AWS re:Invent 2022: Data Analytics Keynote Announcements
Josh Lopez
Partner Cloud Adoption, Versent
Josh Lopez
Partner Cloud Adoption, Versent
Amazon’s Vice President of Database, Analytics and Machine Learning, Swami Sivasubramanian, delivered a fascinating keynote addressing some exciting new services available across Data Analytics & Machine Learning. He focused on how data is the genesis for modern day innovation. It’s important to build a future proof data foundation that removes the heavy lifting for data preparation, performs at scale and has the highest level of security to protect your data. The two announcements that resonated with me the most were:
- Amazon DataZone: is very exciting as it allows you to catalog, discover, share and govern data across your organisation and from all your data sources. This allows you to integrate third party sources through APIs into one place and utilise the power of AWS to draw insights and data action from all data sources.
- Amazon GuardDuty RDS Protection: to protect your data in Aurora using intelligent threat detection. It is so important to protect the data and now with a click of a button you can be given further protection of the data that underpins your organisation.
I’ve put together all the announcements that were showcased in the keynote;
Databases
- Amazon DocumentDB Elastic Clusters: a fully managed solution to scale document workloads of any size and scale. It takes away the months of effort to build Document DB clusters.
- Amazon Redshift Multi-AZ which now delivers high availability and reliability to mission critical data warehouse workloads. It guarantees capacity to automatically failover in the event of an AZ disruption.
- Amazon Redshift auto-copy from S3 which automates the file ingestion from S3 to Redshift. No longer do you need to create Amazon Glue jobs to perform this task. It continuously ingests data as soon as new files are created in S3.
- Trusted Language Extensions for PostgreSQL which is an open source project to support extensions for Amazon RDS and Amazon Aurora. These trusted language extensions allow you to extend PostgreSQL to meet your security and innovative needs without waiting for AWS certification.
Data Governance
- Amazon DataZone allows you to catalog, discover, share and govern data across your organisation. It helps you analyse data within AWS and across third party data sources using APIs. It provides a unified environment to share data securely and analyse it.
- Amazon AppFlow adds 50 more connectors to include connectors for cloud based services like Google Ads, ServiceNow, Databricks and Salesforce. This allows you to connect all your SaaS based services that much easier.
- Amazon GuardDuty RDS Protection to protect your data in Aurora using intelligent threat detection. It only takes one click to enable. It delivers security findings enriched with contextual data so you can take action on any security incidents.
- AWS Glue Data Quality that automatically measures, monitors and manages the data quality in your data lake. It generates automatic data quality rules and if your data quality deteriorates you will be notified to take action.
- Centralized Access Controls for Redshift Data Sharing governs access to Redshift data using AWS Lake Formation. It centralises the access controls for Redshift and improves the security with row level and column level data sharing permissions.
Analytics
- Amazon Athena for Apache Spark which allows you to run interactive analysts on Apache Spark in under second. It enables you to spin up Spark workloads in 75x faster than other serverless Spark platform. Apache Spark runs 3x faster on AWS.
- Amazon SageMaker ML Governance which improves the governance and auditability for end-to-end development. In comes with three feature announcements in, Role Manager define custom user permissions in minutes, Model Cards centralises model information and Model Dashboard that monitors the model performance in one place.
- Amazon SageMaker now support Geospatial ML which makes it easier to build, train and deploy ML models using geospatial data. Geospatial ML assists the automotive, retail, agriculture and urban planning industries draw insights from geospatial data.
Education
- AWS Machine Learning University an AI & ML educator training program for community colleges and MSIs in the United States. It’s a train the trainer program to continue pushing the boundaries for educating students in AI & ML.
There’s plenty of announcements to digest that will accelerate drawing insights from your data. The innovations announced by Swami Sivasubramanian are certainly going to accelerate the data analytics adoption of Versent customers as we start to implement these fantastic new tools and services. If you need to speak to a consultant on how you can utilise these services to transform your business, please do get in contact with us.
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