Applications Architecture Scalability 
CIO
DECEMBER 20, 2024
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.
CIO
NOVEMBER 27, 2024
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.
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CIO
JANUARY 15, 2025
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.
CIO
JANUARY 30, 2025
From data masking technologies that ensure unparalleled privacy to cloud-native innovations driving scalability, these trends highlight how enterprises can balance innovation with accountability. These capabilities rely on distributed architectures designed to handle diverse data streams efficiently.
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There’s no getting around it: selecting the right foundational data-layer components is crucial for long-term application success.
DevOps.com
JANUARY 6, 2025
Micro-frontend is a new and effective approach to building data-dense or heavy applications as well as websites. Building micro-frontend applications enables monolithic applications to divide into smaller, independent units.
Dzone - DevOps
MARCH 28, 2025
The architecture downstream ensures scalability, cost efficiency, and real-time access to applications. This blog post discusses an end-to-end ML pipeline on AWS SageMaker that leverages serverless computing, event-trigger-based data processing, and external API integrations.
Speaker: Tolga Tarhan, Senior Vice President, GM AWS Services at Onica
Of course, the key as a senior leader is to understand what your organization needs, your application requirements, and to make choices that leverage the benefits of the right approach that fits the situation. How to make the right architectural choices given particular application patterns and risks.
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Embedding analytics in your application doesn’t have to be a one-step undertaking. In fact, rolling out features gradually is beneficial because it allows you to progressively improve your application. Application Design: Depending on your capabilities, you can choose either a VM or a container-based approach.
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