Category: Analytics

With Amazon Redshift Serverless, users can run and scale analytics workloads seamlessly, paying only for the compute and storage resources they consume. Businesses often have a need to use change data capture (CDC) to quickly and easily load incremental data to data warehouses. Learn how to load data easily into Amazon Redshift Serverless using Matillion Data Loader, and see an example of CDC loading from PostgreSQL to Amazon Redshift Serverless as the destination.

Over the years, Ganit has successfully deployed business intelligence systems on AWS with a data lake and data warehouse at the core. This system has helped many of Ganit’s clients reduce more than 25 million hours in the creation of reports and spend more time driving action to improve top- and bottom-line numbers. Learn how one of Ganit’s clients in the financial control division of an Indian subsidiary of a large apparel manufacturer was tasked to optimize expenses across divisions and ensure functions operate efficiently.

Tenable One Exposure Management Platform gives organizations a comprehensive view of their attack surface and vulnerabilities to prevent likely attacks and accurately communicate cyber risk. Learn how the Tenable data engineering team uses AWS to ingest data from multiple sources and transform it into a single standard structure. By standardizing into a single data structure, Tenable can focus on giving customers the business insights and actionable intelligence they need from an exposure management platform.

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.