Tag: AWS Partner Success Stories

Amazon EC2 Mac instances allow customers to bootstrap macOS machines in the cloud and use these for building, testing, and deploying iOS applications with the security, scalability, and flexibility of the cloud. Learn how TeamCity, developed by JetBrains, is a common CI/CD automation tool for developers that offers the ability to use build agents, distribute CI/CD pipelines across machines, or schedule parts of a pipeline to a specific instance type or container.

As data grows at an exponential rate both in volume and velocity, it becomes important for organizations to carve out a strategy to store data in appropriate locations with the correct safeguards to address data access and privacy concerns. Learn how organizations can transform their data landscape into a more controlled, flexible, and secure landscape using LTI’s Canvas Scarlet Data Mesh framework built on AWS to meet the data challenges an organization faces today.

A closed loop assurance system predicts network events, such as faults and congestions, that are highly probable of causing service degradation or interruption, and automatically take preventive actions to avert service disruptions. Learn how Infosys leveraged AWS data streaming, data analytics, and machine learning services to ingest, process, and analyze high volumes of data from disparate sources; and to build ML models to predict network events that cause service degradation.

By powering personalized, relevant, and timely digital interactions built on guest behavior data, Braze can help AWS lodging customers generate additional revenue and engage guests for the long run using personalization. Learn how a hotel customer can rapidly and simply transform their web booking engine into a digital user engagement solution offering a personalized booking experience including upsell capabilities.

CAD on the cloud delivers the same, if not better, performance than on-premises setup. For enterprises, it will be a paradigm shift to have their CAD/CAE workload on the cloud, especially using Amazon AppStream 2.0. Learn about Infosys’ flagship Cobalt program, one of the largest service providers in engineering and design, with decades of experience helping customers leverage AWS to optimize cost and performance.

Learn how DXC Technology was able to leverage Amazon ECS Anywhere to fulfill regulatory and compute requirements and increase operational efficiency for a use case for an in-house proprietary tool where a part of the application stack must run on premises. DXC needed a hybrid cloud solution to execute their toolkit data capture and analysis strategy without major changes in application design or architecture.

Learn now Provectus looked into how machine learning models were prototyped and evaluated at VTS, and then delivered a template-based solution enabling their data scientists to more easily create Amazon SageMaker jobs, pipelines, endpoints, and other AWS resources. The resulting coherent set of templates, with usage cookbook and extension guidelines, was applied successfully on an ML model that predicted leasing outcomes.

In construction, new methods of capturing site information, such as laser scanning, photogrammetry, drone photography, and continuous video monitoring have presented challenges for file storage, analysis, and archiving. Learn how the Nasuni Analytics Connector can help architecture, engineering, and construction customers gain business insight from file data, while using many of the network-attached storage they’re familiar with.

Data is the most important resource available to modern institutions. The challenge is not necessarily generating, cataloging, or storing data, but operationalizing it. Palantir Foundry is an operations platform that leverages existing data systems and analytics tooling to power smarter decision-making. Learn how Palantir HyperAuto can rapidly integrate data from ERP systems and operationalize that existing data against pressing business problems.

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.