Remove Business Intelligence Remove Data Observability Remove Data Quality
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Alation 2022.2: Open Data Quality Initiative and Enhanced Data Governance

Alation

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

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Data integrity vs. data quality: Is there a difference?

IBM Journey to AI blog

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

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Data Quality Framework: What It Is, Components, and Implementation

DagsHub

As such, the quality of their data can make or break the success of the company. This article will guide you through the concept of a data quality framework, its essential components, and how to implement it effectively within your organization. What is a data quality framework?

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Visionary Data Quality Paves the Way to Data Integrity

Precisely

And the desire to leverage those technologies for analytics, machine learning, or business intelligence (BI) has grown exponentially as well. Now, almost any company can build a solid, cost-effective data analytics or BI practice grounded in these new cloud platforms. Cloud-native data execution is just the beginning.

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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

The ability to effectively deploy AI into production rests upon the strength of an organization’s data strategy because AI is only as strong as the data that underpins it. Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models.

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How the right data and AI foundation can empower a successful ESG strategy

IBM Journey to AI blog

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

Establishing a foundation of trust: Data quality and governance for enterprise AI As organizations increasingly rely on artificial intelligence (AI) to drive critical decision-making, the importance of data quality and governance cannot be overstated.

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