AWS sharpens focus on modern data strategies with a range of new products

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

To further its mission, AWS today unveiled innovations across a variety of 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 about the new product offering in a keynote address.

While AWS has been massively adopted, according to Sivasubramanian, it is only just getting started. His 90-minute keynote highlighted AWS’ plans to expand its capabilities and services into more global regions and to scale 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 notes that this requires more innovation. While the key benefits of agility, cost and elasticity were the main reasons many customers chose AWS, Sivasubramanian said AWS’s ability to accelerate the pace of innovation was another key benefit. With a hugely vibrant partner ecosystem of more than 100,000 partners, he says AWS is constantly thinking about ways to invent on behalf of its customers.

“In 2021 alone, we added 3,084 services and key features. That’s 3,084 additional capabilities that equip our customers to meet today’s and tomorrow’s needs. As the challenges for a customer today are often different from those of tomorrow, it is all the more important to choose the cloud provider that will be the best technology partner now and in the future,” he said.

How a data-driven approach drives growth

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

According to Forrester, organizations that adopt a data-driven decision-making approach are growing at more than 30% annually. However, most organizations are unable to put this wealth of data to work. A recent Accenture survey found that 68% of companies are unable to derive tangible and valuable benefits from the data. Sivasubramanian said this is the case because it is not easy for organizations to immediately flip a switch and become data-driven.

“It requires leaders to truly embrace data-driven decision-making and create the expectation that decisions should be anchored in data. They also need to lead by example and make data-driven decisions. 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 trying to put the data to work solving these challenges. He added that a modern data strategy must be scalable and flexible, be able to address different use cases and also support the projects of tomorrow. It also needs to take into account things like governance, Sivasubramanian said, making sure the right people have access to the right data. It must be available when it is needed, in a cost-effective manner.

“Your infrastructure must meet the needs of the business data at every stage of the journey — from databases and data lakes to putting it to work through analytics and machine learning with the right governance and controls embedded everywhere. 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 consists of three pillars: modernize, unify and innovate. He noted that customers are beginning to modernize that infrastructure by first migrating to the cloud and moving to an infrastructure that enables them to achieve the scale they need at the right cost while reducing operational burdens.

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

“By modernizing your data infrastructure, you can eliminate costly, undifferentiated heavy tasks such as database provisioning, patching and continuous backups, failover maintenance, software licensing, and more.”

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

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

AWS New Product Offerings

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

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

AWS claims that Aurora Serverless v2 offers customers up to 90% cost savings compared to provisioning database capacity for peak loads. Some of the customers using this product include health software provider 3M and the 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 disables compute capacity based on the volume of inference requests, the GA launch of Amazon SageMaker Serverless Inference enables allows customers to pay only for the duration of the inference code execution 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, allowing compute capacity to scale based on the volume of inference requests without the need to pre-predict traffic demand or manage scaling policies. Clients include software and AI companies Bazaarvoice and Hugging Face.

3. AWS IoT TwinMaker is now generally available: Amazon first introduced the AWS IoT TwinMaker last year. Today, the service is now generally available in the Eastern US (Northern Virginia), Western US (Oregon), Asia-Pacific (Singapore and Sydney), Europe (Frankfurt), and Europe (Ireland) and will be available soon in other AWS regions. The AWS IoT TwinMaker makes it easier for businesses to create digital twins of real-world systems such as buildings, factories, industrial equipment, and production lines.

With IoT TwinMaker, customers such as Siemens Digital Industries Software, Carrier, INVISTA, John Holland and others can use digital twins to build applications that mirror real 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 to allow developers to create fully customizable web applications on AWS with minimal coding. Amplify Studio allows developers to create a user interface using a library of pre-built components, collaborate with UX designers, and connect their user interface to AWS services through a visual interface without writing any code.

AWS Amplify Studio then converts the user interface into JavaScript or TypeScript code, saving developers time and energy, while allowing them to customize the design and behavior of their web application 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 latest offering to specify and extract data from documents using its new Queries feature.

This feature allows users to specify the necessary information in the form of natural language queries 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 are looking for with high accuracy. Some customers already using this product include cloud services and enterprise architecture firm TekStream Solutions and supply chain management consultancy 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, enabling interactive dashboards, visualizations, and ML-powered natural language queries to be embedded in apps and portals.

Current partners include PwC, Rackspace and several others.

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