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Are enterprises ready to adopt AI at scale?

CIO Business Intelligence

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.

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Seniors and Juniors

O'Reilly on Data

Sorting is important because its easy to describe and has many different solutions, and each solution has different properties. The solutions represent different approaches to problem solving. Theyve solved a lot of problems and know what solutions are likely to workand know how to test different approaches.

Software 247
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What is data architecture? A framework to manage data

CIO Business Intelligence

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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AI agents: The next stage in the evolution of enterprise AI

CIO Business Intelligence

The first wave of generative artificial intelligence (GenAI) solutions has already achieved considerable success in companies, particularly in the area of coding assistants and in increasing the efficiency of existing SaaS products. A new architectural paradigm is therefore needed to create and maintain many agent-based applications.

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Partner Webinar: A Framework for Building Data Mesh Architecture

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.

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7 types of tech debt that could cripple your business

CIO Business Intelligence

Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture. Build up: Databases that have grown in size, complexity, and usage build up the need to rearchitect the model and architecture to support that growth over time.

Risk 140
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CIOs contend with gen AI growing pains

CIO Business Intelligence

It’s a position many CIOs find themselves in, as Guan noted that, according to an Accenture survey, fewer than 10% of enterprises have gen AI models in production. “What’s Next for GenAI in Business” panel at last week’s Big.AI@MIT I think driving down the data, we can come up with some kind of solution.”