Tag: Amazon Kinesis Data Stream

By combining Amazon DynamoDB with SingleStore, organizations can efficiently capture, process, and analyze DynamoDB data at scale. SingleStore has high-throughput data ingestion and near-real time analytical query capability for both relational and JSON data. This integration empowers businesses to derive actionable insights from their data in near real time, enabling faster decision-making and improved operational efficiency.

In the financial services industry, detecting fraud is a complex process. For any given transaction or activity, the system needs to decide whether it’s fraudulent or not and take action within seconds. With Redis Enterprise Cloud‘s sub-millisecond latency speeds, up to five 9’s of availability, linear scalability, and multiple data model support coupled with the global cloud infrastructure support of AWS, organizations can benefit from building a real-time fraud detection system to manage and control fraud.

Gogo is a global provider of broadband connectivity products and services for business aviation. It needed a qualified engineering team to undertake a complete transition of its solutions to the cloud, build a unified data platform, and streamline the best speed of the inflight internet. Learn how N-iX developed the data platform on AWS that aggregates data from over 20 different sources using Apache Spark on Amazon EMR.

A SaaS data platform may run in the account of an ISV or a dedicated account provided by the customer. Learn about the main AWS services SaaS data platforms can integrate with to provide customers with a seamless experience and take advantage of AWS services in order to accelerate their drive to meeting their business goals. Explore how those integrations can be built and examples of AWS ISV Partners who have successfully developed these integrations.

In the healthcare industry, the exchange of data incurs risks as it contains personally identifiable information (PII) and protected health information (PHI). At the same time, not exchanging the data can keep valuable insights hidden. Apexon’s data anonymization and de-identification solution uses sophisticated machine learning algorithms to ensure the exchange of data happens without any risk of PII/PHI being exposed, while allowing organizations to meet compliance and regulatory requirements.

The increase in market uncertainty over the last couple of years has demonstrated the need for market participants to have a dynamic view of the risks and impacts due to market moves on their portfolios. This post explores how Validus, a leading independent technology-enabled financial services firm, built a Bloomberg real-time market data integration using serverless managed services on AWS.

Customers building on AWS can benefit from specific alignment to either their architecture or an industry vertical via lenses which are included within the AWS Well-Architected Tool and include questions applicable to that particular workload. Learn how findings from the Serverless Application Lens can be automated using Dashbird Insights to show misconfigurations and best practice violations in relation to serverless workloads. This post walks through the deployment of an example serverless application that we’ll profile using Dashbird Insights.

To improve the fault detection process, it’s crucial to monitor production systems and collect performance data in real-time using smart sensors and IoT devices. This post highlights the critical aspects of Quantiphi’s serverless, fully-managed, and streaming ETL pipeline, along with the benefits of the centralized lakehouse (data lake + data warehouse) solution built on AWS. Learn how the solution helped a U.S.-based manufacturing company make better decisions and improve their customer’s production efficiency.

Serverless technologies have matured a lot over the years, and it’s easier than ever to deploy the entire stack of applications using serverless and AWS managed services. Infosys is seeing enterprises across industries take advantage of the power of serverless architecture for a variety of use cases. Learn how serverless architecture on AWS can help enterprises modernize their application landscape, along with common use cases and some reference architectures.

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.