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
Dataarchitecture definition Dataarchitecture 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 dataarchitecture is the purview of data architects.
Enterprise architecture (EA) has evolved beyond governance and documentation. Establish clear roles and responsibilities for an integrated team of business, application, data and technology architects. Ensure architecture insights drive business strategy. Accelerate transformation by enabling rapid decision-making. The result?
A company that adopts agentic AI will gain competitive advantages in innovation, efficiency and responsiveness and may become more agile in operations. In our real-world case study, we needed a system that would create test data. This data would be utilized for different types of application testing.
Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture. These areas are considerable issues, but what about data, security, culture, and addressing areas where past shortcuts are fast becoming todays liabilities?
Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri
Data teams in large enterprise organizations are facing greater demand for data to satisfy a wide range of analytic use cases. Yet they are continually challenged with providing access to all of their data across business units, regions, and cloud environments.
The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data. The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows.
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. Most enterprises have built tech estates on hybrid cloud architecture, the researchers stated. “In
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.
For instance, an e-commerce platform leveraging artificial intelligence and data analytics to tailor customer recommendations enhances user experience and revenue generation. Adopting agile methodologies for flexibility and adaptation The Greek philosopher Heraclitus famously stated, “Change is the only constant.”
In an effort to be data-driven, many organizations are looking to democratize data. However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs.
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
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.
With growing concerns over advanced threats, VPN security issues, network complexity, and adversarial AI, enterprises are showing increased interest in a zero trust approach to security and moving away from firewall-and-VPN based architecture. Only 15% do not have a plan to embrace zero trust this year.
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] The foundation of the solution is also important.
The latter option had emerged as a compelling solution, offering the promise of enhanced agility, reduced operational costs, and seamless scalability. Financial services unique challenges However, it is important to understand that serverless architecture is not a silver bullet. Architecture complexity. Legacy infrastructure.
What role is data playing in RGAs profitability and growth? Data is a primary asset to RGAs growth, and our ability to leverage it is critical to increase the speed and precision of our core business processes, such as underwriting and actuarial. Our data capability finds global commonality across all our regional solutions.
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 the Forrester/InfoWorld Enterprise Architecture Awards competition, we look for the most dramatic stories of EA’s strategic leadership and concrete business impact.
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.
Two things play an essential role in a firm’s ability to adapt successfully: its data and its applications. 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.
To keep up, IT must be able to rapidly design and deliver application architectures that not only meet the business needs of the company but also meet data recovery and compliance mandates. Moving applications between data center, edge, and cloud environments is no simple task.
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.
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. The IT operating model is driven by the degree of data integration and process standardization across business units, Thorogood observes.
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).
Theyre using approved tools and exploring others too, increasing the risk of leaking data. This change affects the entire IT architectural stack and impacts everything youre currently doing from business transformation to digital transformation and more. The data is clear. the same time, people are experimenting.
Embrace headless architecture for agile corporate training. Future-proof your learning strategy with flexibility and data-driven insights. The post How to Future-proof Training with Headless Architecture appeared first on Spiceworks.
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.
For all its advances, enterprise architecture remains a new world filled with tasks and responsibilities no one has completely figured out. Storing too much (or too little) data Software developers are pack rats. To make matters worse, finding the right bits gets harder as the data lakes get filled to the brim.
The patchwork nature of traditional data management solutions makes testing response and recovery plans cumbersome and complex. To address these challenges, organizations need to implement a unified data security and management system that delivers consistent backup and recovery performance.
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.
Rather than divide IT, digital, and data into different functional leadership roles, Gilbane’s executive management decided, for the first time, to put all of these transformational teams under one leader. “My There’s also investment in robotics to automate data feeds into virtual models and business processes.
Although organizations have embraced microservices-based applications, IT leaders continue to grapple with the need to unify and gain efficiencies in their infrastructure and operations across both traditional and modern application architectures. VMware Cloud Foundation (VCF) is one such solution. Much of what VCF offers is well established.
In CIOs 2024 Security Priorities study, 40% of tech leaders said one of their key priorities is strengthening the protection of confidential data. But with big data comes big responsibility, and in a digital-centric world, data is coveted by many players. Ravinder Arora elucidates the process to render data legible.
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. Contact us today to learn more.
Aerospike, provider of next-generation, real-time NoSQL data solutions, has released the Aerospike Kubernetes Operator and advancements in Aerospike Cloud Managed Service to help enterprises unlock cloud productivity and agility with scale-out cloud data. To […].
That worked when everything lived in the corporate data center. Paying a premium to backhaul traffic to a central data center made sense when that was where all applications lived. By eliminating VPNs and simplifying architecture, the Cafe-like Branch model addresses the connectivity needs of today while securing the future.
Data sovereignty has emerged as a critical concern for businesses and governments, particularly in Europe and Asia. With increasing data privacy and security regulations, geopolitical factors, and customer demands for transparency, customers are seeking to maintain control over their data and ensure compliance with national or regional laws.
Previously, we didn’t have access to all the data about our customers because we didn’t have the direct customer contact,” says Altehed. Now that systems are being replaced, it’s also about creating a new architecture without those types of connections. We were going to leave our data centers, and we did,” he says. “In
Two things play an essential role in a firms ability to adapt successfully: its data and its applications. 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.
Hes seeing the need for professionals who can not only navigate the technology itself, but also manage increasing complexities around its surrounding architectures, data sets, infrastructure, applications, and overall security. There are data scientists, but theyre expensive, he says.
He says, My role evolved beyond IT when leadership recognized that platform scalability, AI-driven matchmaking, personalized recommendations, and data-driven insights were crucial for business success. CIOs own the gold mine of data Leverage analytics to turn your insights into financial intelligence, thus making tech a profit enabler.
One of the newer technologies gaining ground in data centers today is the Data Processing Unit (DPU). As VMware has observed , “In simple terms, a DPU is a programable device with hardware acceleration as well as having an ARM CPU complex capable of processing data.
Composable architecture offers a middle ground between rigid, one-size-fits-all SaaS platforms and fully custom-built solutions. This can not only reduce costs but also simplify your IT landscape and improve data integration. Stay agile : The SaaS landscape is evolving rapidly.
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? This isn’t a matter of demonstrating greater organizational resilience or patience.
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