Tag: ML
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Considerations To Load Data Into VantageCloud Lake
Teradata VantageCloud Lake architecture uses two file systems: Block File System (BFS) and Object File System (OFS). While OFS is cost-effective, BFS enables faster operations and features not available in OFS, such as temporal tables and row-level security. Additionally, the Lake instances are in the UTC zone, which conditions how to load data. This post…
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VantageCloud Lake Architecture
VantageCloud Lake is Teradata’s cloud-native data and analytics platform. This post explains Lake’s architecture, including OFS and BFS storage, and its main capabilities.
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From Zero to Hero in Cross-Site Restores in Teradata
The Cross-Site Restores feature in VantageCloud Enterprise allows you to quickly create a Disaster Recovery site for your Production database.
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Teradata’s Cloud-Native Database
Teradata has just launched a Cloud-native database, VantageCloud Lake. In this post, I discuss its high-level architecture.
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Takeaways from a Microsoft engineer about ML on Azure
Takeaways on how to run ML projects on Azure from a Microsoft engineer – author of the Azure Data Scientist Associate Certification Guide.
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Andreas Botsikas – Microsoft engineer, author of the Azure Data Scientist Guide
“ML models are in fashion, such as customer churn predictions. However, it’s not easy to define what a churned customer is unless you have a multi subscription system like Netflix, where you can quickly identify the customers who stopped paying. E.g., what does churn mean for a supermarket?”