The Power of In-Database Blending: Faster Data Blending with Amazon Redshift

[MaimoonaB]

Faster Data Blending with Alteryx & Amazon RedshiftIt’s an exciting time for data analytics due to access to varied data sources, more up-to-date data sources, and more specific data that analysts and consumers of the data can leverage to learn even more about their business. However with this boon of data, comes a new challenge in blending high volumes of data, and/or multiple sources of high volume data and getting to a clean, trimmed data set for analytics. Then time spent waiting for high volumes of data can be a big roadblock and analysts have to weigh the cost benefit of using all of the data or getting analytic insight in the time the organization needs.

In-database processing is a way to tackle this problem, and we are excited to now include in-database blending for Amazon Redshift in Alteryx Analytics 10.0. By pushing the processing steps from Alteryx into Amazon Redshift, we leverage the processing power of the database itself, eliminating the need to stream data out of the warehouse for processing. For analytics involving very large datasets, this can mean a significant performance improvement – data analysts can spend less time waiting and more time analyzing data!

Download our whitepaper to learn more about Alteryx in-database processing for Amazon Redshift and read about two common scenarios that benefit most from in-database processing.