Salesforce to Data Warehouse: A Comprehensive Guide

By: Published: June 16, 2020

Salesforce to Data Warehouse - Blog Image


Looking to move your data easily from Salesforce to your data warehouse? We have you covered. This guide will take you through the steps involved in Salesforce integration to data warehouse. The blog will also highlight any challenges that you may face along the way. This article aims to equip you with the knowledge you require to choose and implement the method that is right for you.

Let’s see what you will cover here:

Introduction to Salesforce

Salesforce is a cloud-based CRM tool that helps you maintain and manage your organization’s interactions with its customer base. Salesforce generates a lot of data from managing these interactions. Salesforce also has many other cloud-based tools including Data Analytics and Internet of Things products, which similarly generate data that can be useful to your organization. For the purposes of this blog, we will focus primarily on Salesforce’s CRM offering.

You can transfer your Salesforce data to a data warehouse of your choice to combine it with data from other facets of your business or to simply provide an alternative data storage environment. This blog will outline the high-level steps that can help you load your Salesforce data into a data warehouse. Also check out salesforce export data.

Methods to Move Data from Salesforce to Data Warehouse

Method 1: By manually writing ETL scripts

This method involves writing custom ETL scripts manually to access the data, extract the data, transform the data, create a repository in your data warehouse, and finally load the data in the data warehouse. This can be tedious and requires an in-depth technical knowledge of Salesforce’s APIs.

Method 2: By using a fully automated Data Pipeline solution – Hevo data

Hevo is a no-code data pipeline. It is fully automated and maps your Salesforce data to its relevant tables in your data warehouse, giving you access to the data in real-time and for free. This method is hassle-free and easy to implement.

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Salesforce to Data Warehouse: Through Custom ETL Scripts


  1. Salesforce Account
  2. Knowledge of APIs
  3. An operational data warehouse of your choice

Steps to Write Custom ETL Scripts:

Following are the steps involved in writing an ETL script to move data from Salesforce:

  1. Extract Data from Salesforce
  2. Transform and Prepare your Data
  3. Stage your Data
  4. Load your Data

1. Extract data from Salesforce

Salesforce has a rich API with many options including SOAP, REST, and Streaming among others. Each option is well suited for a specific use case. For example, the streaming API is geared towards ensuring that your data is always current. Further information on the Salesforce API options can be found here
You can use the SOAP API by creating a SOAP client and then setting up a web services connector. Alternatively, you might want to interact directly with the REST API or through a client like CURL to access the data. The Salesforce resources will be returned in JSON or XML format. You can also check Salesforce to S3 integration.

2. Transform and Prepare your Data

It is important that you make sure that your data types correspond to those in your chosen data warehouse. The specifics of this step depend largely on the choice of the data warehouse. It may also be helpful to comb through the data to ensure that you carry out any necessary data transformations. The following are links to data type information for some popular data warehouse and database solutions:

3. Stage your Data

It is helpful to initially store your data in a repository within your data warehouse to facilitate easier data transformation or exploration. Some data warehouses like Snowflake make it easy to do this by explicitly providing data stages that you can use.

4. Load your Data

It is helpful to design a schema for your warehouse to map the data from your source. After you have successfully carried out all the steps, you can load the data into the data warehouse. Some data warehouses might only require COPY INTO SQL statements. While others like Google BigQuery might require you to use their respective command lines. 

Limitations of Manually Writing ETL Scripts

This method of performing Salesforce integration to data warehouse has the following limitations:

  • Real-time Limitations: The manual method has real-time limitations as it captures a batch of data at a point in time. This means you might have to repeat the steps each time you want to perform a data update. 
  • Time-consuming: Manually writing ETL scripts requires a lot of code. This could prove to be particularly problematic in situations that require you to meet tight deadlines.
  • Resource-intensive: Using this method requires a lot of commitment from your engineering team, which might not be feasible for small organizations that may not have expert developers.
  • Difficult to Perform Data Transformations: You have to perform manual data transformations under this method. This is a tedious process. There is also no way to perform fast data transformations like currency conversions, time and date changes, etc.
  • Error Handling: Checking for errors that are not initially obvious could pose problems especially if they are discovered at a later stage in the ETL process.

Salesforce to Data Warehouse: Through Hevo Data

You can load the data into your warehouse with a code-free data platform like Hevo. Hevo is fully managed and so requires little time to set up.

Get Started with Hevo for free

You can replicate your Salesforce data in a data warehouse of your choice using these steps:

  1. Authenticate and connect to Salesforce as a source on the Hevo platform.
Salesforce to Data Warehouse: Configure Salesforce

2. Configure your data warehouse (Snowflake in the image below) as a destination and start moving data.

Salesforce to Data Warehouse: Configure data warehouse

Hevo will then ensure that your data is moved from Salesforce to your data warehouse consistently, reliably, and securely. Additionally, It supports integrations from 100+ sources (including 30+ free data sources like Salesforce, etc.). Hevo can also be used to move data from a wide variety of sources like cloud applications, SDKs, databases, etc. 

Hevo also automatically maps your Salesforce data to its relevant tables in your data warehouse, giving you real-time access to your data.

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Key Features of Hevo

  • Simplicity: Using Hevo is easy and intuitive, ensuring that your data is transferred in a few clicks. 
  • Minimal Setup: Hevo is a fully managed and automated platform. Thus, it requires minimal effort on your part to set it up
  • Scalability: Hevo is able to perfectly handle data from a wide variety of sources including analytics applications, databases, and more at any scale. Thus, Hevo is able to help you scale to meet your growing data demands.
  • Real-time: Hevo provides a real-time streaming architecture that enables you to gain real-time insights by enabling you to move your data instantly.
  • Reliable Data Load: Hevo provides a fault-tolerant architecture that ensures that your data loads are done reliably, consistently, and with minimal data loss. 

Using an ETL tool like Hevo for your data transfer can be particularly advantageous to your organization as it provides a dependable and hassle-free alternative to manually performing your ETL.

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Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand.

Want to share your thoughts on moving data from Salesforce to a data warehouse? Leave a comment below.

Rashid Y
Freelance Technical Content Writer, Hevo Data

Rashid is passionate about freelance writing within the data industry, and delivers informative and engaging content on data science by incorporating his problem-solving skills.

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