Tag: Amazon SageMaker

We’re excited to announce the launch of the Amazon SageMaker Ready specialization for AWS Partners with Amazon SageMaker software offerings. Through this specialization, customers can identify software solutions that integrate with Amazon SageMaker—allowing them to seamlessly solve use cases and innovate with machine learning. Software offerings include data platforms, data pre-processing and feature stores, ML frameworks, MLOps tools, and business decisioning and applications.

Enterprises are building data analysis capabilities to extract information captured in data, develop an understanding of their business, and channel efforts towards customer centricity. This post explains the need for operational analytics and how it can be achieved with MongoDB Atlas and Amazon Redshift. MongoDB is an AWS Data and Analytics Competency Partner and developer data platform company empowering innovators to unleash the power of software and data.

Teradata has expanded its collaboration with AWS by adding integration capabilities for Teradata Vantage, the data platform for enterprise analytics and AWS cloud services. Vantage, with its NOS read/write connector to Amazon S3 data, already provides data integration with S3 data and Vantage enterprise data. Now, Teradata introduces an API integration with Amazon SageMaker and Amazon Forecast. This enables business users to drive outcomes with real-time analytics.

One of the most exciting evolutions in cloud computing is the proliferation of hybrid cloud and edge computing services. Learn how the Confluent for AWS Wavelength solution was developed to bring Confluent’s data-in-motion technology to the network edge. We’ll demonstrate how the solution extends Confluent for Kubernetes (CFK) to Amazon EKS self-managed nodes in AWS Wavelength Zones to create a geo-distributed Kafka cluster at-scale for industrial IoT and low-latency 5G use cases.

Sales order fulfillment and billing can impact customer satisfaction, and receivables and payments affect working capital and cash liquidity. As a result, the order-to-cash process is the lifeblood of the business and is critical to optimize. Qlik Cloud Data Integration accelerators integrate with Snowflake to automate the ingestion, transformation, and analytics to solve some of the most common SAP business problems, enabling users to derive business insights that can drive decision-making.

A unified, autonomous, and fully digital airline operations solution can help mitigate challenges related to cost inefficiency, latency, or suboptimal decisions and their consequences, including cost, disruption, and customer dissatisfaction. TCS Aviana is an AI-based solution developed by Tata Consultancy Services (TCS) that enables airlines to have comprehensive operations visibility, digital collaboration, and data-driven decision-making through connected insights and intelligence.

Through the Pega Platform and Amazon SageMaker, you can easily streamline the development and operationalization of machine learning models to improve process automation. This allows customers to combine the strengths of cloud, data, and machine learning with AI-powered decisioning and smart workflow capabilities. It also enables customers to operationalize and monetize data and insight, drive process efficiency and effectiveness, and improve customer experience and value.

Many organizations stay on track and achieve objectives by conducting a constructive analysis of strengths and weaknesses, but revenue and profitability analysis are not easy tasks. Explore why Metrodata chose AWS as a trusted platform to build SAP analytics offerings such as revenue and profitability analysis. These offerings empower customers to make business decisions quickly and effectively to expand in new market opportunities and focus on key growth areas.

The AWS Machine Learning Visionaries Partners Report is a quarterly series that tracks, selects, collates, and distributes horizontal technology capabilities enabled by machine learning in areas that AWS expects to be transformative in 1-3 years. The series’ purpose is to share our insights with AWS Partners and to collect their interest, expertise, and insights in co-building along these prioritized themes. The reports include updates on series topics as we see changes in those areas, and new topics will also be added.

Infusing machine learning into core business processes such as credit scoring creates a competitive edge for banks and financial services institutions. It does not require a data science team, expertise, or platform rollout. Explore an ML-based credit-decisioning model built by ElectrifAi in collaboration with AWS whose model rapidly determines the creditworthiness of a SME, and data-driven, actionable insights reduce the overall processing cost and are consistent and free from any potential human biases.