Category: Case Study

Energy and process manufacturers are looking for mechanisms to predict asset breakdowns well before actual asset failure. Learn how Accenture Industrial Intelligence Suite addresses these challenges by using a strong data foundation, collecting and processing data from a variety of assets at scale. Accenture Industrial Intelligence Suite employs AI/ML models along with scalable AWS services to mitigate unplanned downtime, optimize asset performance, and improve asset reliability.

Learn how Accenture engineered a cloud-native SaaS learning platform that enables users to succeed in fast-paced environments. Take a look at why quick adoption is essential for an organization to acquire new knowledge, adapt mindsets, and develop new capabilities required to deliver changing business initiatives in a timely way. Accenture’s Future Talent Platform enables general or highly focused training to guide customers, partners, or employees to get the most out of new technologies or programs.

If your organization requires a faster time to market for Internet of Things (IoT) applications, AWS Partners have flexible, pre-built solutions to help reduce risk while building the foundational elements that are required to deploy an IoT solution at scale. Businesses interested in deploying an IoT solution should carefully consider which AWS Partner will best fit their organization’s needs, keeping in mind a few key elements, including capabilities, tenancy, security and compliance, migration, and pricing.

Feature engineering is a critical process in which data, produced by data engineers, are consumed and transformed by data scientists to train models and improve their performance. Learn how to accelerate data processing tasks and improve collaboration between data science and data engineering teams by applying MLOps best practices from Data Reply and leveraging tools from AWS. Data Reply is focused on helping clients deliver business value and differentiation through advanced analytics and AI/ML on AWS.

Many companies use online databases for talent sourcing, while others prefer more traditional means such as referrals or networking. Quantiphi’s cloud-native data platform facilitates the convergence of talent and recruiter performance data to provide crucial insights into the talent acquisition process. Explore the critical aspects of Quantiphi’s serverless, fully-managed ETL pipeline along with the benefits of the centralized lake house solution built on AWS in helping talent acquisition companies.

Getting SAP data into AWS in real-time enables insights for better business decisions, realizes competitive advantages, enhances sharing and collaboration, and improves operational performance. It also provides the opportunity to integrate data from SAP and non-SAP sources. Learn how to extract and integrate SAP data on AWS for use cases like analytics, reporting, AI/ML, and IoT in real-time, using the BryteFlow SAP Data Lake Builder on AWS.

Event-driven architecture makes building cloud applications easier, especially applications required to create, detect, consume, and react to multiple events in real time. Learn how DXC Technology helped a customer in the energy industry collect and push events from electricity meters using event-driven architecture. When application complexity increases, this event-driven approach provides better scalability, fault tolerance, and faster development.

Graph databases are useful for solving problems related to connected data, and represent data as nodes and enable organizations to uncover relationships between data that’s not possible with other approaches. Experts from AWS and Neo4j explore four types of databases and the most common applications for each: relational, document, in-memory, and graph. We’ll cover how different industries use graph databases and how they work as part of an AWS architecture.

Infor OS is the foundational enterprise application platform which connects Infor’s various software products and third-party solutions into a complete digital business platform. It enables ongoing innovation with support for AI/ML, integration, hyperautomation, application development, data management, and analytics. The platform delivers everything you need to tackle innovation use cases—from integration to automation and extensibility to data and insights.

Decentralized clinical trials (DCTs) put the patient at the center of the trial experience and incorporate digital technologies like AI/ML to address the challenges associated with traditional clinical trials. DCTs can reshape workflows across the clinical lifecycle—from trial design and patient recruitment to evidence generation. Explore key challenges addressed by DCTs and how SourceFuse is leveraging AWS to build the right solutions for its clients to transform clinical research.