Tag: AWS Partner Guest Post

Customers often need to rely on third-party solutions to extract and transform data from sources such as Slack and Zendesk. Some vendors, however, do not support all of the sources and rely on multiple products to perform ETL and persist data into Snowflake. This post details how Amazon AppFlow simplifies the data transfer process, and how customers can use AWS PrivateLink for transmitting data over AWS rather than via the public internet.

AWS customers are increasingly searching for new ways to manage access in a scalable way that maintains the benefits of an agile DevOps delivery model. However, the traditional and highly-manual processes for assessing and certifying access quickly demonstrates they cannot keep up with the speed of DevOps changes. Learn how PwC designs and implements baseline IAM roles for customers while leveraging usage-based analytics to identify overprivileged roles.

Moving data between multiple data stores requires an extract, transform, load (ETL) process using various data analysis approaches. ETL operations form the backbone of any modern enterprise data and analytics platform. AWS provides a broad range of services to deploy enterprise-grade applications in the cloud. This post explores a strategic collaboration between Tech Mahindra and a customer to build and deploy an enterprise data repository on AWS and create ETL workflows using a serverless architecture.

Scaling doctors’ expertise through artificial intelligence (AI) and machine learning (ML) provides an affordable and accurate solution, giving millions of infants equal access to eye screening. Learn how Pr3vent, a medical AI company founded by ophthalmologists, teamed up with AWS Machine Learning Competency Partner Provectus to develop an advanced disease screening solution powered by deep learning that detects pathology and signs of possible abnormalities in the retinas of newborns.

Learn how to enrich the AWS Well-Architected Tool’s workload report by adding the results of definitive best practice checks. This post will also associate the workload with specific AWS resources through the use of tags. Once the workload is tagged, you can use Trend Micro’s Cloud One – Conformity, which allows you to create a 360-degree workload review. This provides continuous assurance that your resources are complying with the AWS Well-Architected Framework.

Continuity Software helps enterprises achieve resilience in their IT environments, drastically reducing outages, and protecting data before it is lost, damaged, stolen, or unrecoverable. Learn how Continuity’s Coral solution automates adherence to all five pillars of the AWS Well-Architected Framework. This ensures environments adhere to the best practices to drive better outcomes for workloads while helping customers avoid disruptions.

Sumo Logic ingests data across your entire application stack to provide observability and, therefore, reliability of mission-critical apps. It eases the burden placed on engineers, simplifying data collection, unifying visibility, and leveraging machine learning to speed troubleshooting. Sumo Logic’s Observability solution is designed specifically for AWS and seamlessly detects anomalies and events of interest correlated with application incidents.

In a global pandemic, it can be hard for medical practitioners and patients to get connected and treated. Continually being on top of patients’ progress is also a challenge, along with scarcity of doctors who themselves are affected by the pandemic. Learn about a reference architecture from Capgemini that uses AWS machine learning services to enable doctors and patients to interact with the least amount of physical contact, while also improving efficiency in treatment management, tracking, and auditing.

Organizations often need business analysts and citizen data scientists to work with data scientists to create machine learning (ML) models, but they struggle to provide a common ground for collaboration. Newly enriched Dataiku Data Science Studio (DSS) and Amazon SageMaker capabilities answer this need, empowering a broader set of users by leveraging the managed infrastructure of Amazon SageMaker and combining it with Dataiku’s visual interface to develop models at scale.

Tens of thousands of customers use Amazon Redshift to process exabytes of data per day and power analytics workloads such as business intelligence, predictive analytics, and real-time streaming analytics. Learn how Etleap integrates with new data sharing and cross-database querying capabilities in Amazon Redshift to enable workload isolation for diverse analytics use cases in customer environments. Etleap integrates with any data source and runs either as a hosted solution (SaaS) or inside your VPC.