With the importance of data in various applications, there’s a need for effective solutions to organize, manage, and transfer data between systems with minimal complexity. While numerous ETL tools are available on the market, selecting the right one can be challenging. There are a few Key factors to consider when choosing an ETL tool, which includes:
Business Requirement: What type or amount of data do you need to handle? What is the required processing speed? Â
Scalability: As the business grows, there might be the need to create and run more jobs on the go.
Cost: The pricing structure can differ for individual tools, and open-source tools are more cost-effective. However, for a user with specific needs and security norms to follow, it is best to invest in a tool that fits your budget.
Ease of Use: If the tool has an intuitive workflow and a user-friendly interface. Under this category, tools with pre-built connectors for popular data sources and visual tools for data transformation are better choices.
Integration: How well does the tool integrate with your existing infrastructure, databases, cloud platforms, and analytics tools?
In this blog, we will provide a comprehensive overview of ETL considerations, introduce key tools such as Fivetran, Salesforce, and Snowflake AI Data Cloud, and demonstrate how to set up a pipeline and ingest data between Salesforce and Snowflake using Fivetran.
What is Fivetran?
Fivetran is a data integration platform that helps businesses move data from various sources to various destinations, such as data warehouses, databases, or cloud storage. The platform is designed to be easy to use, as minimal configuration is required to set up pipelines. This makes the tool easy to work with for both technical and non-technical users.Â
As the size of your data increases, Fivetran can handle it and scale it to meet your business needs. Fivetran can automate the process of extracting, transforming, and loading it into the destination. What sets Fivetran apart is that it provides a wide range of prebuilt connectors, easing the process of connecting Source and destination. It can also be used for real-time analytics, DB replications, AI workflows, and cloud migrations.Â
Fivetran enforces strict security policies through data encryption and compliance with industry and government standards, making it an excellent tool for handling sensitive data.
What is Salesforce?
Salesforce is a cloud-based, highly flexible, scalable CRM software for managing customer connections. It can onboard chunks of data from different systems into one. Salesforce offers a wide range of tools and services integrated with artificial intelligence called the Einstein platform. It guides businesses to make better decisions by providing insights and predictions based on the data for aspects like customer relationship management, sales, customer service, marketing, etc, all in one platform, makingÂ
Salesforce highly customizable. By implementing encryption, MFA, and other monitoring tools, Salesforce ensures that data is well-secured. It also follows industry and government regulations like GDPR, HIPAA, and SOC2
What is Snowflake Data Cloud?
Snowflake Data Cloud is known for its cloud-based data warehousing platform, which allows users to utilize a large volume of storage space, processing, and analytics solutions. As a fully managed service, Snowflake eliminates the need for infrastructure maintenance, differentiating itself from traditional data warehouses by being built from the ground up. It can be hosted on major cloud platforms like AWS, Azure, and GCP.Â
Snowflake is highly flexible and scalable without affecting the performance of large data sets. It is designed so that storage and computing resources are separated, giving the User more control over scaling each independently. Snowflake can handle structured and unstructured data in a single platform, and data can be shared across different accounts or organizations without the need to move or copy it.Â
Snowflake has robust security features, like encryption and role-based access control, and follows industry and government standards like GDPR, HIPAA, and SOC 2.
How do you Generate Salesforce Data for Snowflake Using Fivetran?
In this section, we’ll provide insights on how to gain hands-on experience using Fivetran to ingest Salesforce data into Snowflake. Fivetran is the intermediary in this process, facilitating the seamless data transfer from Salesforce to Snowflake. The connection between these tools will be established and managed within Fivetran.Â
When setting up a pipeline in Fivetran, specify the Source: Salesforce. To establish the connection between Salesforce and Fivetran, go to the connectors tab on the left-hand side and click Add Connector.
Once you click Add Connector, you will be directed to a page with Fivetran’s list of pre-built connectors. You can either scroll down the list of sources or quickly search the search bar to find the tool.
Hover over the Salesforce menu to access options for the setup page.
Once you are on the setup page, ensure that before setting up the connection, you log in to Salesforce in the same browser as you log in to Fivetran. This will allow you to use the current authorization token, and if you don’t sign in, you will be prompted to sign in to your Salesforce account.
