Since 2011, hc1 has emerged as a bioinformatics leader in precision testing and prescribing. The hc1 platform built on AWS organizes live data, including lab results, genomics, and medications, to deliver solutions ensuring the right patient gets the right test and right prescription at the right time. Learn how hc1 ingests, organizes, and normalizes customer data to deliver analytics and improve operations management. As an outcome, customers use these insights to their fullest potential.
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.
Announced during a Partner Awards Gala at AWS re:Invent, the 2022 AWS Partner Awards recognize a wide range of AWS Partners which have embraced specialization, innovation, and collaboration over the past year. AWS Partner Awards honor partners whose business models continue to evolve and thrive on AWS as they work with customers. Please join us in congratulating these top AWS Partners who are dedicated to helping customers build, market, and sell their offerings so they can grow successful cloud businesses.
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.
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.
AWS is excited to unveil the 2022 Partners of the Year from Canada. Announced during the AWS Toronto Partner Summit, the awards recognize AWS Partner Network (APN) members who have demonstrated outstanding results and innovation using AWS products and solutions. Their expertise allows AWS customers in a wide range of industries—from finance to sports, startups to the public sector—to transform their industries and solve the most difficult business challenges.
A SaaS data platform may run in the account of an ISV or a dedicated account provided by the customer. Learn about the main AWS services SaaS data platforms can integrate with to provide customers with a seamless experience and take advantage of AWS services in order to accelerate their drive to meeting their business goals. Explore how those integrations can be built and examples of AWS ISV Partners who have successfully developed these integrations.
Data-centric AI (DCAI) has been described as the discipline of systematically engineering the data used to build an AI system. It prescribes prioritizing improving data quality over tweaking algorithms to improve machine learning models. In this post, explore a DCAI solution built on Snowflake and Amazon SageMaker to serve as a factory for predictive analytics solutions. Learn about Snowflake’s integrations with SageMaker and get hands-on resources to help you put these capabilities into practice.
Using Snowflake to Access and Combine Multiple Datasets Hosted by the Amazon Sustainability Data Initiative
The zero-cost Amazon Sustainability Data Initiative (ASDI) seeks to accelerate sustainability research and innovation by minimizing the cost and time required to analyze large sustainability datasets. In this post, we’ll use Snowflake, a data cloud company, to work with two different ASDI datasets containing climate and air quality data. We’ll demonstrate how to access ASDI datasets, join them together by date, and ultimately form a merged result.
Healthcare customers use Snowflake to store all types of clinical data in a single source of truth. One method for gaining insights from this data is to use Amazon Comprehend Medical, which is a HIPAA-eligible natural language processing service that uses machine learning to extract health data from medical text. Learn how the Snowflake Data Cloud allows healthcare and life sciences organizations to centralize data in a single and secure location.