ODSC - Open Data Science

JULY 11, 2023

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.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

Snorkel AI

OCTOBER 9, 2024

Enterprise IT admins can configure access to features and data at an instance, workspace, or role level by leveraging a ccess control rules. Snorkel automatically provisions those users with locked-down feature & data access to a set of permissioned workspaces.

Azure 52

Azure AWS Data Lakes Clustering 52

phData

DECEMBER 4, 2023

Thirty seconds is a good default for human users; if you find that queries are regularly queueing, consider making your warehouse a multi-cluster that scales on-demand. Cluster Count If your warehouse has to serve many concurrent requests, you may need to increase the cluster count to meet demand. authorization server.

Clustering 98

Clustering Database SQL Data Pipeline 98

phData

SEPTEMBER 20, 2023

A data mesh is a conceptual architectural approach for managing data in large organizations. Traditional data management approaches often involve centralizing data in a data warehouse or data lake, leading to challenges like data silos, data ownership issues, and data access and processing bottlenecks.

Data Silos 52

Data Silos Database Data Quality Data Engineering 52

The MLOps Blog

JUNE 27, 2023

Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks. It provides tools and components to facilitate end-to-end ML workflows, including data preprocessing, training, serving, and monitoring.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

O'Reilly Media

OCTOBER 19, 2021

ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses. Prior to the cloud, setting up and operating a cluster that can handle workloads like this would have been a major technical challenge.

ML 141

ML ML Data Scientist AWS 141

Alation

JULY 18, 2022

And the highlight, for us data intelligence folks, was the Databricks’ announcement that Unity Catalog , its unified governance solution for all data assets on its Lakehouse platform, will soon be available on AWS and Azure in the upcoming weeks. A simple model to control access to data via a UI or SQL. and much more!

AI 52

AI AI Data Lakes Azure 52

AWS Machine Learning Blog

SEPTEMBER 12, 2024

Organizations that want to build their own models or want granular control are choosing Amazon Web Services (AWS) because we are helping customers use the cloud more efficiently and leverage more powerful, price-performant AWS capabilities such as petabyte-scale networking capability, hyperscale clustering, and the right tools to help you build.

AI 85

AI AI AWS Clustering 85

The MLOps Blog

MARCH 21, 2023

Orchestrators are concerned with lower-level abstractions like machines, instances, clusters, service-level grouping, replication, and so on. Along with the schedulers, they are integral to managing the regular workflows your data scientists run and how the tasks in those workflows communicate with the ML platform.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69