Teach on Udemy

Turn what you know into an opportunity and reach millions around the world.

Learn More

Your cart is empty.

Keep shopping

Salesforce Data 360 (Data Cloud): Build End-to-End Solutions

Name: Salesforce Data 360 (Data Cloud): Build End-to-End Solutions
Rating: 3.9 (8 reviews)

Identity Resolution · Einstein AI · Agentforce-Ready Unified Profiles · S3 & GCS Ingestion · Segmentation & Activation

Created byCosmin Aron

Last updated 8/2026

English

English [Auto],

What you'll learn

Configure a Production-like Data Cloud Playground
Ingest, Model, and Unify Customer Data
Derive Insights and Predictions from Unified Data
Activate Audiences and Enrich Salesforce with Data Cloud

Course content

9 sections • 35 lectures • 5h 13m total length

Course Introduction & The NexaDrive Motors Story7:13
Learners will familiarise themselves with the structure and the content of this course.
What is Salesforce Data Cloud4:02
Leaners will be able to explain in simple terms what Salesforce Data Cloud is.
Data Cloud Architecture & Where Our Data Fits3:22
Leaners will be able to understand the medallion architecture of Salesforce Data Cloud.

Create Your Free Data Cloud + Agentforce Account1:43
Learners will learn how to create and access their Salesforce Data Cloud Developer Edition org for use in the course.
Download of the CSV datasets0:05
Learners will be able to download the CSV datasets that will be used throughout the course.
Data Cloud Provisioning & Instance Preparation21:08
Learners will learn how to provision Data Cloud, remove sample CRM data, enable person accounts, add key contact fields, and import contact records to prepare their org for Data Cloud.
Create Your Free Google Cloud Account10:26
Learners will learn how to create a free Google Cloud Storage account and upload the Finance data.
Create Your Free AWS Account13:47
Learners will learn how to create a free AWS account and upload the DMS data.
Setting Up Your Playground Quiz

Connecting to Salesforce CRM - CRM Bundles13:32
Learners will learn how to install the Sales Cloud data bundle, ingest Salesforce CRM sales objects into Data Cloud, and explore some of the DMO mappings.
Ingesting Finance Data from Google Cloud Storage8:14
Learners will learn how to create the Google Cloud Storage data streams for finance data, set keys and formula fields, and deploy them in Data Cloud.
Ingesting Car Data from AWS S39:26
Learners will learn how to create the AWS S3 data streams for DMS data, set keys and formula fields, and deploy them in Data Cloud.
Ingesting Data Quiz

Data Explorer & Query Editor10:49
Learners will learn how to explore the data using Data Explorer and Query Editor.
Batch Data Transformation - Test Drive Status Bucketing17:10
Learners will learn how to build, run, and verify a batch data transform that normalises test drive statuses into a new Data Lake Object in Data Cloud.
Salesforce CRM Contacts Mappings14:18
Learners will learn how to map the Salesforce Contact Data Stream to the Data Model Objects in Data Cloud.
Finance Contacts Mappings14:37
Learners will learn how to map the Finance Contact Data Stream to the Data Model Objects in Data Cloud.
DMS Contacts Mappings4:45
Learners will learn how to map the DMS Contact Data Stream to the Data Model Objects in Data Cloud.
Creating Custom DMOs7:16
Create and map custom DMOs for remaining data lake objects, including test drive data, DMS service records, car ownership, car catalog, finance agreements, and payments history.
Building Relationships Between DMOs11:58
Amendment: Contact Point Consent0:32
Data Modelling and Harmonization Quiz

Identity Resolution Rulesets & Reconciliation Rules11:47
Learners will learn how to configure and run identity resolution and reconciliation rules in Data Cloud.
Data Exploration - Unified Individual13:17
Learners will learn how to explore unified Data Cloud objects and run queries to see how source profiles roll up into unified customer profiles.
Identity Resolution, Reconciliation Rules & Merge Scenarios Quiz

