AWS sharpens focus on modern data strategies with an array of new products

Amazon Web Services (AWS) is on a mission to enable organizations — including startups, enterprises and government agencies — to become more agile and innovate faster at lower costs. Last year, an AWS executive told VentureBeat that a priority for AWS in 2022 will be automation at scale, allowing customers to bolster the security of their cloud environments.

To advance its mission, AWS today unveiled innovations across several services, including databases, machine learning, IoT and application development. The announcement came yesterday at the AWS Summit, San Francisco, where Swami Sivasubramanian, VP of data, analytics and ML services at AWS, offered details on the new product offerings in a keynote address.

While AWS has seen massive adoption, according to Sivasubramanian, it’s just getting started. His 90-minute keynote highlighted AWS’ plans to expand its capabilities and services across more global regions and to scale up the pace of innovation for customers.

The need for more innovation

Sivasubramanian said analysts estimate that 5% to 15% of IT spending has moved to the cloud — a sign that many more workloads will migrate to the cloud in the coming years. He noted that this meant there’s a need for more innovation. While the primary benefits of agility, cost and elasticity were major reasons many customers chose AWS, Sivasubramanian said AWS’ capability to speed up the pace of innovation was another key benefit. With an enormous vibrant partner ecosystem of more than 100,000 partners, he said AWS is constantly thinking of ways to invent on behalf of its customers.

“In 2021 alone, we added 3,084 services and significant features. That is 3,084 more capabilities that our customers are equipped with to address the needs of today and the future. Since the challenges for a customer today are often different from the ones of tomorrow, it makes it all the more important to pick the cloud provider that will be the best technology partner now but also in the future,” he said.

How a data-driven approach boosts growth

Sivasubramanian said effective leaders use the immense amount of data that is available to them to make informed decisions, look around the corners and take meaningful action. He said such organizations build a modern data strategy to deliver insights to the people and applications that need it.

According to Forrester, organizations that take a data-driven approach to decision-making grow more than 30% annually. However, most organizations aren’t able to put this wealth of data to work. A recent Accenture study revealed 68% of companies are not able to realize tangible and valuable benefits from the data. Sivasubramanian said that’s the case because it’s not easy for organizations to instantly turn on a switch and become data-driven.

“It requires leaders to truly embrace data-driven decision making and set the expectation that decisions need to be anchored in data. They also need to lead by example, and make data driven decision making. And there are also technical challenges when it comes to setting up access control and scaling your data infrastructure,” he said 

Sivasubramanian added that these factors can slow down organizations that are trying to put the data to work to solve these challenges. He added that modern data strategy needs to be scalable, flexible, able to address various use cases and also support the projects of tomorrow. It also has to consider things like governance, according to Sivasubramanian, ensuring that the right people have access to the right data. It must be available when it’s needed, in a cost effective manner.

“Your infrastructure should serve the needs of the business data at every stage of its journey — from databases and data lakes, to putting it to work through analytics and machine learning with the right governance and controls embedded throughout. Our customers are using AWS tools and services to become data-driven organizations and make faster data decisions.”

Building a modern data strategy

Sivasubramanian said a typical modern data strategy comprises three pillars: modernize, unify and innovate. He noted that customers start modernizing that infrastructure by first migrating to the cloud and moving towards infrastructure that enables them to achieve the scale they need at the right costs while reducing the operational burdens.

Then they unify the data storage and access control infrastructure. Finally, they put the data to work by leveraging analytics and ML on top of the data.

“Modernizing your data infrastructure allows you to remove costly, undifferentiated heavy lifting, such as database provisioning, patching and continuous backups, failover maintenance, software licensing and more.”

This is where AWS comes in. According to Sivasubramanian, AWS’ unmatched experience, maturity, reliability, scalability and performance is the solid foundation for building organizations’ data-driven applications.

AWS’ new product offerings will help organizations to be even more agile and innovate faster, cost-effectively, he said.

AWS new product offerings

Here are the new services and features announced at the AWS Summit.

1. Amazon Aurora Serverless v2 is generally available: instant scaling for demanding workloads: AWS says Amazon Aurora Serverless v2 scales capacity in fine-grained increments based on an application’s needs, all while including Amazon Aurora’s capabilities for high availability, performance, and resiliency, with low latency and fast querying.

AWS claims Aurora Serverless v2 provides customers up to 90% cost savings compared to provisioning database capacity for peak loads. Some customers using this product include healthcare software provider, 3M and managed WordPress hosting platform, Pagely.

2. Amazon SageMaker Serverless Inference general availability – machine learning inference without worrying about servers: While Amazon SageMaker automatically provisions, scales, and turns off compute capacity based on volume of inference requests, the GA launch of Amazon SageMaker Serverless Inference allows customers to pay only for the duration of running the inference code and the amount of data processed.

According to AWS, the elimination of idle time payments makes it ideal for applications with intermittent or unpredictable traffic, helping to scale compute capacity based on the volume of inference requests without a need for forecasting traffic demand up front or managing scaling policies. Customers include software and AI companies Bazaarvoice and Hugging Face, among others.

3. AWS IoT TwinMaker is now generally available: Amazon first debuted the AWS IoT TwinMaker last year. Today, the service is now generally available today in US East (Northern Virginia), US West (Oregon), Asia Pacific (Singapore and Sydney), Europe (Frankfurt), and Europe (Ireland) with availability in additional AWS regions coming soon. The AWS IoT TwinMaker makes it easier for businesses to create digital twins of real-world systems like buildings, factories, industrial equipment, and production lines.

With IoT TwinMaker, customers like Siemens Digital Industries Software, Carrier, INVISTA, John Holland and others can use digital twins to build applications that mirror real-world systems that improve operational efficiency and reduce downtime.

4. AWS Amplify Studio is now generally available: AWS Amplify Studio is a new visual development environment for creating web application user interfaces (UIs) that extends AWS Amplify so developers can create fully customizable web applications on AWS with minimal coding. With Amplify Studio, developers can create a UI using a library of prebuilt components, collaborate with UX designers, and connect their UI to AWS services through a visual interface without writing any code.

AWS Amplify Studio then converts the UI into JavaScript or TypeScript code, which saves developers time and energy while allowing them to customize their web application design and behavior using familiar programming languages.

5. Amazon Textract: Amazon Textract, a machine learning service that automatically extracts text, handwriting and data from any document or image, is announcing its newest offering to specify data and extract from documents using the new Queries feature.

This feature allows users to specify the information needed in the form of natural language questions and receive the exact information as part of the API response. The feature uses a combination of visual, spatial, and language models to extract the information users seek with high accuracy. Some customers already using this product include cloud services and enterprise architecture company TekStream Solutions and supply chain management consulting firm Camelot Management Consultants.

6. Amazon QuickSight Embedded Analytics Partner Program: Amazon QuickSight — a cloud-native, serverless business intelligence (BI) service — is designed to help customers create and share interactive analytics with thousands of end-users, allowing interactive dashboards, visualizations, and ML-powered natural language queries to be embedded into apps and portals. The Amazon QuickSight Embedded Analytics Partner Program is designed to allow AWS customers to find trusted AWS partners that can help integrate Amazon QuickSight with hands-on assistance and long-term stability. Current partners include PwC, Rackspace and several others.