This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
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.
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.
To succeed, Operational AI requires a modern data architecture. These advanced architectures offer the flexibility and visibility needed to simplify data access across the organization, break down silos, and make data more understandable and actionable.
Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture. What CIOs can do: Avoid and reduce data debt by incorporating data governance and analytics responsibilities in agile data teams , implementing data observability , and developing data quality metrics.
To address this, a next-gen cloud data lake architecture has emerged that brings together the best attributes of the data warehouse and the data lake. This new open data architecture is built to maximize data access with minimal data movement and no data copies.
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.
To overcome those challenges and successfully scale AI enterprise-wide, organizations must create a modern data architecture leveraging a mix of technologies, capabilities, and approaches including data lakehouses, data fabric, and data mesh. Another challenge here stems from the existing architecture within these organizations.
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.
Skills in architecture are also in high demand, as power-hungry AI systems require rethinking of data center design. Additionally, the industry is looking for workers with knowledge of cloud architecture and engineering, data analytics, management, and governance skills.
In this paper, we explore the top considerations for building a cloud data lake including architectural principles, when to use cloud data lake engines and how to empower non-technical users. The primary architectural principles of a true cloud data lake, including a loosely coupled architecture and open file formats and table structures.
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?
Yet, as transformative as GenAI can be, unlocking its full potential requires more than enthusiasm—it demands a strong foundation in data management, infrastructure flexibility, and governance. Trusted, Governed Data The output of any GenAI tool is entirely reliant on the data it’s given.
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).
In a way, the battle between sustainability objectives and AI and development objectives inside government and across society hasnt really begun, Lawrence explained on a recent webinar sharing the research firms predictions. Data centers are going to face intense scrutiny as they consume more energy and more water.
Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri
In this webinar, learn how Enel Group worked with Agile Lab to implement Dremio as a data mesh solution for providing broad access to a unified view of their data, and how they use that architecture to enable a multitude of use cases. Leveraging Dremio for data governance and multi-cloud with Arrow Flight.
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.
So as a CIO, how should you reign in the chaos and implement a suitable level of governance and control? This change affects the entire IT architectural stack and impacts everything youre currently doing from business transformation to digital transformation and more. Todays challenge is perhaps far greater.
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.
The World Economic Forum shares some risks with AI agents , including improving transparency, establishing ethical guidelines, prioritizing data governance, improving security, and increasing education. Placing an AI bet on marketing is often a force multiplier as it can drive data governance and security investments.
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?
Its not unusual [for organizations] to take six months to get to a yes, or worse yet, get to a no, he says, because their governance processes arent guardrails but rather governing by committee. Using AI is a faster way to do things, from writing code to having gen AI test and deploy, he says.
Intelligent data services With the rise of AI, there is an increasing need for robust security and governance to protect sensitive data and to comply with regulatory requirements, especially in the face of threats like ransomware. Planned innovations: Disaggregated storage architecture.
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. Essentially, cloud cost management is a shared responsibility between the enterprise and vendor, Kulkarni says.
The future of leadership is architecturally driven As the demands of technology continue to reshape the business landscape, organizations must rethink their approach to leadership. The future of leadership is agile, adaptable and architecturally driven.
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?
As such, he views API governance as the lever by which this value is assessed and refined. Good governance is the telemetry on that investment, from which operational and tactical plans can be adjusted and focused to achieve strategic objectives,” he says. Ajay Sabhlok, CIO and CDO at zero trust data security company Rubrik, Inc.,
Governance: Maps data flows, dependencies, and transformations across different systems. Greater integration and scalability: This modular architecture distributes tasks across multiple agents working in parallel, so Code Harbor can perform more work in less time.
This move underscores the country’s commitment to embedding AI at the highest levels of government, ensuring that AI policies and initiatives receive focused attention and resources. AI is at the core of this vision, driving smart governance, efficient resource management, and enhanced quality of life for residents and visitors alike.
As organizations work to establish AI governance frameworks, many are taking a cautious approach, restricting access to certain AI applications as they refine policies around data protection. Enterprises blocked a large proportion of AI transactions: 59.9% Zscaler Figure 2: Industries driving the largest proportions of AI transactions 5.
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.
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.
AI and Machine Learning will drive innovation across the government, healthcare, and banking/financial services sectors, strongly focusing on generative AI and ethical regulation. Governments will prioritize tech-driven public sector investments, enhancing citizen services and digital education.
For example, a business that depends on the SAP platform could move older, on-prem SAP applications to modern HANA-based Cloud ERP and migrate other integrated applications to SAP RISE (a platform that provides access to most core AI-enabled SAP solutions via a fully managed cloud hosting architecture).
We didn’t have a centralized place to do it and really didn’t do a great job governing our data. The lack of a corporate governance model meant that even if they could combine data, the reliability of it was questionable. “We We focused a lot on keeping our data secure. We didn’t spend as much time making our data easy to use.”
Your cloud governance must match this new reality. For this reason, along with new and developing industry regulations, growing sovereignty requirements, and a plethora of breaches/vulnerabilities, companies are revisiting or standing up governance programs that have not existed in […]
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. Its about investing in skilled analysts and robust data governance. Its about making sustainability a core priority.
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.
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.
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.
For example, the open-source AI model from Chinese company DeepSeek seems to have shown that an LLM can produce very high-quality results at a very low cost with some clever architectural changes to how the models work. These improvements are likely to be quickly replicated by other AI companies. Networking will be heavily impacted by AI.
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.
Governance and risk management in technology initiatives While agile methodologies promote flexibility, governance and risk management are critical for ensuring that technology initiatives remain aligned with business priorities. Now, he focuses on strategic business technology strategy through architectural excellence.
According to Forrester , for example, the approach accelerates and simplifies onboarding for new learners and developers, powers more effective digital governance, and improves the user experience. [3] The business benefits of GenAI-driven modernisation The benefits of powering application modernisation with GenAI are clear.
Understanding this complexity, the FinOps Foundation is developing best practices and frameworks to integrate SaaS into the FinOps architecture. Following the audit, it is crucial to create and implement governance guidelines for the organisation’s use, management, and acquisition of SaaS.
We organize all of the trending information in your field so you don't have to. Join 83,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content