Remove Data Governance Remove Metadata Remove Telecommunication
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Accelerate Your Machine Learning Workflows in Snowflake with Snowpark ML 

Snowflake

Snowpark ML Operations: Model management The path to production from model development starts with model management, which is the ability to track versioned model artifacts and metadata in a scalable, governed manner. The Snowpark Model Registry API provides simple catalog and retrieval operations on models.

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Expert Insights for Your 2025 Data, Analytics, and AI Initiatives

Precisely

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. Focus on metadata management.

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How to Choose a Futureproof Data Integration Solution

Precisely

The same is true of systems that monitor trading exchanges, ATM transactions, telecommunications network outages, suspicious network traffic, and more. Real-time visibility of data is a competitive advantage. A notable capability that achieves this is the data catalog. That’s where real-time integration makes a difference.

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Expert Insights for Your 2025 Data, Analytics, and AI Initiatives

Precisely

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. Focus on metadata management.

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From Data Quality to Data Integrity: The Path to Trusted Data

Precisely

In the context of improving their organizations’ data integrity , respondents cite data quality and data integration as priorities for 2023 and as challenges to data integrity. Let’s explore more of the report’s findings around data integrity maturity, challenges, and priorities.

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How to Choose a Futureproof Data Integration Solution

Precisely

The same is true of systems that monitor trading exchanges, ATM transactions, telecommunications network outages, suspicious network traffic, and more. Real-time visibility of data is a competitive advantage. A notable capability that achieves this is the data catalog. That’s where real-time integration makes a difference.

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What is Data Enrichment? Best Practices and Use Cases

Precisely

When we think about the big picture of data integrity – that’s data with maximum accuracy, consistency, and context – it becomes abundantly clear why data enrichment is one of its six key pillars (along with data integration, data observability, data quality, data governance, and location intelligence).