Difference Between Salesforce Architecture and Salesforce Data Cloud Architecture – Salesforce Data Cloud Architecture
Difference Between Salesforce Architecture and Salesforce Data Cloud Architecture – Salesforce Data Cloud Architecture

Difference Between Salesforce Architecture and Salesforce Data Cloud Architecture – Salesforce Data Cloud Architecture

Salesforce Architecture and Salesforce Data Cloud architecture are related to the Salesforce platform, but they have different purposes and components.

  • Salesforce Architecture

Salesforce Architecture refers to the underlying infrastructure and components that make up the Salesforce platform. This includes the Salesforce database, servers, APIs, and user interface. It is designed to provide a scalable, secure, and reliable platform for businesses to manage their customer data and operations. It includes features such as Salesforce Lightning, which provides a modern user interface, and Salesforce Einstein, which provides artificial intelligence capabilities for the platform.

Let us look at the high-level Salesforce architecture diagram in Figure 4.5.

Figure 4.5: Salesforce Architecture

In the preceding diagram, at the bottom is the transaction database, which stores transaction data. Transaction data includes data related to Leads, Opportunities, Accounts, and other objects used in daily operations. It is a traditional relational database that every Salesforce org shares with all the tenants of the instance. Both standard and custom objects are physically stored here, making the data easily accessible for all queries, triggers, flows, and process automation.

The unified metadata dictionary describes the data structures to enforce integrity when saving records. The security and access control layer ensures that data is only visible to relevant users in a specific org.

The Einstein layer is the artificial intelligence layer of Salesforce that provides machine learning and AI capabilities to Salesforce. The AI can train on the data residing in Salesforce and provide analysis or predictions to users. The end users interact with the top three layers, which contain the lighting design system, applications, and other features. These layers enable users to interact with the Salesforce system. Salesforce is extensible and customizable, which is denoted by the left-hand side block. You can connect various applications from the AppExchange or build your own on top of the Salesforce platform, leveraging its architecture.

  • Salesforce Data Cloud Architecture

Salesforce Data Cloud Architecture, on the other hand, is specifically focused on managing data from various sources to drive better business decisions. It includes several components such as data sources, data storage, data management, data APIs, data analytics and insights, and data security and privacy. These components work together to provide businesses with access to a wide range of data sets, including third-party data, customer data, and social media data.

The Salesforce Data Cloud Architecture enables businesses to collect and ingest data from various sources, clean, transform, and enrich the data, store it in a centralized data warehouse, expose the data to other applications and services, and provide insights into the data through data analytics and reporting tools. The platform also includes security and privacy features to protect the data from unauthorized access and ensure compliance with data privacy regulations.

Now, let us examine the high-level Salesforce Data Cloud architecture diagram (see Figure 4.6).

Figure 4.6: Salesforce Data Cloud Architecture diagram

As you can see, there is an addition of a Lakehouse to the Salesforce architecture. Data Cloud essentially brings this Lakehouse to the Salesforce platform and the data that resides in it.

The rest of the architecture remains the same. The difference is that the Lakehouse data is incorporated in the transaction data, unified metadata dictionary, and security and access control layers. The Einstein layer also gets a boost from the data in the Lakehouse. It gets more data to train on and can be used to solve more AI use cases. The applications on the top layer can operate on Lakehouse data. You can also build customizations with it.

While both architectures are related to the Salesforce platform and similar, they serve different purposes. Salesforce Architecture is focused on providing a platform for managing customer data and operations, while Salesforce Data Cloud Architecture is focused on managing data from various sources to drive better business decisions.

Leave a Reply

Your email address will not be published. Required fields are marked *