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.
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.
Adopting Operational AI Organizations looking to adopt Operational AI must consider three core implementation pillars: people, process, and technology. Technology: The workloads a system supports when training models differ from those in the implementation phase. To succeed, Operational AI requires a modern data architecture.
From obscurity to ubiquity, the rise of large language models (LLMs) is a testament to rapid technological advancement. The analyst firm Forrester named AI agents as one of its top 10 emerging technologies this year and that it will deliver benefits in the next two to five years. Why has agentic AI become the latest rage?
There was a time when technology managers needed to actively monitor these kinds of granular metrics, but today, these alerts just create distracting noise. The premise of SLIs/SLOs is that all teams—product, architecture, development, and platform— need to look at services from the customer’s perspective.
The second-order impacts of this spending are being strategized, architected, and designed in real time, and were seeing the early signs of emerging technologies like agentic AI being used to reinvent core capabilities in businesses especially now, in light of new tariffs.
During my career I have developed a few mottos. The topics of technical debt recognition and technology modernization have become more important as the pace of technology change – first driven by social, mobile, analytics, and cloud (SMAC) and now driven by artificial intelligence (AI) – increases. Which are obsolete?
In a world where business, strategy and technology must be tightly interconnected, the enterprise architect must take on multiple personas to address a wide range of concerns. These include everything from technical design to ecosystem management and navigating emerging technology trends like AI.
For transformation to take hold, IT Leaders must focus on developing their emotional and adaptability quotient skills. However, in todays era of rapid technological advancement and societal shifts, especially over the past five years, relying solely on traditional approaches is no longer enough to stay competitive.
That’s why we developed this white paper to give you insights into four key open-source technologies – Apache Cassandra®, Apache Kafka®, Apache Spark™, and OpenSearch® – and how to leverage them for lasting success.
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.
The survey found that people are surprisingly knowledgeable and excited about AI and business leaders should understand and not underestimate consumers when developing and deploying AI-enabled solutions. In the UAE, 91% of consumers know GenAI and 34% use these technologies. Positioning the country at the forefront of AI development.
Caldas joined me for a recent episode of the Tech Whisperers podcast , where she opened up her leadership playbook and discussed what it takes to be a truly innovative, tech-forward company, one that leverages technology to gain first-mover advantage. Monica Caldas: I always think of technology as having a defensive and an offensive side.
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.
Particularly well-suited for microservice-oriented architectures and agile workflows, containers help organizations improve developer efficiency, feature velocity, and optimization of resources.
It seems like only yesterday when software developers were on top of the world, and anyone with basic coding experience could get multiple job offers. This yesterday, however, was five to six years ago, and developers are no longer the kings and queens of the IT employment hill. An example of the new reality comes from Salesforce.
Generative AI has seen faster and more widespread adoption than any other technology today, with many companies already seeing ROI and scaling up use cases into wide adoption. Vendors are adding gen AI across the board to enterprise software products, and AI developers havent been idle this year either.
AIMMO announced today it has raised $12 million in a Series A round to advance its data labeling technology and spur global expansions. AIMMO declined to comment on its valuation. The startup said its tools help improve the inefficiency of the data annotation process so that customers focus only on their AI modeling.
Cloud architects are responsible for managing the cloud computing architecture in an organization, especially as cloud technologies grow increasingly complex. Its an advanced job title, with cloud architects typically reporting to the IT director, CIO, CTO, or other technology executives. What does a cloud architect do?
As enterprises evolve their AI from pilot programs to an integral part of their tech strategy, the scope of AI expands from core data science teams to business, software development, enterprise architecture, and IT ops teams. The Forrester Wave™ evaluates Leaders, Strong Performers, Contenders, and Challengers.
This is where Delta Lakehouse architecture truly shines. Approach Sid Dixit Implementing lakehouse architecture is a three-phase journey, with each stage demanding dedicated focus and independent treatment. Step 2: Transformation (using ELT and Medallion Architecture ) Bronze layer: Keep it raw.
Agent Development Kit (ADK) The Agent Development Kit (ADK) is a game-changer for easily building sophisticated multi-agent applications. It is an open-source framework designed to streamline the development of multi-agent systems while offering precise control over agent behavior and orchestration.
Unfortunately, despite hard-earned lessons around what works and what doesn’t, pressure-tested reference architectures for gen AI — what IT executives want most — remain few and far between, she said. Second, Guan said, CIOs must take a “platforms-based approach” to AI development and deployment.
