Salesforce is a robust Cloud computing service that has expertise in Customer Relationship Management (CRM). It allows brands and businesses to connect better with their customers and partners. This article deals with understanding the Salesforce Database structure and working that reflects the true potential of Salesforce.
Introduction to Salesforce Database
The structure and working of the Salesforce Database help to unravel how Salesforce is able to cater to over 150,000 customers and manage all their requirements. The Database lies at the center of all the functionality. It structures data, organizes, and manages it using a tabular approach.
It is also a hub to store large amounts of data that is collected from multiple users. This enables Salesforce to load more than the available system RAM. Multiple users and admins can access this data for fast and easy retrieval at any time.
The Salesforce Database is powered by Oracle. This employs a variety of features that makes it self-secure and improve the repairing functionality. There are a number of languages that are used for the Salesforce Database including SQL.
Evolution of Salesforce Database
Since the launch of Salesforce in 1999, its Database utilities have evolved to exist in the form that it does today. Salesforce was initially conceived to create business software applications in a new way. This is where the software would be delivered through a SaaS (Software-as-a-Service) model.
Understanding Need for Salesforce Database
The first idea to explore is the need for a Database for Salesforce in the first place. Being involved in Customer Relationship Management for businesses, it only makes sense that Salesforce is required to deal with a lot of data including that of both the direct customers and their customers’ client base.
Thus, it establishes an inherent need for a robust Database system. The Salesforce Database is structured with some key principles in mind: easy access, sync, and migration of data in a secure environment.
Understanding Architecture of Salesforce Database
The Salesforce Architecture is designed to deliver an interface that is flexible and customizable for use by customers, employees, and partners. It comprises a series of layers interconnected with each other which can be seen in the representation below.
How does Salesforce Architecture look like?
The different layers are interlinked to function as a Database that is robust and multitenant.
- Being a Cloud-based company; all the components are contained in a multitenant cloud.
- Metadata powers different aspects such as APIs, data services, and AI services. This composes the foundation layer of the services.
- The multi-tenancy in the architecture ensures that irrespective of the size of the business, the access to the computing power, data storage, and core features remains the same.
- The metadata comprises all standard custom configurations, functions, and codes. This aspect of the architecture enables the user to navigate faster through the platform.
- The APIs enable different software in the architecture to be connected with each other for the rapid exchange of information. These are used to retrieve the metadata that is being searched for.
Beyond the functional features, the physical organization of the Salesforce Database comprises various components. Salesforce employs dedicated terminology for the three basic elements that compose the database. These are – Objects, Fields, and Records.
1) Objects in Salesforce Database
In any relational Database, the data is stored in the form of tables. Each table consists of a number of columns with a certain type of data. These tables can also be related to each other using unique identifiers.
An Object is a table with a set of fields and data records within it. Objects are interrelated with each other through different types of relationships.
Types of Objects
Several types of objects are supported on the Salesforce platform. These primarily include:
- Standard Objects: These are objects that are pre-created by the Salesforce platform for your use. This includes common details like Contact, Account, Leads, etc.
- Custom Objects: Custom Objects are those you can create as per your requirements on the basis of particular business processes or functionalities needed.
- External Objects: There are a number of external objects that can be created to map the data stored outside your organization. The combination of these types allows businesses to maneuver between different kinds of data and make the platform flexible for their use.
2) Fields in Salesforce Database
A field in Salesforce refers to a custom database column. The object fields store the data for the records. Each field represents a certain type of data.
There are mainly two types of field references in Salesforce Databases:
- Standard Fields: There are certain fields that remain standard on all objects on Salesforce. These are pre-build are provided on the platform. They include:
- Identity: It is a 15-character, case-sensitive field that gets automatically generated for every record.
- System: The system field is a Read-only field that provides information about a record from the system.
- Name: Every record has a name to be able to create a distinguishing feature. These can be text names or auto-numbered names.
- Custom Fields: Other than the standard fields, there are custom fields that you can create on standard as well as custom objects on Salesforce.
