Category: Amazon Forecast
Gauging market demand for the apparel retail industry is challenging. The success of SKUs sold depends on customer preference (fitting, feel, regional acceptance) and latest trends, which can change frequently. Learn how Ganit has successfully deployed inventory management systems using intelligent demand forecasting at the core of its solutions. This system has helped many clients optimize their inventory, leading to efficient working capital deployment and improvement in topline and bottom-line numbers.
Teradata has expanded its collaboration with AWS by adding integration capabilities for Teradata Vantage, the data platform for enterprise analytics and AWS cloud services. Vantage, with its NOS read/write connector to Amazon S3 data, already provides data integration with S3 data and Vantage enterprise data. Now, Teradata introduces an API integration with Amazon SageMaker and Amazon Forecast. This enables business users to drive outcomes with real-time analytics.
Predicting demand for medical products can be a formidable challenge, since many items have no underlying seasonality patterns nor a consistent shelf life. Learn how Ganit worked with a client to achieve reductions in inventory by designing a robust solution with Amazon Forecast. This post details the approach used to define the objectives and discover the data treatments, and cover employing the flexible architecture provided by Forecast to turn the client’s data into a strength.
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.
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.