Analytics Vidhya

JANUARY 15, 2021

ArticleVideos I will admit, AWS Data Wrangler has become my go-to package for developing extract, transform, and load (ETL) data pipelines and other day-to-day. The post Using AWS Data Wrangler with AWS Glue Job 2.0 appeared first on Analytics Vidhya.

AWS 264

AWS ETL Data Pipeline Analytics 264

Smart Data Collective

OCTOBER 17, 2022

Data pipelines automatically fetch information from various disparate sources for further consolidation and transformation into high-performing data storage. There are a number of challenges in data storage , which data pipelines can help address. Choosing the right data pipeline solution.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Data Lakes 145

Data Science Blog

FEBRUARY 4, 2023

If the data sources are additionally expanded to include the machines of production and logistics, much more in-depth analyses for error detection and prevention as well as for optimizing the factory in its dynamic environment become possible.

Cloud Data 147

Cloud Data Data Science Business Intelligence Business Intelligence 147

phData

FEBRUARY 7, 2024

Snowpark Use Cases Data Science Streamlining data preparation and pre-processing: Snowpark’s Python, Java, and Scala libraries allow data scientists to use familiar tools for wrangling and cleaning data directly within Snowflake, eliminating the need for separate ETL pipelines and reducing context switching.

Python 52

Python ML ML SQL 52