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Why Cloud Data Governance is Critical: 9 Key Principles

Alation

Therefore, the question is not if a business should implement cloud data management and governance, but which framework is best for them. Whether you’re using a platform like AWS, Google Cloud, or Microsoft Azure, data governance is just as essential as it is for on-premises data.

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Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

Flipboard

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. For Azure AD, you must also specify a unique identifier for the scope.

AWS 123
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What Are The Best Third-Party Data Ingestion Tools For Snowflake?

phData

Fivetran works with all three Snowflake cloud providers. If using a network policy with Snowflake, be sure to add Fivetran’s IP address list , which will ensure Azure Data Factory (ADF) Azure Data Factory is a fully managed, serverless data integration service built by Microsoft.

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Three essential steps to protecting your data across the hybrid cloud

IBM Journey to AI blog

Enforce security policies in near real-time that protect data across the enterprise—for all data access, change control and user activities. Guardium supports deployment on several cloud platforms, including Amazon AWS, Google, IBM Cloud, Microsoft Azure and Oracle OCI.

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Using Matillion Data Productivity Cloud to call APIs

phData

Matillion is also built for scalability and future data demands, with support for cloud data platforms such as Snowflake Data Cloud , Databricks, Amazon Redshift, Microsoft Azure Synapse, and Google BigQuery, making it future-ready, everyone-ready, and AI-ready. Each API has its own set of requirements.

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Present and future of data cubes: an European EO perspective

Mlearning.ai

EO data is not yet a commodity and neither is environmental information, which has led to a fragmented data space defined by a seemingly endless production of new tools and services that can’t interoperate and aren’t accessible by people outside of the deep tech community ( read more ). Yet nobody feels locked-in by technology.

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What Can AI Teach Us About Data Centers? Part 1: Overview and Technical Considerations

ODSC - Open Data Science

Co-location data centers: These are data centers that are owned and operated by third-party providers and are used to house the IT equipment of multiple organizations. Edge data centers: These are data centers that are located closer to the edge of the network, where data is generated and consumed, rather than in central locations.