Amazon’s annual technology event AWS re:Invent kicked off on Monday, and throughout the week the company has been making exciting announcements at the event.
The latest highlights from the event include:
Amazon previews OpenSearch Serverless
This new offering will enable customers to do analytics on their data without having to manage any of the underlying infrastructure. The platform will automatically provision and scale underlying resources for the user.
A benefit of the platform is that users don’t even have to take into account factors like frequency and complexity of queries, or the volume of data, as these can be difficult to predict in advance.
AWS DataZone announced
The new solution will make it easy to catalog, discover, share, and govern data that is stored across AWS, on-premises, or third-party sources.
It uses machine learning to suggest metadata for datasets and improve over time by training on the customer’s data taxonomy and preferences.
It also enables administrators to set the appropriate privilege levels for users to ensure that engineers, data scientists, product managers, analysts, and business users can access the data they need.
Integrations in Amazon Aurora with Amazon Redshift and Apache Spark
These two new integrations make it easier for customers to analyze their data across different storage locations, without having to move that data to do so. Typically, a user would need to perform extract, transform, and load (ETL) on that data.
Amazon is trying to move its customers toward a zero-ETL future, and these new capabilities help bring them a step closer to that.
“The vastness and complexity of data that customers manage today means they cannot analyze and explore it with a single technology or even a small set of tools. Many of our customers rely on multiple AWS database and analytics services to extract value from their data, and ensuring they have access to the right tool for the job is important to their success,” said Swami Sivasubramanian, vice president of Databases, Analytics, and Machine Learning at AWS. “The new capabilities announced today help us move customers toward a zero-ETL future on AWS, reducing the need to manually move or transform data between services. By eliminating ETL and other data movement tasks for our customers, we are freeing them to focus on analyzing data and driving new insights for their business—regardless of the size and complexity of their organization and data.”
Five new capabilities added to Amazon QuickSight
Amazon QuickSight is another business intelligence tool that can be used for analytics at scale. Amazon QuickSight Q, which is a natural language querying capability, now offers support for asking “why” questions, such as “why did sales increase last month?” Amazon QuickSight Q also now automatically infers and adds semantic information to data. This significantly reduces the amount of time that is spent on data preparation.
Reporting capabilities have also been updated with the addition of paginated reports. These reports offer a formatted summary of data to share critical information. According to Amazon, with other solutions companies need to maintain multiple systems to produce paginated reports: one for analyzing the data and another for producing reports.
Billion-row support has been added to the calculation engine SPICE, which will allow teams to analyze larger datasets.
And finally, QuickSight now enables customers to create, manage, and edit business intelligence assets through an API. This will allow them to accelerate migrations from legacy systems.
Amazon Security Lake available in preview
This new service provides a centralized location for storing security data to enable customers to act on insights from that data faster.
It includes customizable data retention settings for data throughout its life cycle. It converts incoming data into the Apache Parquet format, then conforms it to the Open Cybersecurity Schema Framework standard.
According to Amazon, most companies rely on log and event data from multiple sources, which must then be converted to a consistent format before it can be analyzed. Customers often rely on various solutions to do these analyses, which leads to duplicate data, which is time consuming and costly.
“Amazon Security Lake lets customers of all sizes securely set up a security data lake with just a few clicks to aggregate logs and event data from dozens of sources, normalize it to conform with the OCSF standard, and make it more broadly usable so customers can take action quickly using their security tools of choice. With Amazon Security Lake, customers get superior visibility and control, with help from the largest ecosystem of security partners and solutions,” said Jon Ramsey, vice president for Security Services at AWS.