Tag: Amazon Kinesis Data Firehose

Fragmented supply-chain management systems can impair an enterprise’s ability to make informed, timely decisions. Accenture’s Intelligent Revenue and Supply Chain (IRAS) platform integrates insights generated by machine learning models into an enterprise’s technical and business ecosystems. This post explains how Accenture’s IRAS solution is architected, how it can coexist with other ML forecasting models or statistical packages, and how you can consume its insights in an integrated way.

Explore several common AWS services and architectural patterns used by SaaS vendors to interact with their customers’ cloud accounts. Examples of SaaS products requiring some level of account interaction often fall into the categories of logging and monitoring, security, compliance, data analytics, DevOps, workflow management, and resource optimization. SaaS products, such as the ones in these categories, regularly interact with resources in the subscribing customer’s AWS account.

In spite of the rich set of machine learning tools AWS provides, coordinating and monitoring workflows across an ML pipeline remains a complex task. Control-M by BMC Software that simplifies complex application, data, and file transfer workflows, whether on-premises, on the AWS Cloud, or across a hybrid cloud model. Walk through the architecture of a predictive maintenance system we developed to simplify the complex orchestration steps in a machine learning pipeline used to reduce downtime and costs for a trucking company.

Splunk software collects, analyzes, and visualizes real-time and historical machine data from any source, enabling you to improve operations, ensure safety and compliance, perform predictive maintenance, and better manage the uptime and availability of industrial assets. Learn how to collect data from Internet of Things (IoT) devices using AWS IoT services and ingest that data into Splunk for meaningful and action-oriented analytics using Amazon Kinesis Data Firehose.