The shifting leadership landscape In a fast-paced, tech-driven world, business strategy and technology are more intertwined than ever. They are instrumental in navigating the complex intersection of technology and business, driving innovation, and accelerating decision-making in ways traditional leadership roles have struggled to do.
Noting that companies pursued bold experiments in 2024 driven by generative AI and other emerging technologies, the research and advisory firm predicts a pivot to realizing value. Forrester said most technology executives expect their IT budgets to increase in 2025. Others won’t — and will come up against the limits of quick fixes.”
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. The speed of the cyber technology revolution is very fast and attackers are always changing behaviors.
In response, traders formed alliances, hired guards and even developed new paths to bypass high-risk areas just as modern enterprises must invest in cybersecurity strategies, encryption and redundancy to protect their valuable data from breaches and cyberattacks. Security was another constant challenge.
As a consequence, these businesses experience increased operational costs and find it difficult to scale or integrate modern technologies. 1] Retaining outdated technology may seem like a cautious approach but there are mounting inherent dangers. The foundation of the solution is also important.
In the 1970s, five formerIBMemployees developed programs that enabled payroll and accounting on mainframe computers. In 2008, SAP developed the SAP HANA architecture in collaboration with the Hasso Plattner Institute and Stanford University with the goal of analyzing large amounts of data in real-time.
Generally speaking, a healthy application and data architecture is at the heart of successful modernisation. The thing that makes modernising applications so difficult is the complexity of the heterogeneous systems that companies have developed over the years. Take IBM Watson Code Assistant for Z, for example.
4, NIST released the draft Guidance for Implementing Zero Trust Architecture for public comment. Tenable has been proud to work alongside the NIST National Cybersecurity Center of Excellence (NCCoE) to launch the Zero Trust Architecture Demonstration Project.
Technology has shifted from a back-office function to a core enabler of business growth, innovation, and competitive advantage. Senior business leaders and CIOs must navigate a complex web of competing priorities, such as managing stakeholder expectations, accelerating technological innovation, and maintaining operational efficiency.
Key considerations for cloud strategy and modernization The what: The executive leadership team of business and IT together need to evaluate business needs and their current business challenges, global footprint and current technology landscape and define the companys Northstar, (aka, the what, the vision).
The implications for cloud adoption are profound, as businesses increasingly rely on these technologies to drive digital transformation, optimize operations and gain competitive advantages. The result was a compromised availability architecture. This siloed approach leads to suboptimal decision-making and fractured strategies.
They are using the considerable power of this fast-evolving technology to tackle the common challenges of cloud modernization, particularly in projects that involve the migration and modernization of legacy applications a key enabler of digital and business transformation.
The Middle East is rapidly evolving into a global hub for technological innovation, with 2025 set to be a pivotal year in the regions digital landscape. Looking ahead to 2025, Lalchandani identifies several technological trends that will define the Middle Easts digital landscape.
This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. Similarly, there is a case for Snowflake, Cloudera or other platforms, depending on the companys overarching technology strategy.
1 Meanwhile Tom Mainelli, group vice president for device and consumer research at IDC, says: “The NPU-equipped AI PCs shipping today are the beginning of a technology ramp that could lead to big changes in the way we interact with our PCs.”
Organizations look at digital transformation as an opportunity to radically improve operations and increase the value of a product or service to the customer by embedding technology into the decision-making fabric and building automation into its functions.
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 core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both. That’s why we’re introducing a new disaggregated architecture that will enable our customers to continue pushing the boundaries of performance and scale. Imagine that you’re a data engineer.
This can lead to feelings of being overwhelmed, especially when confronted with complex project architectures. This can lead to feelings of being overwhelmed, especially when confronted with complex project architectures. Does the term Architecture Decision Records (ADRs) sound familiar?
Migration to the cloud, data valorization, and development of e-commerce are areas where rubber sole manufacturer Vibram has transformed its business as it opens up to new markets. We’re in publishing, but it’s the accompanying services that differentiate us on the market; the technology component is what gives value to our business.”
Since 2022, the tech industry has experienced massive layoffs, as large tech companies have reduced their workforce numbers in response to rising interest rates and emerging generative AI technology.
We organize all of the trending information in your field so you don't have to. Join 49,000+ 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