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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). Ensure security and access controls. AI and machine learning models. Application programming interfaces.

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

CIO

All industries and modern applications are undergoing rapid transformation powered by advances in accelerated computing, deep learning, and artificial intelligence. This means that the infrastructure needs to provide seamless data mobility and management across these systems.

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Relativity reaps the rewards of automated access management

CIO

This award-winning access management project uses automation to streamline access requests and curb security risks. Access management is crucial in the legal world because cases depend on financial records, medical records, emails, and other personal information.

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Navigating the complexities of security and compliance on the mainframe

CIO

As organizations look to modernize IT systems, including the mainframe, there’s a critical need to do so without sacrificing security or falling out of compliance. With the stakes so high, IT leaders need to ensure their modernization strategies are inclusive of mainframe security. PCI DSS v4.0).

Security 391
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Security team management: Top 4 findings from discussions with CISOs

CIO

Most large businesses have a security team. But what, exactly, does that security team look like? And is it optimized in each of these respects to maximize the organization’s security posture? We learned, for example, that very few organizations have just a single security team. How is it structured?

Security 459
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Leveraging AMPs for machine learning

CIO

As a result, many companies are now more exposed to security vulnerabilities, legal risks, and potential downstream costs. Explainability is also still a serious issue in AI, and companies are overwhelmed by the volume and variety of data they must manage.

Learning 221
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Are enterprises ready to adopt AI at scale?

CIO

This requires greater flexibility in systems to better manage data storage and ensure quality is maintained as data is fed into new AI models. As data is moved between environments, fed into ML models, or leveraged in advanced analytics, considerations around things like security and compliance are top of mind for many.

Banking 524