Category: Analytics

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.

There is a growing trend of investment managers incorporating environmental, social, and governance (ESG) issues into their analysis. The increasing recognition of ESG factors within the investment process has created pressure on investment managers to adopts a robust ESG data strategy and framework. Learn how Tata Consultancy Services (TCS) has collaborated with AWS to offer the TCS ESG Integration Solution on AWS, which includes a cloud-native ESG data ingestion platform and custom ESG scoring model.

Dremio Cloud is a cloud lakehouse platform on AWS that democratizes data and provides self-service access to data consumers by connecting business intelligence users and analysts directly to data on Amazon S3 and beyond. Learn about the benefits of Dremio Cloud, how to set it up, and start using Dremio’s high-performance lakehouse platform in less than 15 minutes. Review Dremio Cloud’s key features and explore a getting started tutorial with sample datasets.

To quickly build intelligent data-driven workflows, organizations need business analysts to work with data scientists and development teams to unlock useful insights from unstructured or semi-structured data. Learn how KNIME’s end-to-end data science product portfolio helps bridge the gap between the ideation and productionalization steps of data science projects, while also assisting in the communication of key data science aspects between teams.

Amazon Athena is a serverless interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Data stored in S3 can span gigabytes to petabytes, however, and querying such massive data poses unique challenges. Follow along as experts from AWS and Innovative Solutions present a use case-based approach to help evaluate these challenges and propose solutions to improve Amazon Athena query performance.

Forward-looking finance teams will build resilience and responsiveness to future disruption. To deliver this strategic mandate, finance offices must be data-driven and share insights that help the organization connect, predict, and adapt within a changing business environment. Learn how Genpact’s data lake analytics reference architecture helps finance teams incorporate functional expertise into AWS solutions with the goal of delivering business impact beyond increased productivity.

Spatial data is a vital ingredient in today’s applications, enabling capabilities ranging from asset tracking and location-based marketing to monitoring deforestation and more. Learn about the most important areas that organizations need when working with spatial data in Amazon Redshift and how CARTO helps them unleash unique spatial visualization, analysis, and app development features right inside AWS’s cloud data warehouse.

Saint Louis University is at the cutting edge of research, studying human behavior and its economic impact. Learn how the Sinquefield Center for Applied Economic Research (SCAER) uses MontyCloud DAY2, a no-code autonomous CloudOps platform, to run an environment that’s fully automated and self-managed. MontyCloud also helps SCAER automate mounting and unmounting Amazon EBS volumes on demand when Amazon EC2 instances are provisioned.

A key goal of modern data strategy, whether a data mesh, data fabric, data lake, or data warehouse, is to deliver access to data when and where it’s needed. Learn how AWS and Informatica can combine and automate data governance for access within a data marketplace. This solution combines Information’s data governance architecture and the Informatica Intelligent Data Management Cloud (IDMC) which orchestrates and automates data access management with AWS Lake Formation.