Connect Salesforce to Snowflake

Connect Salesforce to Snowflake in 2023

Many organizations are turning to Salesforce to improve the sales process, but integrating this software with other applications can be difficult. Snowflake is a cloud-based data warehouse that can simplify the integration process by providing a single platform for all your data and analytics needs.

Salesforce is an excellent platform for businesses of all sizes. It offers a wide range of features and functionality that you can customize to meet the needs of any organization.

However, even with its flexibility, there may be times when you need integrations such as Snowflake Salesforce to maximize effectiveness. Fortunately, there are several easy methods you can use to do this.

This page will explore several ways to integrate Snowflake with Salesforce. We’ll also discuss each approach’s pros and cons so you can decide which is best for your business. Stay tuned!

Table of content

1. What is Salesforce and SnowFlake?
2. Why connect Snowflake to Salesforce?
3. How can I connect Salesforce and Snowflake?
4. Conclusion
5. FAQ: Salesforce to Snowflake Integration

What is Salesforce and SnowFlake?

What is SalesForce?

Salesforce is a leading cloud-based CRM platform (all-in-one platform for Sales, Service, Marketing and more) that integrates with an amazing number of applications and is used by companies to handle everything from customer servicing, account management and digital marketing to time management, team collaboration etc.

If you use Salesforce, you are aware of all the data it generates and the need to securely load and query that data for valuable business and customer insights.

What is Snowflake?

Snowflake refers to a cloud-based data warehouse service and the company that provides it. Snowflake’s data warehouse service is built for the cloud and offers a unique architecture optimized for data warehouse workloads.

This allows businesses to use Snowflake to store and analyze data in the cloud without having to set up and manage their data warehouse infrastructure.

In addition to its cloud-based data warehouse service, Snowflake offers several other products and services, including a data integration platform, a data exchange service, and a data analytics platform.

Why connect Snowflake to Salesforce?

With Snowflake and Salesforce integration, businesses can use the best of both platforms by using Snowflake’s powerful data warehousing capabilities to complement Salesforce’s sales and marketing data.

For example, businesses can use Snowflake to extract data from Salesforce, clean and prepare it for analysis, and load it into a data warehouse.

Businesses can use Snowflake’s SQL query language to run complex queries on their data.

You can use the combination of Salesforce and Snowflake to answer several business questions, such as:

• How effective is your sales team at converting leads into customers?

• What are the most common reasons that customers churn?

• What are the most popular products or services that your customers purchase?

• How do seasonal changes impact your sales?

• Which marketing campaigns are the most effective at generating leads?

How can I connect Salesforce and Snowflake?

Various connectors allow Snowflake Salesforce integration. When deciding how to connect the two platforms, you’ll need to consider factors such as the data you want to transfer, the frequency of data transfers, and the level of integration you need.

Below are four different methods you can use for Snowflake to Salesforce integration:

Method 1: Easily Move Data from Salesforce to Snowflake Using Windsor.ai Connector

The Windsor.ai Connector is a point-and-click tool that makes it easy to connect all your sales, marketing, and CRM data. For example, you can connect Google Analytics 4, Salesforce, Facebook Ads, and LinkedIn Ads in minutes without writing any code.

With this Snowflake Salesforce connector, the integration between the two tools is seamless, and you’re set in just a few steps. 

The steps involved in the Salesforce Snowflake integration using the Windsor.ai Connector are as follows:

Step 1: Sign up for a Windsor.ai account

The first step is to sign up for a Windsor.ai account. You can do this by going to the Windsor.ai website and clicking on the “Sign Up” button. You will then be prompted to enter your email address and create a password.

Step 2: Grant access to your Snowflake account

2.1 The first step will be adding all the columns your connector’s URL returns.

2.2 Next, establish the WINDSOR_UPLOAD role.

2.3 Now that you have a role, create a user, then give that user the previously created role.

2.4 The created user will also require rights to the database. As the system admin, grant your user database privileges.

2.5 The next step is to grant rights, including delete, insert, select, and update, to the destination table.

2.6 You will then need to fetch the necessary fields from Snowflake to use the Snowflake destination in the Onboard Form. The fields include:

Username

Password

Account

Warehouse

Database

Schema

Table name

Step 3: Choose Snowflake as destination

Connecting your data sources to the Windsor.ai Snowflake to Salesforce connector allows you to select and transfer Salesforce data to Snowflake.

