Load Data from Salesforce to Data Warehouse: Step by Step Guide

Looking to move your data easily from Salesforce to 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.

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.

Salesforce to Data Warehouse: Through Custom ETL Scripts

Prerequisites

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:

• https://docs.snowflake.net/manuals/sql-reference/data-types.html
• http://www.postgresqltutorial.com/postgresql-data-types/
• https://dev.mysql.com/doc/refman/8.0/en/data-types.html

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. 

Learn more about Salesforce Connect.

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.

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.

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

Hevo will then ensure that your data is moved from Salesforce to your data warehouse consistently, reliably, and securely. Additionally, It supports integrations from 150+ data 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.

Conclusion

In conclusion, leveraging Hevo’s method for integrating Salesforce with a data warehouse offers a streamlined, efficient approach to data management. By utilizing Hevo’s no-code platform, businesses can seamlessly extract, transform, and load Salesforce data into their data warehouse, ensuring accurate and up-to-date insights. This integration not only simplifies the data pipeline but also enhances data accessibility and reporting capabilities, empowering organizations to make data-driven decisions with ease and confidence.

FAQ on Salesforce to Data Warehouse

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