Smart Data Collective

OCTOBER 17, 2022

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

Big Data 119

Big Data Big Data Data Engineering Data Engineer 119

phData

NOVEMBER 9, 2023

Snowflake’s Data Cloud has emerged as a leader in cloud data warehousing. As a fundamental piece of the modern data stack , Snowflake is helping thousands of businesses store, transform, and derive insights from their data easier, faster, and more efficiently than ever before.

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98

AWS Machine Learning Blog

FEBRUARY 23, 2023

For more information about distributed training with SageMaker, refer to the AWS re:Invent 2020 video Fast training and near-linear scaling with DataParallel in Amazon SageMaker and The science behind Amazon SageMaker’s distributed-training engines.

AWS 116

AWS ML ML Machine Learning 116

Alation

DECEMBER 23, 2021

The elf teams used data engineering to improve gift matching and deployed big data to scale the naughty and nice list long ago , before either approach was even considered within our warmer climes. Get the latest data cataloging news and trends in your inbox. And this is just the beginning. Subscribe to Alation's Blog.

Data Governance 59

Data Governance Data Pipeline Tableau Big Data 59

phData

MAY 25, 2023

Snowflake is a cloud computing–based data cloud company that provides data warehousing services that are far more scalable and flexible than traditional data warehousing products. Gateways are being used as another layer of security between Snowflake or cloud data source and Power BI users.

Power BI 84

Power BI Analytics Analytics Azure 84

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. And so that’s where we got started as a cloud data warehouse.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. And so that’s where we got started as a cloud data warehouse.

SQL 52

SQL ML ML Python 52