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. Optimize data flows for agility.
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.
As enterprises scale their digital transformation journeys, they face the dual challenge of managing vast, complex datasets while maintaining agility and security. These capabilities rely on distributed architectures designed to handle diverse data streams efficiently.
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. But in reality, the proof is just the opposite.
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.
Speed and agility bring in the top transformation prize. Go all-in with agile Another way to ensure IT can quickly deliver transformative results is to go all-in with modern approaches, starting with a full embrace of agile development. The 2024 State of Agile report from Digital.ai
I believe that the fundamental design principles behind these systems, being siloed, batch-focused, schema-rigid and often proprietary, are inherently misaligned with the demands of our modern, agile, data-centric and AI-enabled insurance industry. This is where Delta Lakehouse architecture truly shines. Ensure reliability.
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.
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.
Adopting agile methodologies for flexibility and adaptation The Greek philosopher Heraclitus famously stated, “Change is the only constant.” In today’s business environment, agile methodologies have become indispensable for maintaining alignment between IT and business strategies.
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).
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.
Data is the foundation of innovation, agility and competitive advantage in todays digital economy. Key recommendations include investing in AI-powered cleansing tools and adopting federated governance models that empower domains while ensuring enterprise alignment. When financial data is inconsistent, reporting becomes unreliable.
In the Forrester/InfoWorld Enterprise Architecture Awards competition, we look for the most dramatic stories of EA’s strategic leadership and concrete business impact.
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.
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.
In the digital world, data integrity faces similar threats, from unauthorized access to manipulation and corruption, requiring strict governance and validation mechanisms to ensure reliability and trust. The adoption of cloud-native architectures further mitigates the impact of data gravity.
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.
According to research from NTT DATA , 90% of organisations acknowledge that outdated infrastructure severely curtails their capacity to integrate cutting-edge technologies, including GenAI, negatively impacts their business agility, and limits their ability to innovate. [1]
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).
Social, Agile, and Transformation. I cover topics for Technologists from CIOs to Developers - agile development, agile portfolio management, leadership, business intelligence, big data, startups, social networking, SaaS, content management, media, enterprise 2.0 Five Key Agile Practices to Support Architects.
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.
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?
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.
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.
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.
With digital operating models altering business processes and the IT landscape, enterprise architecture (EA) — a rigid stalwart of IT — has shown signs of evolving as well. The transition from monolith to microservices needs a high level of good governance.” CIO, Enterprise Architecture, IT Leadership says LeanXI’s Christ.
The evolution of agile development The agile manifesto was released in 2001 and, since then, the development philosophy has steadily gained over the previous waterfall style of software development. Its a step forward in terms of governance, trying to make sure AI is being used in a socially beneficial way.
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.
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.
When evaluating options, prioritize platforms that facilitate data democratization through low-code or no-code architectures. Effective data governance and quality controls are crucial for ensuring data ownership, reliability, and compliance across the organization.
Now that systems are being replaced, it’s also about creating a new architecture without those types of connections. Paring down agile Another change the digital organization has gone through recently is to start backing away from a pure agile approach. But it’s extremely difficult to suddenly launch a successfully IT system.
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.,
Thats primarily due to the benefits of FinOps in designing governance, cost optimization strategies and cloud usage policies that organizations understand. Automation and governance. Implementing governance policies ensures compliance with organizational standards and prevents cost overruns. CCOE vs. CBO: Why not both?
Leadership and governance Leadership is crucial in ensuring that AI initiatives align with business goals. Governance starts with data and is then integrated into AI. As AI becomes more embedded in data processes, governance in AI encompasses data integrity and quality. Thats just the nature of this beast.
From manufacturing to healthcare and finance to defense, AI enhances efficiency, decision-making and operational agility, providing organizations a competitive edge in an increasingly data-driven world. Senior executives are challenged with securing AI, aligning initiatives with governance frameworks and fortifying business resilience.
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?
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.
One of the federal government’s key procurement arms, the General Services Administration (GSA), has released a survey to the tech community in the form of a request for information asking a few simple questions regarding the experience of their vendor base. Agile Software Development. By Bob Gourley.
CIOs should prioritize data architecture, AI governance, and improving customer experiences, while maintaining rigorous evaluation of risks and compliance to maximize the benefits of genAI. CIOs must move beyond mere productivity and embrace genAI opportunities in digital transformation.
These outdated systems are not only costly to maintain but also hinder the integration of new technologies, agility, and business value delivery. It adopted a microservices architecture to decouple legacy components, allowing for incremental updates without disrupting the entire system.
The broad adoption of cloud apps, platforms, and infrastructure has led to a complete re-thinking of access, governance, and security. The modern approach to identity governance. Okta’s cloud-first approach to identity governance.
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