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The What & Why of Data Governance

erwin

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. The What: Data Governance Defined. Data governance has no standard definition.

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

This is where we dispel an old “big data” notion (heard a decade ago) that was expressed like this: “we need our data to run at the speed of business.” Instead, what we really need is for our business to run at the speed of data. Confluent – providing access and discovery across real-time event data and streaming data.

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Why The Public Sector Needs Data Governance

Alation

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

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The Rising Need for Data Governance in Healthcare

Alation

Leaders in healthcare seek to improve patient outcomes, meet changing business models (including value-based care ), and ensure compliance while creating better experiences. Data & analytics represents a major opportunity to tackle these challenges. In other words, they use data to heal more people and save more lives.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

“All they would have to do is just build their model and run with it,” he says. But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. For now, it operates under a centralized “hub and spokes” model.

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Breaking down data silos for digital success

CIO Business Intelligence

For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

For the downstream consumption by all departments across the organization, smava’s Data Platform team prepares curated data products following the extract, load, and transform (ELT) pattern. The Raw Vault describes objects loaded directly from the data sources and represents a copy of the landing stage in the data lake.