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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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Alation & Bigeye: A Potent Partnership for Data Quality

Alation

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it. Extract data quality information.

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Alation + Soda: Dynamic Data Quality with the Data Catalog

Alation

Alation and Soda are excited to announce a new partnership, which will bring powerful data-quality capabilities into the data catalog. Soda’s data observability platform empowers data teams to discover and collaboratively resolve data issues quickly. Do we have end-to-end data pipeline control?

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16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

We couldn’t be more excited to announce our first group of partners for ODSC East 2023’s AI Expo and Demo Hall. These organizations are shaping the future of the AI and data science industries with their innovative products and services. Check them out below.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

” – James Tu, Research Scientist at Waabi Play with this project live For more: Dive into documentation Get in touch if you’d like to go through a custom demo with your team Comet ML Comet ML is a cloud-based experiment tracking and optimization platform. Data monitoring tools help monitor the quality of the data.

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Exploring Innovations in Data Integrity

Precisely

When attempting to build a data strategy, the primary obstacle organizations face is a lack of resources. Teams are building complex, hybrid, multi-cloud environments, moving critical data workloads to the cloud, and addressing data quality challenges.

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Demystifying Data Mesh

Precisely

Quality and formatting may differ with more autonomous domain teams producing data assets, making interoperability difficult and data quality guarantees elusive. Data discoverability and reusability. Data products must be properly designed and organized to be reused across the organization.