Connect Salesforce to Google BigQuery

salesforce bigquery integrate

Analyze your Salesforce data with Google BigQuery

Connect Salesforce to Google BigQuery in 2023

It is very simple to connect Salesforce to Google BigQuery, it can be done in a fast and easy manner with Windsor.ai.

 

First Step:

Sign up for Windsor.ai. You can also take advantage of the free trial to get a feel of the platform and see its features.

Once in your account’s dashboard, select Salesforce in the left column as a data source.

Salesforce Windsor.ai Onboarding Screen

 

Second Step:

Once you select the data source, click the Next (Data Preview Button). 

Select BigQuery by clicking on the logo, as shown in the screenshot below.  

select bigquery

 

Third Step:

Once you select Bigquery, click the Add Destination Task Button and fill out necessary fields . 

create bigQuery destination task

Fourth Step:

In the final step, grant access to the user: bq-upload@windsor-ai-bigquery.iam.gserviceaccount.com. That’s all!

Once you go through these steps, you will see that the data is automatically populated into your BigQuery account.

 

Note: As a connector URL, you can use any URL providing a JSON. Either from the connectors or for example a URL with cached and transformed data.

 

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Why integrate Salesforce to BigQuery?

Integrating Salesforce with BigQuery offers several benefits for businesses:

  1. Centralized Data Analysis: By integrating Salesforce with BigQuery, you can bring together your customer data from Salesforce and other sources into a single data warehouse. This centralization allows you to perform comprehensive data analysis and gain a holistic view of your customers, products, and business operations.
  2. Scalability and Performance: BigQuery is a highly scalable and fully managed data warehouse solution provided by Google Cloud. It can handle large volumes of data and perform complex queries efficiently, enabling you to process and analyze vast amounts of Salesforce data without performance bottlenecks.
  3. Advanced Analytics: BigQuery provides powerful analytics capabilities, including machine learning and data visualization tools. By combining Salesforce data with other datasets within BigQuery, you can leverage these advanced analytics features to uncover valuable insights, identify patterns, predict customer behavior, and optimize your business strategies.
  4. Real-time and Near-real-time Analysis: Integrating Salesforce with BigQuery allows you to capture and analyze real-time or near-real-time data. You can set up data pipelines or use connectors to stream data from Salesforce into BigQuery, ensuring that your analysis reflects the most up-to-date information. This capability is especially useful for monitoring sales performance, customer interactions, and marketing campaigns in real-time.
  5. Cross-functional Insights: By integrating Salesforce data with other sources such as marketing platforms, customer support systems, or financial data, you can gain cross-functional insights. This integration enables you to analyze the entire customer journey, understand the impact of marketing campaigns on sales, measure customer satisfaction and retention, and make data-driven decisions across different business functions.

 

What data to export from Salesforce to BigQuery?

  • Calendar
  • Account
  • Contact
  • Campaign
  • Contact
  • Order
  • Payment
  • Product
  • Case
  • Asset
  • Custom Salesforce Objects
  • User
  • Task
  • Lead
  • Opportunity

 

Salesforce to Bigquery by writing custom code

You are correct that using the APIs provided by Salesforce and BigQuery gives you a high level of flexibility and control over data import and export operations. You can write code in your preferred programming language, such as Java or Python, to handle the data transfer operations according to your specific requirements. 

 

When it comes to writing custom code to transfer data from Salesforce to BigQuery, there are several disadvantages to consider:

 

  1. Resource Requirements: Developing and maintaining custom code requires skilled programmers who are knowledgeable about both Salesforce and BigQuery. Finding and retaining such resources can be challenging and expensive.
  2. Platform Knowledge: Custom code needs to account for the intricacies of both Salesforce and BigQuery. Understanding the internals and nuances of these platforms is essential to ensure data integrity and efficient data transfer.
  3. Testing and Verification: Building a custom solution requires a dedicated team to test and verify that the desired data is successfully transferred to BigQuery. This team must ensure the data is in a suitable format for further analysis, which adds complexity and time to the development process.
  4. Maintenance and Updates: Custom code needs to be regularly updated to accommodate any changes in your business processes or the underlying platforms. This ongoing maintenance effort can be time-consuming and costly, as it requires constant monitoring and adjustment.
  5. Data Source Integration: When using custom code, you’ll have to write multiple programs to extract data from different sources and transfer them to BigQuery. This can be a complex and labor-intensive task, especially if you have disparate data sources. 
  6. Cost Considerations: The investment required for developing custom code, including programming resources, testing, maintenance, and updates, can quickly exceed the cost of using a specialized data integration platform like Windsor.ai. The upfront savings of building a custom solution can be outweighed by the long-term expenses associated with its development and maintenance.

 

Using a dedicated data integration platform like Windsor.ai can provide a more efficient and cost-effective solution for transferring data from Salesforce to BigQuery.

 

How much time do I need to create a Salesforce and BigQuery integration?

Windsor.ai’s user-friendly interface allows you to create integrations in less than 9 minutes.

 

Conclusion

Overall, integrating Salesforce with BigQuery empowers businesses to unlock the full potential of their customer data, perform advanced analytics, and make data-driven decisions that drive growth and improve customer experiences.

 

Windsor.ai is an ETL tool that integrates with multiple sources or services like databases, CRM, email campaigns, analytics and more. Quickly and safely move all your data from Salesforce into Google BigQuery and start generating insights from your data.

 

See how easy it is to migrate data from Salesforce to BigQuery and that too for free.

Try Windsor.ai today

Access all your data from your favorite sources in one place.
Get started for free with a 30 - day trial.

Start Free Trial

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