Remove AWS Remove Data Observability Remove Data Quality
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How Anomalo solves unstructured data quality issues to deliver trusted assets for AI with AWS

Flipboard

As a result, the competitive edge is shifting toward data access and data quality. The challenge is how to use that data. Transforming unstructured files, maintaining compliance, and mitigating data quality issues all become critical hurdles when an organization moves from AI pilots to production deployments.

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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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Visionary Data Quality Paves the Way to Data Integrity

Precisely

First, private cloud infrastructure providers like Amazon (AWS), Microsoft (Azure), and Google (GCP) began by offering more cost-effective and elastic resources for fast access to infrastructure. Now, almost any company can build a solid, cost-effective data analytics or BI practice grounded in these new cloud platforms.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services. SageMaker Studio offers built-in algorithms, automated model tuning, and seamless integration with AWS services, making it a powerful platform for developing and deploying machine learning solutions at scale.

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Modern Data Architectures Provide a Foundation for Innovation

Precisely

At Precisely’s Trust ’23 conference, Chief Operating Officer Eric Yau hosted an expert panel discussion on modern data architectures. The group kicked off the session by exchanging ideas about what it means to have a modern data architecture. Data observability also helps users identify the root cause of problem in the data.

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Trustworthy AI, Powered by Trusted Data

Precisely

Watch the webinar AI You Can Trust Watch this webinar and see how we explore organizational challenges in maintaining data integrity for AI applications and real-world use cases showcasing the transformative impact of high-integrity data on AI success. Fuel your AI applications with trusted data to power reliable results.

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Data Integrity Trends for 2024

Precisely

They’re where the world’s transactional data originates – and because that essential data can’t remain siloed, organizations are undertaking modernization initiatives to provide access to mainframe data in the cloud. That approach assumes that good data quality will be self-sustaining.