AWS Unveils New Features for Smarter Data-Crunching

A trio of new Amazon Web Services (AWS) enhancements announced at re:Invent this week promises to make it easier for customers to process, organize and make sense of their data assets across the AWS cloud.

The features, all in preview, are associated with the AWS Glue, Amazon QuickSight and Amazon Redshift products. Collectively, they're designed to "meaningfully change the speed and ease of use with which customers can get value from their data at any scale," according to Rahul Pathak, AWS vice president of Analytics, in an announcement Tuesday.

The first, AWS Glue Elastic Views (preview sign-up here), is an upcoming feature of the existing AWS Glue product, a serverless extract, transform and load (ETL) solution. Organizations use AWS Glue to prepare their data for machine learning and analytics tasks.

AWS Glue Elastic Views lets users generate materialized views of data from multiple data stores, including those outside their data lakes. It copies and combines data from a customer's selected data sources and replicates it in a target database. As changes are made to the original data sources, AWS Glue Elastic Views automatically updates the materialized view that's inside the target database.

Additionally, according to AWS, "[i]f there is a change to the data model in one of the source databases, Elastic Views proactively alerts the developers, so they can update their materialized view to adapt to the change."

Also in preview is Amazon QuickSight Q (sign-up here), a search bar-type feature in the Amazon QuickSight business intelligence service. Using machine learning, Amazon QuickSight Q lets users query the data within their chosen data store using just natural language. It removes the need for organizations to create pre-defined data models; Amazon QuickSight Q "automatically understands the meaning of and relationships between business data," according to AWS.

Amazon QuickSight Q comes pre-trained on language and data from several industries, including human resources, retail, pharmaceuticals and sales/marketing. Query results are returned in seconds, but in those cases where Amazon QuickSight Q can't immediately retrieve an answer, it will present the user with a list of suggested queries that it does understand.

Last, there's AQUA for Amazon Redshift (preview sign-up here, with general availability expected in January). AQUA is short for Advanced Query Accelerator. As its name suggests, AQUA for Amazon Redshift works with the Amazon Redshift cloud data warehouse to significantly improve query performance -- by as much as tenfold, according to AWS.

AWS describes AQUA for Amazon Redshift as a "distributed and hardware-accelerated cache." It reduces the time that data spends shuttling between where it's stored and where it's processed; instead, AWS says, AQUA for Amazon Redshift "brings compute to the storage layer."

"The AQUA cache scales out and processes data in parallel across many nodes," AWS explained in its announcement. "Each node possesses a hardware module composed of AWS-designed analytics processors that dramatically accelerate data compression, encryption, and data processing tasks like scans, aggregates, and filtering."

About the Author

Gladys Rama (@GladysRama3) is the editorial director of Converge360.


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