Data Science Blog

MAY 20, 2024

It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL. Support for Various Data Warehouses and Databases : AnalyticsCreator supports MS SQL Server 2012-2022, Azure SQL Database, Azure Synapse Analytics dedicated, and more. This allows for rapid prototyping of various models.

Data Pipeline 262

Data Pipeline Data Warehouse Azure Data Lakes 262

Smart Data Collective

OCTOBER 17, 2022

zettabytes in 2012. Older ETL technology, which might be code-heavy and slow down your process even more, isn’t helpful. This is an increase from 64.2 zettabytes of data in 2020, a tenfold increase from 6.5 Can’t get to the data.

Big Data 119

Big Data Big Data Data Engineering Data Engineer 119

AWS Machine Learning Blog

MAY 5, 2023

The following figure shows an example diagram that illustrates an orchestrated extract, transform, and load (ETL) architecture solution. For example, searching for the terms “How to orchestrate ETL pipeline” returns results of architecture diagrams built with AWS Glue and AWS Step Functions. join(", "), }; }).catch((error)

AWS 104

AWS ETL ML ML 104

AWS Machine Learning Blog

APRIL 16, 2024

You can use these connections for both source and target data, and even reuse the same connection across multiple crawlers or extract, transform, and load (ETL) jobs. or later image versions. These connections are used by AWS Glue crawlers, jobs, and development endpoints to access various types of data stores.

SQL 119

SQL AWS Database Data Scientist 119

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. Users can write data to managed RMS tables using Iceberg APIs, Amazon Redshift, or Zero-ETL ingestion from supported data sources.

SQL 76

SQL Data Analyst Data Warehouse AWS 76