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Unlocking business insights by integrating Machine Learning in SAP Data Intelligence Cloud

Published on 6 November 2023
 SAP Data Intelligence Cloud
Anu Treesa Joseph
Anu Treesa Joseph
Consultant - Data and Analytics

Anu Treesa Joseph, Consultant - Data and Analytics, at Applexus, carries expert proficiency in SAP Data management (BODS), SAP Data Intelligence Cloud (DIC), and Smart Data Integration (SDI). Anu has developed extensive experience in Data Mapping and Conversions with migration tools, designing and building the SAP load objects and completing S/4HANA data migration projects. She also has end-to-end implementation experience including System study, Requirement gathering, Design, Development, Documentation, Implementation process, Customer Interaction, Product Demonstration, Helpdesk activities, and User Training.

The ML Scenario Manager in SAP Data Intelligence serves as a centralized platform to efficiently organize, manage, and execute machine learning (ML) scenarios. An ML scenario refers to a comprehensive workspace encompassing various components crucial for ML projects such as datasets, pipelines, Jupyter Notebooks, and monitoring tools. All this enables efficient monitoring of model performance metrics, deployment history review, and thorough analysis - encouraging exploration of the data estate for insightful intelligence in any organization.

This blog focuses on building a fundamental ML project with the aim of forecasting sales within a date range and leveraging the collected sales data, besides equipping users with the skills to navigate the ML Scenario Manager and initiate ML model deployments using graphical pipelines.

To read further please visit Unlocking business insights by integrating Machine Learning in SAP Data Intelligence Cloud | SAP Blogs

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