Amazon Web Services has announced a number of new offerings around data and analytics, including a new supply chain solution, and new enhancements for OpenSearch, Redshift and Aurora.
Announced at AWS’s re:Invent conference in Las Vegas by chief executive Adam Selipsky, the new AWS Supply Chain solution is a cloud-based application aimed to increase supply chain resilience by helping mitigate risks and lower costs.
The solution unifies supply chain data and provides machine learning-powered actionable insights for supply chain leaders and teams. It also features contextual collaboration to bolster customer service by reducing stock outs and reducing overstock costs.
AWS Supply Chain provides a real-time map showing inventory levels and health in each location, with insights and targeted watchlists alerting users to potential risks. It addresses risks through inventory rebalancing recommendations and the collaboration tools to coordinate teams to implement solutions.
The offering connects to a customer’s existing ERP system or supply chain management system without requiring any replatforming work, upfront licensing fees or long-term contracts.
AWS has not provided availability details yet for Australia, initially rolling out in select parts of the United States and Europe.
AWS Clean Rooms
The cloud giant also announced a new analytics service to help customers easily and securely analyse and collaborate on combined datasets without revealing underlying data.
Customers can create a secure data clean room within AWS and have access to a set of built-in data access controls that protect sensitive data, including query controls, query output restrictions, query logging, and cryptographic computing tools.
The solution is aimed at customers that require a complete view of their clients’ businesses, like those in the advertising industry, to improve the relevance of their campaigns and improve customer service, but also those who want to protect sensitive consumer information and reduce or eliminate the sharing of raw data.
The service will be available in Australia (Asia-Pacific Sydney) and other regions by early 2023.
Healthcare data
AWS also launched a new service for healthcare and life science customers called Amazon Omics, which stores, queries and analyses genomic, transcriptomic, and other omics data to generate insights for medical research use.
Omics is designed for scale analysis and collaborative research to allow storing and analysis of genome data from large groups to entire populations. It also automates provisioning and scaling of bioinformatics workflows to allow analysis at production scale.
The service has three main components, namely an optimised object storage service, managed compute for bioinformatics workflows (removing the need to provisioning underlying infrastructure) and optimised data stores for population-style variant analysis.
Enhancements for OpenSearch, Aurora and Redshift
Amazon OpenSearch, the Elasticsearch-based open source, distributed search and analytics suite, now has a serverless option to help simplify large-scale search and analytics workloads without having to configure, manage, or scale OpenSearch clusters.
OpenSearch Serverless automatically provisions and scales resources to speed up data ingestion and query responses through a pay-as-you-go model.
The offering decouples compute and storage to separate indexing and search components, using Amazon S3 as the primary data storage for the former. This allows both search and indexing to scale independently.
Amazon Aurora, AWS’s global-scale relational database service, now has an option to go zero-ETL (extract, transform and load) when integrating with Amazon Redshift, AWS’s cloud data warehouse offering.
The new service lets users bypass the need to build and maintain complex data pipelines to perform ETL operations, as well as allow analysing data from multiple Aurora database clusters in the same new or existing Amazon Redshift instance to derive insights.
Amazon Redshift now also has an integration with Apache Spark, an open source unified analytics engine for large-scale data processing, allowing users to run Apache Spark applications on Redshift data.
The integration builds on an existing open source connector project by improving its performance and security. The original project can be viewed in this Github repository.
AWS said the integration lets users bypass the manual process of setting up a spark-redshift open-source connector, allowing users to only specify the connection to a data warehouse and start working on the data immediately.
Nico Arboleda attended AWS re:Invent in Las Vegas as a guest of AWS.
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