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Accelerating AI at scale without sacrificing security

CIO Business Intelligence

As AI adoption accelerates, it demands increasingly vast amounts of data, leading to more users accessing, transferring, and managing it across diverse environments. Each interaction amplifies the potential for errors, breaches, or misuse, underscoring the critical need for a strong governance framework to mitigate these risks.

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Integrating Data Governance and Enterprise Architecture

erwin

Why should you integrate data governance (DG) and enterprise architecture (EA)? Data governance provides time-sensitive, current-state architecture information with a high level of quality. Data governance provides time-sensitive, current-state architecture information with a high level of quality.

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What Is Data Governance? (And Why Your Organization Needs It)

erwin

Organizations with a solid understanding of data governance (DG) are better equipped to keep pace with the speed of modern business. In this post, the erwin Experts address: What Is Data Governance? Why Is Data Governance Important? What Is Good Data Governance? What Is Data Governance?

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Automating Data Governance

erwin

Automating data governance is key to addressing the exponentially growing volume and variety of data. Data readiness is everything. The State of Data Automation. Data readiness depends on automation to create the data pipeline. We asked participants to “talk to us about data value chain bottlenecks.”

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7 Benefits of Metadata Management

erwin

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

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Metadata Management Best Practices: How to Plan Your Metadata Management Program

Octopai

Metadata has been defined as the who, what, where, when, why, and how of data. Without the context given by metadata, data is just a bunch of numbers and letters. But going on a rampage to define, categorize, and otherwise metadata-ize your data doesn’t necessarily give you the key to the value in your data.

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Monitoring Apache Iceberg metadata layer using AWS Lambda, AWS Glue, and AWS CloudWatch

AWS Big Data

It addresses many of the shortcomings of traditional data lakes by providing features such as ACID transactions, schema evolution, row-level updates and deletes, and time travel. In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient.

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