Once you connect Salesforce to Windsor.ai, you’ll need to select Snowflake as your destination. 

Step 4: Enter your Snowflake account details

When prompted, enter your Snowflake account details. After selecting Snowflake, all your data is streamed in real-time, so you’ll always have up-to-date data in Snowflake.

After the Snowflake Salesforce connection, you can apply data-driven attribution on the conversion journeys. This lets you see which marketing channels are the most effective at generating leads and customers.

It also lets you see how different channels work together to create a customer journey. This is a valuable tool for optimizing your marketing efforts.

Snowflake and Salesforce integration using Windsor.ai allows you to join the costs of all connected channels. This helps you understand the return on ad spend (ROAS), cost per acquisition (CPA), and other important KPIs.

It also allows you to optimize your marketing efforts for the maximum return on investment and see which channels are the most efficient at generating leads and customers.

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Method 2: Load Data from Salesforce to Snowflake using Tableau CRM Integration

Tableau CRM is a software company that provides data visualization and analytics solutions. The Tableau CRM integration is a cloud-based solution that acts as a Snowflake Salesforce connector.

The steps involved in using the Tableau CRM integration as a Salesforce Snowflake connector are:

Step1: Sign up for a Tableau CRM account

You can sign up for a Tableau CRM account by going to the Tableau website and clicking on the “Try Now” tab. You will need to enter your contact information on the Tableau CRM page.

The Tableau CRM free trial allows you to use all the software’s features for 14 days and see if it’s a good fit for your needs. After the trial, you must acquire a paid Tableau CRM license to continue using it.

Step 2: Build Snowflake objects

You must represent any Salesforce data you intend to move to Snowflake as a Tableau CRM object. To do this, you’ll need to create a new object in Tableau CRM. Find a warehouse to load your data, then create a new database and schema that are compatible with your Salesforce data.

After setting these up, create a new Role and grant usage access to the database, warehouse, and schema. You will also need to assign this Role to a User who will create and replace tables. They require the ability to insert, truncate, update, merge data, and create a temporary internal stage.

You should create a user specifically to avoid giving full control of your data warehouse.

Step 3: Enable Tableau CRM sync out

In order to load data from Salesforce to Snowflake, you will need to enable sync out in Tableau CRM. Tableau CRM is available in performance, enterprise, and unlimited Salesforce editions.

From the Salesforce setup menu, type “Analytics” into the fast find box and select “Settings” from the drop-down list. Check “Enable Data Sync and Connections” and “Enable Snowflake Output Connection” after opening the settings panel, then hit “Save.”

Step 4: Configure the Snowflake output connection

Open Salesforce and access the Analytics Studio app. Open the Connect page by going to Data Manager in the left-hand column and clicking “Connect to Data.” From this point, you may choose the “Snowflake” data source type and input your Snowflake login information, which includes the Connection Name, Developer Identity, Description, Username, Role, Passcode, Account, Database, Warehouse, and Schema information.

You should not include any capital letters in your Snowflake details or lowercase letters in your Schema, Username, Database, and Role.

Step 5: Connect to Salesforce data

You can connect Snowflake to Salesforce after configuring your Snowflake output connection. In the Connections window, open your Salesforce database sync settings, enable the object you would like to sync, and click “Continue.”

Tableau CRM will automatically map the data fields from Salesforce to Snowflake. You can also use Tableau CRM’s transformation rules to customize the data mapping further.

Step 6: Enable Tableau CRM sync out and create a schedule

The final step is to enable sync out and create a schedule. Click the drop-down arrow at the top-right of the table and click “Sync Out.” Flick the toggle to enable sync out and click save.

Click the same drop-down menu and click “Schedule” to create your schedule. You will need to modify this stage based on your company’s needs, but the options are self-explanatory.

