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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.

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Is your EA just IT? Unlocking the value of enterprise architecture

CIO Business Intelligence

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?

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Agentic AI design: An architectural case study

CIO Business Intelligence

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.

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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. These areas are considerable issues, but what about data, security, culture, and addressing areas where past shortcuts are fast becoming todays liabilities?

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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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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO Business Intelligence

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.

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IBM: 78% of mainframe shops are piloting, operating AI apps

Network World

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

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The Next-Generation Cloud Data Lake: An Open, No-Copy Data Architecture

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.