Training Artificial Intelligence Models with Redshift Data

Redshift

Amazon Redshift is a popular data warehousing solution that can handle data on an exabytes scale. It is useful for processing real-time analytics, combining multiple data sources, log analysis, or more. Redshift uses parallel-processing and compression to decrease command execution time. This allows Redshift to perform operations on billions of rows at once. This also makes Redshift useful for storing and analyzing large quantities of data from logs or live feeds through a source such as Amazon Kinesis Data Firehose.

Artificial Intelligence Models

Artificial intelligence (AI) models are computer programs that can perform tasks that would normally require human intelligence to complete. AI models are popular because they can automate tasks that would otherwise require human intervention, such as image recognition, natural language processing, and decision making. AI models can also help businesses make better decisions by providing insights into customer behavior and business operations.

With the growing popularity of both Redshift for storage and artificial intelligence models for AI deployments, it is unsurprising that many organizations are seeking to train artificial intelligence models using data in Redshift. Kaspian offers native connectors for this operation. Just register your Redshift datastore and link your model training job; Kaspian's autoscaling compute layer makes it easy to train and deploy artificial intelligence models using any data in your cloud with minimal setup or management.

Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.