Method 3: Load Data from Salesforce to Snowflake using Data loader

A data loader is a tool that helps you to load data into Salesforce from a comma-separated values (CSV) file. The data loader is handy when you want to load a large amount of data into Salesforce since it has an upload of up to 5 million records per sync. It is also helpful when you want to schedule the loading of data into Salesforce so that you can keep your data up-to-date.

To implement a data loader, follow the steps below:

Step1: Download and install the data loader on your computer

The data loader is available for free from Salesforce. You can download it from AppExchange. Once you download it, double-click on the file to begin the installation process and follow the instructions on the screen.

Step 2: Configure the data loader

Open the data loader and click “Configuration” in the left-hand side panel. Enter your Salesforce username, password, and security token.

The security token is a unique code that Salesforce generates. You can find it by logging into Salesforce and going to “My Profile” > “Personal” > “Reset My Security Token.” Once you enter your Salesforce credentials, click “Login” and then “Allow.”

Step 3: Map the data fields

The next step is to map the data fields from the CSV file to the fields in Salesforce. To do this, click “Map Fields” and then “Create New Map.” Select the CSV file you want to upload and click “Next.”

Choose the object you want to update in Salesforce and then map the fields from the CSV file to the fields in Salesforce.

Step 4: Load the data

Once you have mapped the fields, you can load data from Snowflake to Salesforce. To do this, click “Load Data” and then “Add to Queue.” Select the CSV file you want to upload and click “Next.” Choose the object you want to update in Salesforce and click “Start Load.” The data loader will then upload the data into Salesforce.

Method 4: Move Data from Salesforce to Snowflake Using Data import wizard

The Data import wizard is a tool that helps you to load data into Salesforce from a comma-separated values (CSV) file. It is similar to the data loader but has a few limitations. The data import wizard can only upload up to 50,000 records per sync and cannot schedule data loading.

To implement the data import wizard, follow the steps below:

Step 1: Log into Salesforce

The first step is to log into Salesforce and go to Setup. Enter “data import” in the search bar and click “Data Import Wizard.”

Step 2: Select the object you want to update

The next step is selecting the object you want to update. The data import wizard supports most standard and custom objects. Choose custom or standard objects and select the type of import you want to perform. You can add new records, update existing records, or upsert new records.

Step 3: Map the data fields

Next, map the fields from the CSV file to the fields in Salesforce. To do this, click “Map Fields” and then “Create New Map.” Select the CSV file you want to upload and click “Next.” Choose the object you want to update in Salesforce and then map the fields from the CSV file to the fields in Salesforce.

The Data Import Wizard is not automatic, and you will need to select the object you want to update and map the fields manually. If you want to automate the process, you can use the data loader.

Conclusion

When it comes to choosing a cloud-based data platform, it depends on your needs. Snowflake will be a good choice if you are mainly concerned with storing and querying data. However, if you are interested in managing customer relationships, then Salesforce would be a better option.

No matter which platform you choose, Windsor.ai can help you load your data into Salesforce. Windsor.ai is a cloud-based data integration platform that makes it easy to load data from Snowflake to Salesforce. Windsor.ai offers a free trial, so you can try it out before you commit to a subscription.

A Snowflake to Salesforce connector allows you to schedule data transfers and map data fields. Sign up for a free trial today and see how Windsor.ai can help you streamline your Snowflake to Salesforce integration process.

FAQ: Salesforce to Snowflake Integration

What is the difference between Snowflake and Salesforce?

The main difference between Snowflake and Salesforce is that Snowflake is a cloud-based data warehouse while Salesforce is a cloud-based CRM. Both platforms are designed to help businesses manage their data but have different functionality.

Snowflake is mainly used for storing and querying data, while Salesforce is used for managing customer relationships.

The platforms also differ in terms of pricing. Snowflake charges based on the amount of data stored and queried, while Salesforce charges based on the number of users and the features used.

Why sync data from Snowflake to Salesforce?

Salesforce is the single source of truth for your sales team, but it only shows one view of your customer. Actually, all of your product usage data, event data, and custom audiences live in Snowflake. To truly have a 360-degree view of your customer, your sales team needs access to this information.

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