3) Records in Salesforce Database
The Salesforce Database creates records for leads, tasks, opportunities, accounts, and notes. This is where the actual data is stored.
There are a variety of record types that allow linking different business processes to users, customers, and admins based on their user profiles. The records are used to distinguish between certain specific types of data that are being stored and dealt with.
Understanding Keys in Salesforce Database
The Salesforce Database employs keys to act as unique identifiers. There are two main types of keys that are used: Primary and Foreign Keys.
1) Primary Key
A Primary key may refer to a column or a set of columns that uniquely identifies an object record. There are instances where multiple columns can be used to define a primary key. Here, data from every column is used to determine whether a record is unique.
2) Foreign Key
A Foreign key is a column or set of columns from an object that refers to the primary key of another object. The Foreign key might not always point to a primary key, but it always uniquely identifies a row or record in a table.
Defining Relationships in Salesforce
Certain defining relationships are used to connect Salesforce objects with each other. There are mainly three relationships defined in Salesforce objects. These are based on aspects regarding data sharing, deleting, and accessing. The following types of relationships are observed in the Salesforce Database:
- Many to Many
- Many to One
- Master-Detail
- Look Up
- Self
- Hierarchical
Syncing Data from Salesforce
Another important aspect is the Syncing or Migration of data from Salesforce. This consists of the process of transferring data from one system to another. The synchronization process can differ greatly depending on the format, size, and accuracy of source data involved.
Methods to Migrate Data from Salesforce to any Data Warehouse
You can migrate your data from Salesforce Database to any Data Warehouse such as Redshift, BigQuery, and so on using one of the following methods:
Method 1: Migrate Data from Salesforce Using Manual Data Extraction
In order to synchronize data manually in Salesforce, the first step involves identifying the data that is to be migrated. This involves selecting which data to migrate along with its extraction location.
Once the data has been organized, the next step involves ensuring that all records hold a unique identifier. There might also be the need for a data cleansing process if the IDs are not organized. This is to ensure that all the duplicated and outdated content is discarded during the migration process.
After the preparation of the data, the second phase will cater to the actual transfer of data which will depend on the types of resources available.
This involves ensuring that all the data is being transferred correctly. After the transfer, the correct format and relationships between the different data objects are also to be checked for accuracy.
Thus, the manual Salesforce data migration process can be pretty complex, and each migration corresponds to a unique process. Also, you’ll need to do this over and over again whenever you need to transfer or migrate the data.
Method 2: Migrate Data from Salesforce Using Hevo
Hevo, a No-code Data Pipeline can help you transfer data seamlessly. With Hevo, you can move data from Salesforce to a data warehouse within minutes without any coding.
An interactive visual interface is used here to produce some valuable insights from the data. It is fully managed as an interface, thus leaving no concerns about the maintenance and monitoring of the process.
This saves hours of effort that otherwise has to be spent on identifying, selecting, and moving data to the desired destination. The role of Hevo can be understood by understanding more about its specific features.
Role of Hevo in Data Migration
How does it function?
The functionality of Hevo Data is simple and easy to implement. It allows companies and organizations to access reliable and updated data with ease. Real-time insights can be accessed and employed to grow the client base as well as implement business strategies.
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Conclusion
In this article, you gained a detailed understanding of the Salesforce Database. You learned about the architecture of the Salesforce Database, its keys, 3 significant elements, and relationships. In addition, you understood 2 key methods to Migrate Data from Salesforce to any Data Warehouse – using manual method and other using Hevo.
With an array of interesting features, Hevo provides a time-efficient, reliable, and secure channel to relay data to any desired location. It is a one-stop destination to integrate data without any technical knowledge while also providing real-time access. You can use Hevo to channel your data into any warehouse, all within a matter of minutes!
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Dimple is an experienced Customer Experience Engineer with four years of industry proficiency, including the last two years at Hevo, where she has significantly refined customer experiences within the innovative data integration platform. She is skilled in computer science, databases, Java, and management. Dimple holds a B.Tech in Computer Science and excels in delivering exceptional consulting services. Her contributions have greatly enhanced customer satisfaction and operational efficiency.