This blog post provides an overview of the IBM Software Data and AI portfolio on Amazon Web Services (AWS) and highlights a few of the new product launches at AWS re:Invent 2022.

The importance of data and AI

Data and analytics have changed enterprise companies drastically in the last few years. According to Forrester Research: “AI adoption is no longer an emerging trend, with 73% of data and analytics decision-makers building AI technologies and 74% seeing a positive impact in their organizations, according to Forrester’s Data And Analytics Survey, 2022. As more companies succeed in implementing the fundamentals of AI practices, we are seeing the beginnings of a step-change surge of horizontal and vertical use cases that are transforming the way enterprises perform fundamental functions — from coding to content generation. Enterprises of any size from any industry can capitalize on at least some of the opportunities offered by the implementation of AI-supported software development and visual/textual content generation, deliberate governance reporting, faster time to care in healthcare, and increased trust with users engaging transparently with virtual agents.”

As enterprises adopt AI across their organizations, new trends are emerging, according to Forrester. These trends will require organizations to build or acquire hybrid products that can accelerate machine learning model development and production deployment, content generation, and virtual human assistance for improved trust. These new trends are placing executives closer to the business applications and ethical implications of AI, with Forrester predicting that “one in four tech execs with report to their board in AI governance.”

Here at IBM Data and AI, we are dedicated to helping our clients find success in numerous industries by taking advantage of artificial intelligence, machine learning, and data science technology that exists across the hybrid cloud. We pride ourselves in being an industry leader that is widely recognized by analysts, such as IDC (WorldWide Semiannual intelligence tracker) and Gartner (2021 Magic Quadrant for Data Science and Machine Learning Platforms).

IBM Data and AI on AWS

At IBM, we always strive to be at the forefront of innovation. Our Hybrid Cloud Strategy allows our customers to build applications once and deploy them across any environment -- whether it’s public cloud, private cloud, or edge-based. This gives our customers the flexibility and agility they need to stay ahead of the competition.

Over the last 18 months, we've been expanding our strategic partnership with AWS in order to better serve our customers. This expansion has enabled us to provide support for a broad range of IBM Data and AI Software products on the AWS platform. By partnering with AWS, we can offer our customers the scalability and rapid deployment of AWS services, as well as IBM product-native integration support for different AWS Services. This allows our joint customers to extract the greatest potential from their solution architectures across hybrid cloud environments.

Discover how IBM Data and AI solutions can help your business on AWS.

Today, at AWS re:Invent 2022, we, as an AWS partner, are excited to review the IBM Data and AI Portfolio and share some insight around our 24-plus software offerings that are available on AWS. These offerings are industry proven, AWS Well Architected, and AWS FTR-compliant. Within IBM Data and AI, we segment our offerings on AWS into three core categories (see Figure 1).

Diagram shows IBM Data and AI software products and use cases on AWS

Data applications: The IBM data applications portfolio is designed to help those with limited machine learning knowledge, whether they be application developers or domain experts. The goal is to make it easy for enterprises of all sizes to adopt and integrate machine learning into their organizations.
Data fabric: IBM data fabric capabilities focus on helping both data scientists and data stewards build end-to-end lifecycle management for data operations and machine learning development. IBM Cloud Pak for Data provides customers with access to integral products such as IBM Watson Studio and IBM Watson Knowledge Catalog. These allow customers to achieve data integration, governance, and insights.
Data store and workload: IBM data store and workload products focus on helping data engineers, researchers, and academics with data management, high-performance computing, and large machine learning model support.

IBM data applications

IBM data applications offerings reduce the skills requirement and minimize the time needed to build, implement, and scale enterprise-grade AI. Each offering is designed for businesses, users, developers, and subject matter experts to create and tailor models for their specific domains and use cases. Highlighted offerings include:

IBM Watson Discovery: Find answers, monitor trends, and surface patterns in high volumes of structured and semi-structured data. Build domain-specific AI that’s able to understand complex, high-value documents and respond to questions with concise, trusted, and personalized answers.
IBM watsonx Assistant: Build customer service chatbots and virtual agents that can understand complex customer inquiries and improve customer experiences in any channel. Integrate AI into existing applications, content, and data.
Embeddable AI: Adding enterprise-grade AI to your applications and solutions has never been easier. Embeddable AI is a flexible, first-of-a-kind suite of IBM Watson APIs and advanced natural language processing (NLP) solutions, such as watsonx Assistant or Watson Discovery, that makes it simple to add powerful cognitive capabilities to any application or solution.

