Striking the right balance between Sales data accessibility and retaining control over your Pipedrive account can be quite challenging. This is where exporting your data from Pipedrive to BigQuery can help save your day. Many organizations want to take advantage of Google BigQuery’s capabilities to swiftly run complex analytical queries across petabytes of data.

Google BigQuery has become a globally trusted Cloud Data Warehouse & Analytics solution due to its fast and unrivaled query speed. It is a reliable and secure cloud platform for enterprises of all sizes, thanks to its on-demand scalability, affordable pricing, and ability to effectively handle variable workloads.

In this blog, you will walk through Pipedrive and Google BigQuery. You will explore the various features offered by them and also understand the need for Pipedrive BigQuery Integration. Further in this post, you will explore the key methods to load your data from Pipedrive to BigQuery. At the end of this post, you will discover some of the amazing benefits offered by the Pipedrive BigQuery Integration. Read along, to gain more insights and understand how this integration can help your use case.

Methods to Load Data from Pipedrive to BigQuery

In this section, you will understand how to move your data from Pipedrive to BigQuery using the following 2 methods:

Method 1: Load Data from Pipedrive to BigQuery using Hevo’s No-Code Data Pipeline

Pipedrive to BigQuery - Google BigQuery Hevo

Hevo provides an Automated No Code Data Pipeline that helps you move data from your Pipedrive to BigQuery. You can set up a Data Warehouse managed by Hevo on the fly, as part of the Integration process. The ingested data from the source is first stored in a Data Warehouse managed by Hevo and then loaded to the destination such as Databases, or Business Applications. Learn the benefits of loading your data to BigQuery here.

Hevo’s fault-tolerant architecture will enrich and transform your data securely and consistently and load it to your destination without any assistance from your side. You can entrust us with your data transfer process by both ETL and ELT processes to a data warehouse, Reverse ETL processes to CRMS, etc and enjoy a hassle-free experience.

Here are more reasons to try Hevo:

  • Smooth Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to your schema in the desired Data Warehouse.
  • Exceptional Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Fexibility designed for everyone.
  • Quick Setup: Hevo with its automated features, can be set up in minimal time. Moreover, with its simple and interactive UI, it is extremely easy for new customers to work on and perform operations.
  • Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
  • Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.

Try Hevo to easily load your data from Pipedrive to BigQuery!


Method 2: Load Data from Pipedrive to BigQuery using Pipedrive REST APIs

Pipedrive provides a plethora of endpoints through which you can communicate with the platform. These endpoints can be used to do tasks such as adding a new contact to your contact list and retrieving information from it.

A unique feature of the Pipedrive API is that for many of the resources, a companion resource controls the custom fields that you may have developed for the resource. Users of the platform will have the greatest freedom possible as a result of this. Some of the accessible resources that can be accessed using Pipedrive API are listed below:

  • Activities: Appointments, assignments, and events in general that can be linked to a contract and your sales funnel are referred to as activities.
  • Currencies: Supported currencies that can be used to indicate the monetary value of a Deal or the value of any custom monetary field.
  • Deals: Deals are ongoing, lost, or won sales to a company or individual.
  • Email Messages: EmailMessages are E-Mail messages sent or received using the Pipedrive E-Mail account.
  • Files: Files are any type of document that is uploaded to Pipedrive such as pictures, spreadsheets, text files, etc.
  • Goals: Goals assist your team in achieving their sales targets.
  • Organizations: Companies and other types of organizations with whom you do business are referred to as organizations.
  • Persons: Persons are your contacts or the clients with whom you conduct deals.
  • Pipelines: Pipelines are groups of Stages that are arranged in a certain sequence.
  • Products: The commodities or services with which you are dealing.
  • Stages: A Pipeline’s Stage is a logical component and, in essence, a bucket that can carry several Deals.
  • Users: People who have access to your Pipedrive account are known as users.

The above are just a few data resources you can export from Pipedrive to BigQuery using Pipedrive APIs. To learn about other data resources, refer to the Pipedrive API Documentation.

What are the Benefits of Loading Data from Pipedrive to BigQuery?

Now that you have understood the various methods of loading data from Pipedrive to BigQuery, let’s check out some of the key benefits this integration offers.

  • Turn your Pipedrive Data into Insights: With the Pipedrive to Google BigQuery connectivity, you can harness the power of data analytics to gain deep insights into your company. Large sets of historical data can be managed and processed without causing performance difficulties. Analyze all of your sales, revenue, profit, and pipeline data in one location using analytics-friendly CRM data. Take use of Google BigQuery’s analytical querying and predictive sales analysis.
  • Secure Backup of Pipedrive Data: To keep all of your pipeline data safe and secure in a scalable cloud-based database, load data from Pipedrive to Google BigQuery on a specified schedule. Create a data lake for a reasonable price with Google BigQuery. Use common SQL queries to quickly explore your data. If you lose data on Pipedrive due to a server breakdown, an accidental deletion, or other disasters, you can restore it or move it to another machine.
  • Build Advanced Dashboards: To generate comprehensive and stunning visualizations, combine your data from Pipedrive and other sources in Google BigQuery and leverage a direct Data Studio connection. Fast Data Studio reports based on BigQuery are available. Collaborate on multiple dashboards with your peers using collaborative editing. Alternatively, use built-in connectors to connect Google BigQuery data views to other popular BI applications like Power BI or Tableau.


In this article, you gained a basic understanding of Pipedrive and BigQuery. You also explored the 2 methods to load your data from Pipedrive to BigQuery. At the end of this article, you discovered the various advantages of migrating data from Pipedrive to BigQuery. 

However, knowing where to start and how to combine consumer data from various applications can be a challenge for many companies. This is where Hevo can help save your day!

Hevo Data is a No-Code Data Pipeline that offers a faster way to move data from 100+ Data Sources including 40+ Free Sources, into your Data Warehouse such as Google BigQuery. Hevo is fully automated and hence does not require you to code.


Want to take Hevo for a spin?

SIGN UP and experience the feature-rich Hevo suite first hand. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.

Share your experience with loading data from Pipedrive to BigQuery in the comments section below!

Former Research Analyst, Hevo Data

Shubnoor is a Data Analyst with extensive expertise in market research, and crafting marketing strategies for data industry. At Hevo, she specialized in developing connector integrations and product requirement documentation for multiple SaaS sources.

No-Code Data Pipeline for Google BigQuery