Once signing into Salesforce is completed, the User will be directed to the setup page in the destination schema, which will be in Snowflake. Remember that the schema’s name cannot be changed once you define it and save it. After defining the schema’s name, click the Authorize button. Once the authorization has been successful, click the Save & Test button, which saves your configuration and tests the connection.
If the connection tests are successful, you should see a message similar to the one in the above screenshot. We have successfully established a connection between Salesforce and Fivetran at this stage. As shown below, we must select the data to ingest from Salesforce into Snowflake.
Fivetran not only lets Users select the tables they want to ingest into Snowflake but also gives them the flexibility to select the columns they want to ingest along with the table.Â
Users also have the option to hash or unhash the selected fields inside them. After selecting the respective tables with the required columns, click the Save and Continue button at the bottom of the page.
Fivetran allows Users to handle changes in their data source schema, such as new columns or tables. This option lets Users choose whether new schema elements should be automatically synced to their destination, require manual selection, or be ignored. This setting ensures that the data pipeline adapts to changes in the Source schema according to user-specific needs.
Fivetran’s pre-built data models are pre-configured transformations that automatically organize and clean the User’s synced data, making it ready for analysis. These models are designed to run instantly after syncing data with the Source. This feature saves time and effort in preparing the data for reporting or analytical purposes. At this point, the pipeline connection for Salesforce and Fivetran is completed.Â
When it comes to the connection settings between Fivetran and Snowflake, there are two ways to establish the connection. The fastest way is Snowflake, which already has a built-in connector. These connectors are readily available in the Snowflake UI within the Snowflake Partner Connect tab. Snowflake’s connector feature allows users to integrate with third-party tools and services. It simplifies the setup process for data integration, business intelligence, data preparation, and other functionalities with just a few clicks. Â
Another way is to add the Snowflake details through Fivetran. Once the User clicks on Partner Connect, a page with all the pre-built connectors will open, as shown in the picture below. If you don’t see a specific tool, always use the search bar to find the respective tool.
As shown below, a popup should appear once the User clicks on the Fivetran tool to establish a connection between Snowflake and Fivetran.
This popup shows the details of the default objects Fivetran can use. This removes the need to write scripts to create necessary objects like Databases, Warehouses, and Roles that can be designated for Fivetran’s use. The objects created through Partner Connect will have a default naming convention and cannot be altered.Â
Once the Connect button is clicked, the required objects will be created in Snowflake, and a connection will be established between Fivetran and Snowflake. Another way of establishing a connection between Fivetran and Snowflake is to add Snowflake details to successfully establish the connection to the correct destination.Â
As Snowflake will be the final destination to which the Salesforce Data will be moved, click the Destination tab on the left. This will give the Users the option to add the destination details.Â
Once the Add Destination button is clicked, Fivetran throws a popup asking the Users to name the Destination in Fivetran. Â
Once completed, the User will be directed to a different page that shows a list of all the destinations to which Fivetran has pre-built connectors. Once Snowflake is selected, the User will be navigated to another page where the configuration details must be added.Â
Before establishing the connection details, the User must create particular objects in Snowflake. These objects are as follows: Roles, Users, Warehouse, Database, etc. Since no objects are being built by default in this connection, the mentioned objects must be created manually.Â
Once the objects are built in Snowflake, the details in the above picture need to be filled. The host is the URL or your Snowflake account in the connection details. Under the User, Database, and Role, the User needs to define the names of the objects they created in Snowflake for Fivetran to use. The User can also Authenticate the connection either by Password or Key pair. Once completed and the connection has been successful, the User can start their first run.Â
Conclusion
Selecting the best ETL solution to handle your data can be challenging due to the increasing complexity of data and its wide range of applications across numerous organizational domains. One simple and effective way to handle challenging data integration jobs is to use Fivetran to ingest Salesforce data into Snowflake.Â
Fivetran makes things easier and enables the company to move any volume of data with little manual involvement because of its intuitive interface and library of pre-built connectors. Integrating Salesforce data into Snowflake via Fivetran optimizes the workflow, making it a valuable tool for any data-driven organization.Â
If you need additional assistance or have questions about integrating Salesforce data into Snowflake using Fivetran, please contact phData. Our team of experts can help guide you through the process, ensuring a seamless and efficient data integration solution tailored to your organization’s needs.
