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Cloud Data Warehouse Migration 101: Expert Tips

Alation

As enterprises migrate to the cloud, two key questions emerge: What’s driving this change? And what must organizations overcome to succeed at cloud data warehousing ? What Are the Biggest Drivers of Cloud Data Warehousing? Yet the cloud, according to Sacolick, doesn’t come cheap. “A

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How to Architect Data Quality on Snowflake

Dataversity

With the accelerating adoption of Snowflake as the cloud data warehouse of choice, the need for autonomously validating data has become critical. While existing Data Quality solutions provide the ability to validate Snowflake data, these solutions rely on a rule-based approach that is […].

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What Is Data Quality and Why Is It Important?

Alation

What is Data Quality? Data quality is defined as: the degree to which data meets a company’s expectations of accuracy, validity, completeness, and consistency. By tracking data quality , a business can pinpoint potential issues harming quality, and ensure that shared data is fit to be used for a given purpose.

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Good AI in 2021 Starts with Great Data Quality

Dataversity

The post Good AI in 2021 Starts with Great Data Quality appeared first on DATAVERSITY. Achieving good AI is a whole other story. AI initiatives can take a lot of time and effort to get up and running, often exceeding initial budget and […].

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Data Fabric: Convergent Solutions to Avoid Complex Tools Patchwork

Dataversity

According to Gartner, data fabric is an architecture and set of data services that provides consistent functionality across a variety of environments, from on-premises to the cloud. Data fabric simplifies and integrates on-premises and cloud Data Management by accelerating digital transformation.

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Trends in Data Governance and Security: What to Prepare for in 2024

Dataversity

Organizations learned a valuable lesson in 2023: It isn’t sufficient to rely on securing data once it has landed in a cloud data warehouse or analytical store. As a result, data owners are highly motivated to explore technologies in 2024 that can protect data from the moment it begins its journey in the source systems.

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5 Common Data Governance Challenges (and How to Overcome Them)

Dataversity

It’s common for enterprises to run into challenges such as lack of data visibility, problems with data security, and low Data Quality. But despite the dangers of poor data ethics and management, many enterprises are failing to take the steps they need to ensure quality Data Governance.