Read the first article in this series on Sales Use Cases, which can improve productivity of sales teams and help achieve targets faster 🎯. Read this article to understand how to tackle below models: Note: A ready-reference of this blog is available as a pdf in our revamped Help article section. Here is the direct […]
This will be a series of posts detailing Predictive Use Cases that can be built with Data cloud’s Model Builder. The first article in this series is aimed at Sales Use Cases, which can improve productivity of sales teams and help achieve their targets faster 🎯. Bonus: A ready-reference of this blog is available as
This guide will walk you through the process of building a predictive model for a forecasting use case using the Model builder in Data Cloud. If you’re new to building predictive models and exploring the No-code model builder, make sure to check out the excellent Salesforce Blog Build an AI Model With Clicks In Data
With this feature, Einstein Studio now gives you full visibility into how the deployed models are used and helps assess Data quality issues on incoming data to ensure accuracy and reliability of the models live in production. 🔥 Explore what’s new: In this article, get a deep-dive on these brand new feature: Model Monitoring post
This article rounds up the latest enhancements in Einstein Studio’s Model Builder, designed to simplify key stages of the machine learning lifecycle, from training data preparation and feature engineering, to model retraining and agentic flow integration. Note: Read the previous blog on Using Model Predictions in Data Cloud One (DC1) Orgs 🔥 Explore what’s new:
This blog talks about how predictive models built in the Home org of a DC1 setup using the No-code Model builder is surfaced across all of its companion orgs basis data access Basics of Data Cloud One Salesforce Data Cloud One is a Data Cloud feature which facilitates businesses to seamlessly manage multi-org environments. In
The all new Einstein Studio tab in Data Cloud is now GA and will allow users with access to Data Cloud to build, connect, and manage their predictive and generative models. Models which can be seamlessly integrated into any Salesforce Customer 360 application for intelligent decision making. Previously Einstein Studio allowed users to connect to
Einstein Discovery drives business value for companies by eliminating friction in using machine learning, and maximizing its time-to-value. It is designed to facilitate every step of the journey towards operationalizing Machine Learning in the workspace, in a safe, ethical and most of all practical and easy way. This applies training the model and interpreting the Story, but it
これは、Data Cloudのモデルビルダーを使用して構築できる予測AIのユース ケースを詳しく説明する一連の記事です。このシリーズの最初の記事は、営業チームの生産性を向上させ、目標をより早く達成するのに役立つ営業ユース ケースを対象としています