While we have seen considerable adoption of IBM Data Applications, our customers have also indicated their interest in these IBM products as software as a service (SaaS). Industry analysts also share similar perspectives on enterprise demand for SaaS (cloud services). In fact, IDC in its SaaSPath Survey 2021, indicates that “80% of businesses across functional markets currently use or plan to deploy SaaS.” Interestingly, IDC also states that while “buyers recognize the value of a new generation of SaaS applications that are composable, intelligent, and data-driven … 80% indicate a willingness to pay more for SaaS applications infused with AI-enabled automation and advanced analytics [and] 82% cite the need for “greater portability and agility as justification for paying more for cloud-native SaaS.”

Earlier this year, IBM announced that we had signed a strategic collaboration agreement with Amazon Web Services to deliver IBM Software-as-a-Service on AWS. We indicated that “clients will be able to procure the IBM SaaS products in AWS Marketplace, and then set up and integrate with AWS services, allowing them to get started with just a few clicks, without deploying, updating, or managing any of the infrastructure. IBM SaaS products on AWS are designed to provide high availability and elastic scaling on demand to meet unpredictable throughput needs, and will offer a native AWS experience with deep integration of AWS services out of the box.”

Today, at AWS re: Invent 2022, we promoted our upcoming launch of IBM Planning Analytics with Watson as a SaaS Solution on AWS. IBM Planning Analytics is an AI-infused solution that streamlines planning, budgeting, and forecasting across every part of the organization. With Planning Analytics, customers can create more responsive plans that adapt to changing market conditions in real time. It can handle increasing data volumes and user demands without negative consequences to speed or function.

IBM Data Fabric

IBM Cloud Pak for Data enables enterprises to create a data fabric that helps unlock the full potential of their data, whether it is stored in AWS or in other cloud environments. Customers can take advantage of a comprehensive suite of tools and services that can be used to collect process, govern, and analyze data:

Multi-cloud data integration: Provide a single, unified view of data from across on-premises and cloud locations. Enable simple, efficient access to data without impacting mission-critical systems. Easily connect and query from multiple AWS, third-party, and open source data sources.
Data governance: Leverage an AI-augmented data catalog to automate data governance and privacy. Ensure regulatory compliance and automatically apply industry-specific regulatory policies. Dynamically identify and mask personally identifiable information (PII) without human involvement.
AI governance: Deliver trustworthy AI with improved model development, transparency, and explainability. Introduce governance and transparency at each stage of the AI lifecycle. Monitor AWS SageMaker and third-party models at runtime for fairness, drift, and explainability.
Data science: Utilize diverse coding and visual tools to refine data as well as develop and deploy ML models. Build models in minutes using IBM AutoAI and export models as Jupyter notebooks for use in AWS SageMaker.

Diagram shows IBM Data Fabric integrations with AWS databases and AWS SageMaker

Integrations allow Data Fabric to augment existing AWS data architectures and get more out of their investment in on-AWS data sources and services. For example, customers can use Data Fabric to pull and integrate data from AWS S3, AWS RedShift, MongoDB, and Snowflake through a single, optimized query. Data Fabric can then automatically identify and mask PII and apply governance rules to ensure compliance and data quality.

Data Store and Workloads

IBM Data Store products provide high-performant online analytical processing (OLAP), online transactional processing (OLTP), and high-performance computing (HPC) solutions that enable efficiency at any scale:

Db2 Portfolio -- Db2's databases are extremely high-performing and resilient, offering low-latency transactions and real-time analytics that will suit any business requirement. Db2's best-in-class failure detection and recovery system allow customers to eliminate unplanned downtime without sacrificing performance levels.
IBM Spectrum Portfolio -- IBM Spectrum on AWS not only quickens high-performance computing, data analytics, and simulation environments for clients in industries like Aerospace, Financial Services, Defense, and Life Sciences, -- it also boosts resource utilization so customers see a greater ROI.

Summary and next steps

To learn more, visit the IBM Developer Amazon Web Services (AWS) hub and check out the AWS Marketplace to review our Data and AI offerings from IBM.

And be sure to check out the associated IBM Developer article, "Monitor machine learning models for bias and drift using IBM Watson OpenScale integrated with Amazon SageMaker." This article demonstrates how IBM Watson OpenScale can be used to monitor models created using Amazon SageMaker to identify and reduce bias and drift, and how AWS Services and IBM Cloud Pak for Data can be integrated to create an effective solution.

About the IBM AWS partnership

For companies looking to enable and accelerate their customers hybrid cloud journey by leveraging AWS’ cloud platform, IBM brings leading-edge technologies and expertise on AWS through a unique combination of IBM Consulting, Software, and as-a-service capabilities. From concept to scale, our end-to-end solutions and proven methods help companies modernize their applications and infrastructure with speed and consistency so businesses stay ahead of the curve.

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IBM Data and AI on AWS: Unlock the power of your data

IBM Data and AI on AWS: Unlock the power of your data