Generative Data Intelligence

Tag: Amazon SageMaker Canvas

Enable intelligent decision-making with Amazon SageMaker Canvas and Amazon QuickSight

Every company, regardless of its size, wants to deliver the best products and services to its customers. To achieve this, companies want to understand...

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...

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...

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...

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...

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...

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...

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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