for the right problem.
Replace on-prem VMs with public cloud infrastructure Theres an argument to be made for a strategy that reduces reliance on virtualized on-prem servers altogether by migrating applications to the public cloud. Those resources are probably better spent re-architecting applications to remove the need for virtual machines (VMs).
The imperative for APMR According to IDC’s Future Enterprise Resiliency and Spending Survey, Wave 1 (January 2024), 23% of organizations are shifting budgets toward GenAI projects, potentially overlooking the crucial role of application portfolio modernization and rationalization (APMR). Set relevant key performance indicators (KPIs).
Despite the fact that we seem to be years away from having practical working quantum computers, or even a common set of standards for how to build these things, investors, governments, and large corporations are taking quantum computing seriously. Error correction will definitely accelerate the adoption of quantum-based solutions in the bank.
For organizations with stringent security and compliance requirements, private cloud offers a dedicated environment that provides greater control over data and applications. Thats primarily due to the benefits of FinOps in designing governance, cost optimization strategies and cloud usage policies that organizations understand.
As someone deeply involved in shaping data strategy, governance and analytics for organizations, Im constantly working on everything from defining data vision to building high-performing data teams. These potential applications are truly transformative. Its about investing in skilled analysts and robust data governance.
The US government has already accused the governments of China, Russia, and Iran of attempting to weaponize AI for those purposes.” To address the misalignment of those business units, MMTech developed a core platform with built-in governance and robust security services on which to build and run applications quickly.
The government and Congress are taking notice of unfair consumer experiences, and it is crucial for businesses to address their technical debt and minimize the risk of negative press, government fines, and damaged reputations. Customers may describe applications as clunky, buggy, and outdated. What is technical debt?
As a networking and security strategy, zero trust stands in stark contrast to traditional, network-centric, perimeter-based architectures built with firewalls and VPNs, which involve excessive permissions and increase cyber risk. The main point is this: you cannot do zero trust with firewall- and VPN-centric architectures.
Agentic AI systems require more sophisticated monitoring, security, and governance mechanisms due to their autonomous nature and complex decision-making processes. Building trust through human-in-the-loop validation and clear governance structures is essential to establishing strict protocols that guide safer agent-driven decisions.
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