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Making your enterprise architecture framework work for you

CIO

More organizations than ever have adopted some sort of enterprise architecture framework, which provides important rules and structure that connect technology and the business. Choose the right framework There are plenty of differences among the dozens of EA frameworks available.

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Download our enterprise architecture (EA) tools buyer’s guide

CIO

In the beginning, no one needed enterprise architecture (EA) tools. The modern enterprise, however, is much different. The back of an envelope would do in the early years. It needs EA tools.

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Why CIOs must lead the charge on ESG – and why enterprise architecture is the key

CIO

In an era marked by heightened environmental, social and governance (ESG) scrutiny and rapid artificial intelligence (AI) adoption, the integration of actionable sustainable principles in enterprise architecture (EA) is indispensable.

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The key to operational AI: Modern data architecture

CIO

From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. Today, enterprises are leveraging various types of AI to achieve their goals. To succeed, Operational AI requires a modern data architecture.

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Top Considerations for Building an Open Cloud Data Lake

Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.

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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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Are enterprises ready to adopt AI at scale?

CIO

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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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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The Forrester Wave™: AI/ML Platforms: Vendor Strategy, Market Presence, and Capabilities Overview

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.

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Microservices: The Dark Side

Speaker: Prem Chandrasekaran

In his best-selling book Patterns of Enterprise Application Architecture, Martin Fowler famously coined the first law of distributed computing—"Don’t distribute your objects"—implying that working with this style of architecture can be challenging.