Category: Analytics

Virtual care is fast emerging as an important tool in driving this shift and delivering on the desired outcomes. Learn how the HARMAN Intelligent Healthcare Platform leverages AI/ML, cloud services, and data to unlock value for clients and seamlessly transform data, analytics, intelligence, and governance functions in a secure, cost effective, and privacy-preserving process. It offers improved customer experience and engagement through predictive analytics and actionable insights on data harnessed from disparate sources.

The Internet of Things (IoT) is a fast-growing and innovative area that enables AWS customers to support a wide variety of use cases. IoT customers can also stream sensor data into a data lake where insights can be gathered by leveraging AWS machine learning services. Learn how Noser Engineering helped a customer build a general digital twin platform that is capable of adapting to rapid changes in the twined building through the integration of many different sensor types.

To get the most out of your data, you must first collect it and then transform it into a reusable format. CloudCover developed a unified solution to remove the complexity of cloud and data ecosystems, allowing organizations to focus on delivering value from their data. Learn how CloudCover Data Pipes leverages AWS services to provide a cloud-native data management platform allowing you to gain insights from your trusted data.

Change Healthcare collaborated with the innovation teams at AWS to develop Drug Analyzer, a commercial launch application powered by AWS. The application is built on Change Healthcare’s Data Science as a Service (DSaaS) platform, a security-enabled analytic cloud service that enables persistent compliance monitoring and highly customizable analytics capabilities. Drug Analyzer provides life sciences organizations with data insights that inform treatment decisions and support the development of new therapies.

Amazon QuickSight is an easy-to-use, cloud-powered analytics business intelligence tool that provides insights and analytics capabilities. Experts from AWS and Quantiphi, an AWS Premier Tier Services Partner, discuss an approach to assist users in leveraging Amazon QuickSight as an enterprise-wide BI tool. The entire process, creation of data sources, datasets, analysis, and eventually dashboards, can be automated using AWS CodePipeline.

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.

Organizations realize the value of data and analytics for their businesses, but not all of them have been successful in defining a mature analytics vision and strategy. By cross-leveraging experience in process management, safeguarding data, and rich analytics practices, Genpact has developed an analytics maturity assessment framework known as the Analytics Maturity Meter (AMM). Learn how this solution evaluates a company’s current capabilities in data, process, technology, talent, and enterprise leadership.

To curb spend and unlock scale, Precisely collaborates with AWS to provide the means to synchronize mainframe data in the cloud at speed and power modern applications. Learn how Precisely Connect integrates data seamlessly from legacy systems into next-generation cloud and data platforms. Using Precisely Connect, data from sequential files, VSAM datasets, or databases such as IMS and Db2 can be transferred to Amazon RDS.

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.