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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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TransUnion transforms its business model with IT

CIO Business Intelligence

That data is in the process of being unified on a multilayered platform that offers a variety of data services, including data ingestion, data management, data governance, and data security. We’re modernizing existing products to get to this entire data analytics value chain.”

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The Enduring Significance of Data Modeling in the Modern Data-Driven Enterprise

erwin

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

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Why Spreadsheets Are Your Secret Weapon for Efficient Data Governance

Alation

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. A “Value at Risk” (VaR) model operated on a series of spreadsheets, which were built manually, via copy and paste.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. The offensive side?

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Ingestion tools are connected to various data sources. Then they collect data through a push mechanism, a replication engine, a webhook, an API call, or other methods. A batch-processing model will collect data at set intervals, while a stream-processing model will ingest data almost instantaneously as it is created.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

A data hub is a center of data exchange that constitutes a hub of data repositories and is supported by data engineering, data governance, security, and monitoring services. A data hub contains data at multiple levels of granularity and is often not integrated.