Batch Transformation: Training Data Creation11:35
Create training data with batch data transforms by joining unapproved finance agreements and finance profile DMOs, filtering out outright purchases, to train a predictive default model in Data Cloud.
Create Einstein AI model4:37
Train an Einstein AI model in Einstein Studio using Bash data transforms with all records, autopilot selecting variables, and extreme gradient boosting predicting defaults to minimize them.
Analyse Model Training Quality4:43
Assess model training quality with AUC 0.729 and threshold 0.45, predictors credit score, debt-to-income ratio, and APR; review ROC, confusion matrix, and gain charts to activate and score applications.
Finance Applications Data Ingestion3:48
Ingest finance agreements data from Google Cloud Storage into Data Cloud, map to a custom DMO, and use the Einstein model to predict default likelihood.
Predict finance default risk7:18
Learn to build end-to-end finance default risk predictions in Einstein Studio by creating and activating a predict job, mapping model inputs, and exploring results with a query editor.
AI - Einstein Studio Quiz

Segmentation - In The Market Segment8:29
Segmentation using a Calculated Insight4:59
Build a complete customer segmentation using a calculated insight in a visual builder, creating and publishing a delinquency risk segment based on the unified individual.
Creating an Activation Target3:30
Create and configure an activation target to route a market segment to destinations such as Marketing Cloud, CRM, or ad platforms, including bucket setup and CSV or JSON export settings.
Send a segment to the Activation Target7:24
Data Graphs7:41
Create data graphs by combining multiple data model objects into a unified view, set filters and refresh intervals, and explore real-time queries with the data explorer.
Segmentation & Activation Quiz

Adding Data Cloud Components to Contact Layout (Insights, Related Lists)8:05
Learn how to add three Data Cloud components—profile engagements, profile insights, and profile-related records—to a contact page, unifying profile data and displaying key insights in Salesforce.
Copy Fields for Cross-Cloud Use10:35
Use Data Cloud copy field enrichment to copy the unified individual ID from the unified profile to the contact, after enabling the data space and permissions, then run the sync.
Create Data Cloud Related Lists7:14
Salesforce Enrichments Quiz

Requirements

No prior Salesforce Data Cloud experience required, everything is explained step-by-step.

Description

This course contains the use of artificial intelligence.

Salesforce just renamed Data Cloud to Data 360. The architecture hasn't changed — but the stakes have. This is the only hands-on course that takes you from raw data ingestion to a unified profile that powers Agentforce AI agents.

What you'll build:

You'll construct a complete Data 360 solution from a clean Developer Edition org using real cloud storage - Amazon S3 and Google Cloud Storage - as your ingestion sources. You'll model data to standard and custom Data Model Objects (DMOs), harmonise inconsistent values across systems, and configure an Identity Resolution ruleset with match and reconciliation rules to produce a single Unified Profile per customer.

From there, you'll build a calculated insight for delinquency risk and train an Einstein AI model to predict which finance agreements are likely to default - then evaluate, activate, and surface those predictions directly inside Salesforce CRM using enrichment components, copy-field enrichments, and related lists.

Finally, you'll design powerful segments and activate them to external destinations — giving your organisation a complete, Agentforce-ready data activation layer.

Who this is built for:

Salesforce Architects and Consultants preparing for the Data 360 / Agentforce 360 transition

Data Engineers building real multi-source ingestion pipelines (S3, GCS)

Admins and RevOps professionals who want to build segments and activations, not just read about them

Anyone who has watched a Data Cloud demo and thought, "but how do I actually build this?

No coding required. No prior Data 360 or Data Cloud experience needed. Just bring a laptop and the willingness to build something real.

Who this course is for:

This course is for you if you work with customer data and want to turn Salesforce Data Cloud into something practical, not just theory.
Salesforce Admins who want to understand how Data Cloud fits into your existing org
Data & Analytics Practitioners Working in the Salesforce Ecosystem
Product Owners & Stakeholders Evaluating Data Cloud
Best suited for beginner-to-expert Data Cloud learners.

Salesforce Data 360 (Data Cloud): Build End-to-End Solutions

What you'll learn

Explore related topics

Course content

Welcome & Foundations3 lectures • 15min

Setting Up Your Playground5 lectures • 47min

Ingesting Data3 lectures • 31min

Data Modelling and Harmonization8 lectures • 1hr 21min

Identity Resolution, Reconciliation Rules & Merge Scenarios2 lectures • 25min

Calculated Insights1 lecture • 24min

AI - Einstein Studio5 lectures • 32min

Segmentation & Activation5 lectures • 32min

Salesforce Enrichments3 lectures • 26min

Requirements

Description

Who this course is for: