Tag: Amazon Forecast

As a SaaS provider, it’s essential to have a clear picture of how tenants are exercising your system. Being able to model the functional and operational profile of tenants and tenant tiers is critical to evolving the business and technical strategies of a SaaS organization. Learn about the role metrics play within a SaaS-based application, and dive deep into a solution that provides all of the infrastructure that will support the ingestion, aggregation, and analysis of SaaS metric data.

Many organizations have started applying machine learning and artificial intelligence expertise to scale customer communications and accelerate research during the COVID-19 pandemic. Onica has been actively involved in these efforts, leveraging AWS technologies to help decision makers navigate this pandemic. In this post, dive into the technical details of two COVID-19-related solutions Onica has produced and learn about their results and impact.

One of the biggest challenges in moving to the cloud for organizations that collect and process personally identifiable information (PII) is the fundamental change to the trust model. SecuPi minimizes changes to the trust model and reduces the risk associated with digital transformations. Learn how SecuPi can help you collect and process sensitive or regulated PII and reduce barriers to cloud adoption while satisfying the trust model requirements of even the most conservative and risk-averse companies.

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.

Time series forecasting is a common customer need. Amazon Forecast accelerates this and is based on the same technology used at Amazon.com. This new service massively reduces the effort required to automate data updating and model retraining, and it manages this while retaining the granularity of control that data scientists will appreciate and utilize. This post explores the use of this new service for energy consumption forecasting.