AWS Machine Learning Blog

Category: Amazon SageMaker Canvas

Predict shipment ETA with no-code machine learning using Amazon SageMaker Canvas

Logistics and transportation companies track ETA (estimated time of arrival), which is a key metric for their business. Their downstream supply chain activities are planned based on this metric. However, delays often occur, and the ETA might differ from the product’s or shipment’s actual time of arrival (ATA), for instance due to shipping distance or […]

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Predict types of machine failures with no-code machine learning using Amazon SageMaker Canvas

Predicting common machine failure types is critical in manufacturing industries. Given a set of characteristics of a product that is tied to a given type of failure, you can develop a model that can predict the failure type when you feed those attributes to a machine learning (ML) model. ML can help with insights, but […]

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Extract insights from SAP ERP with no-code ML solutions with Amazon AppFlow and Amazon SageMaker Canvas

Customers in industries like consumer packaged goods, manufacturing, and retail are always looking for ways to empower their operational processes by enriching them with insights and analytics generated from data. Tasks like sales forecasting directly affect operations such as raw material planning, procurement, manufacturing, distribution, and inbound/outbound logistics, and it can have many levels of […]

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Use a pre-signed URL to provide your business analysts with secure access to Amazon SageMaker Canvas

Agility and security have historically been two aspects of IT of paramount importance for any company. With the simplification of access to advanced IT technologies thanks to low-code and no-code (LCNC) tools, an even bigger number of people must be enabled to access resources, without impacting security. For many companies, the solution has been to […]

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Enable business analysts to access Amazon SageMaker Canvas without using the AWS Management Console with AWS SSO

IT has evolved in recent years: thanks to low-code and no-code (LCNC) technologies, an increasing number of people with varying backgrounds require access to tools and platforms that were previously a prerogative to more tech-savvy individuals in the company, such as engineers or developers. Out of those LCNC technologies, we have recently announced Amazon SageMaker […]

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Reinventing retail with no-code machine learning: Sales forecasting using Amazon SageMaker Canvas

Retail businesses are data-driven—they analyze data to get insights about consumer behavior, understand shopping trends, make product recommendations, optimize websites, plan for inventory, and forecast sales. A common approach for sales forecasting is to use historical sales data to predict future demand. Forecasting future demand is critical for planning and impacts inventory, logistics, and even […]

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Predict customer churn with no-code machine learning using Amazon SageMaker Canvas

Understanding customer behavior is top of mind for every business today. Gaining insights into why and how customers buy can help grow revenue. But losing customers (also called customer churn) is always a risk, and insights into why customers leave can be just as important for maintaining revenues and profits. Machine learning (ML) can help […]

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Build, Share, Deploy: how business analysts and data scientists achieve faster time-to-market using no-code ML and Amazon SageMaker Canvas

Machine learning (ML) helps organizations increase revenue, drive business growth, and reduce cost by optimizing core business functions across multiple verticals, such as demand forecasting, credit scoring, pricing, predicting customer churn, identifying next best offers, predicting late shipments, and improving manufacturing quality. Traditional ML development cycles take months and require scarce data science and ML […]

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