Название: Hands-On Salesforce Data Cloud: Implementing and Managing a Real-Time Customer Data Platform
Автор: Joyce Kay Avila
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 528
Язык: английский
Формат: epub
Размер: 26.0 MB

Learn how to implement and manage a modern customer data platform (CDP) through the Salesforce Data Cloud platform. This practical book provides a comprehensive overview that shows architects, administrators, developers, data engineers, and marketers how to ingest, store, and manage real-time customer data.

Author Joyce Kay Avila demonstrates how to use Salesforce's native connectors, canonical data model, and Einstein's built-in trust layer to accelerate your time to value. You'll learn how to leverage Salesforce's low-code/no-code functionality to expertly build a Data Cloud foundation that unlocks the power of structured and unstructured data. Use Data Cloud tools to build your own predictive models or leverage third-party machine learning platforms like Amazon SageMaker, Google Vertex AI, and Databricks.

Salesforce’s Data Cloud platform is built from the ground up, with a completely new architecture. First, Salesforce built a data lake house as a way to store large volumes of data and leverage Salesforce’s canonical data model for data harmonization. Then the automated identity resolution process made it possible to unify data from disparate sources to achieve a single source of truth. That was just the beginning. Powerful segmentation and activation functionality were added next. Data action features were enabled so that users could automatically send instructions to both internal and external targets. This year, many new native connectors were added. Recently, near real-time capabilities were made possible with features like data graphs. Index configuration and vector databases were just added so users could leverage Data Cloud to unlock the power of unstructured data.

The addition of functionality like data graphs and vector databases were the final pieces Data Cloud needed to empower all business users with the tools to easily access, use, and act on all their data. Data Cloud is at the very heart of an organization’s first-party data strategy. It’s open and extensible, too. Marketers, salespeople, service engineers, strategists, and analysts can take advantage of Data Cloud’s many value activities in a variety of different ways. One way users can unlock the power of Data Cloud value activities is by using Einstein Copilot as their conversational AI assistant. It’s now possible to do so because of data graphs and vector databases built on top of a solid Data Cloud foundation.

This book will help you:

Develop a plan to execute a CDP project effectively and efficiently
Connect Data Cloud to external data sources and build out a Customer 360 Data Model
Leverage data sharing capabilities with Snowflake, BigQuery, Databricks, and Azure
Use Salesforce Data Cloud capabilities for identity resolution and segmentation
Create calculated, streaming, visualization, and predictive insights
Use Data Graphs to power Salesforce Einstein capabilities
Learn Data Cloud best practices for all phases of the development lifecycle

Who Is This Book For?
This book is essential reading for technology and data professionals who use customer data to make critical business decisions and for anyone who wants to set themselves apart as a Salesforce professional. Whether you’re an experienced Salesforce professional or someone who is just beginning their Salesforce journey, there is plenty of information in this book for you to get started with Salesforce’s new customer data platform features. Those who will get the most from this book will typically find themselves in one of the following roles:

Salesforce solution architects and consultants
Salesforce technical architects
Salesforce administrators
Salesforce Marketing Cloud developers
Enterprise architects and data engineers
Data scientists and business analysts

With this book, Salesforce solution architects and consultants can focus on learning about customer data platforms in general to be prepared to identify when Data Cloud is a good choice for a particular use case. They’ll also want to take a deep dive into how to implement Salesforce Data Cloud and how to make choices from the specific Salesforce AppExchange partners who can help to extend Data Cloud functionality. Solution architects and consultants are tasked with recommending the right products to internal and external customers, and they can use this book as a guide when they need to research alternatives for new or different use cases that arise.

Salesforce technical architects are experts in the functional, platform, and integration architecture of Salesforce and will be most interested to discover the details of Data Cloud’s hyperscale platform architecture. They’ll want to learn how to take advantage of open data access by leveraging Salesforce’s strategic partners like Amazon, Databricks, Google, Microsoft, and Snowflake. Salesforce technical architects are expected to be the Salesforce domain experts. Thus, they’ll likely rely on this Salesforce Data Cloud book as a reference when having those high-level Data Cloud conversations.