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What is data architecture? A framework to manage data

CIO

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.

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The key to operational AI: Modern data architecture

CIO

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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Reimagine application modernisation with the power of generative AI

CIO

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.

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Master Building Scalable Micro-Frontend Application Using React

DevOps.com

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.

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An Architect’s Guide for Selecting Scalable, Data-Layer Technologies

There’s no getting around it: selecting the right foundational data-layer components is crucial for long-term application success.

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Can serverless fix fintech’s scaling problem?

CIO

Add to this the escalating costs of maintaining legacy systems, which often act as bottlenecks for scalability. The latter option had emerged as a compelling solution, offering the promise of enhanced agility, reduced operational costs, and seamless scalability. Scalability. Architecture complexity. Legacy infrastructure.

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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. Solution overview The solution presented in this post uses batch inference in Amazon Bedrock to process many requests efficiently using the following solution architecture.

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Serverless and Containers: How to Choose the Right Application Strategy

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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Best Practices for Deploying & Scaling Embedded Analytics

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.