This module provides an in-depth look at the foundational concepts of Data Cloud, including data architecture, deployment models, and data management tools. Learners will gain practical insights into how Data 360 works, how to set up a Data Cloud environment, and how to manage access and data spaces effectively. The module also addresses real-world challenges and expectations when implementing data solutions.

This module provides a comprehensive overview of data modeling concepts, including entity relationships, data types, and normalization strategies. Learners will gain insights into best practices for designing effective data models in the Data Cloud environment. The content also explores key decisions such as standard versus custom DMOs and the role of primary and foreign keys in data relationships.

This module explores the critical aspects of data ethics, privacy, and governance in the context of data cloud environments. Learners will gain an understanding of how to identify and evaluate data sources, as well as how to implement effective data management practices.

This module provides an in-depth understanding of data objects, categories, and primary key configurations in Data Cloud. Learners will gain foundational knowledge on how data is structured, categorized, and optimized for efficient use. The content prepares learners to implement best practices in data modeling and management.

This module provides a comprehensive overview of data ingestion processes in Data Cloud, covering methods, tools, and practical applications. Learners will explore how to prepare environments, transform data, and use data kits for efficient configuration. The module includes hands-on activities to reinforce real-world implementation skills.

This module provides a comprehensive introduction to data mapping and harmonization, covering techniques for aligning data sources, using a checklist for effective mapping, and navigating the Data Cloud UI. Learners will gain practical skills in mapping CRM data and streaming data from S3 sources.

This module provides an in-depth look at identity resolution, covering key concepts, terminology, and practical implementation techniques. Learners will explore how to unify customer profiles, configure identity resolution systems, and evaluate their results for accuracy and insights.

This module provides an introduction to generating insights using Data 360, covering the types of insights available, the process of creating them, and practical SQL functions for analytics. Learners will gain hands-on experience in building insights through interactive exercises.

This module covers the fundamentals of customer segmentation, including the process, tools, and practical implementation. Learners will gain insights into how to effectively target and analyze customer groups using segmentation techniques and tools. It also includes hands-on practice to apply segmentation configurations.

This module explores the process of activating customer segments and leveraging data actions to enhance customer profiles. Learners will gain practical knowledge on using Data Cloud environments and understanding data relationships through data graphs. It emphasizes real-world applications of data enrichment and segment activation.

This module explores the fundamentals of Retrieval-Augmented Generation (RAG), including its setup in Data Cloud, the role of search indexes, and how retrievers and ADL support efficient data retrieval and processing. Learners will also gain insight into knowledge articles and their importance in AI and search systems.

This module provides an in-depth look at Document AI, covering its role in processing and extracting structured data from documents. Learners will explore real-world use cases and gain hands-on experience with setting up and integrating Document AI for tasks like KYC document processing. The module emphasizes both theoretical understanding and practical implementation.

This module guides learners through reflecting on their educational journey and applying key concepts from the Data Cloud Consultant course. It emphasizes the importance of gratitude and self-assessment in professional development.