How to load data from Marketo to BigQuery

Learn how to use Airbyte to synchronize your Marketo data into BigQuery within minutes.

Try Airbyte Cloud
Get a demo

Trusted by data-driven companies

Building your pipeline or Using Airbyte

Airbyte is the only open solution empowering data teams  to meet all their growing custom business demands in the new AI era.

Building in-house pipelines
Bespoke pipelines are:
  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.
After Airbyte
Airbyte connections are:
  • Reliable and accurate
  • Extensible and scalable for all your needs
  • Deployed and governed your way
All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Marketo connector in Airbyte

Connect to Marketo or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up BigQuery for your extracted Marketo data

Select BigQuery where you want to import data from your Marketo source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Marketo to BigQuery in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
Try Airbyte Cloud

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Talk to our team

Old Automated Content

TL;DR

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

  1. set up Marketo as a source connector (using Auth, or usually an API key)
  2. set up BigQuery as a destination connector
  3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Marketo

Marketo develops the marketing automation software underlying the capabilities of inbound marketing solutions, CRM, social marketing, and other services of the same type. A powerful yet simple-to-use solution for any size company, Marketo was built by marketers for marketers, so it is designed with the needs and solutions required by real businesses in mind. Marketo aims to simplify the marketing process with an all-in-one solution that includes social marketing, event management, marketing ROI and analytics reports, CRM integration, and more.

What is BigQuery

BigQuery is an enterprise data warehouse that draws on the processing power of Google Cloud Storage to enable fast processing of SQL queries through massive datasets. BigQuery helps businesses select the most appropriate software provider to assemble their data, based on the platforms the business uses. Once a business’ data is acculumated, it is moved into BigQuery. The company controls access to the data, but BigQuery stores and processes it for greater speed and convenience.

Integrate Marketo with BigQuery in minutes

Try for free now

Prerequisites

  1. A Marketo account to transfer your customer data automatically from.
  2. A BigQuery account.
  3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Marketo and BigQuery, for seamless data migration.

When using Airbyte to move data from Marketo to BigQuery, it extracts data from Marketo using the source connector, converts it into a format BigQuery can ingest using the provided schema, and then loads it into BigQuery via the destination connector. This allows businesses to leverage their Marketo data for advanced analytics and insights within BigQuery, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Marketo as a source connector

1. First, navigate to the "Sources" tab on the Airbyte dashboard and click "New Source".

2. Select "Marketo" from the list of available sources.

3. Enter a name for your Marketo source connector and click "Next".

4. Enter your Marketo credentials, including your Client ID, Client Secret, and REST Endpoint URL. You can find these credentials in your Marketo account under "Admin" > "LaunchPoint".

5. Click "Test" to ensure that your credentials are correct and that Airbyte can connect to your Marketo account.

6. Once your credentials have been verified, select the objects you want to replicate from Marketo. You can choose from a variety of objects, including leads, opportunities, and campaigns.

7. Configure any additional settings, such as the replication frequency and the number of records to replicate per batch.

8. Click "Create Source" to save your Marketo source connector.

9. Your Marketo data will now be replicated to Airbyte, where you can use it to create pipelines and sync your data with other destinations.

Step 2: Set up BigQuery as a destination connector

1. First, navigate to the Airbyte dashboard and select the "Destinations" tab on the left-hand side of the screen.

2. Scroll down until you find the "BigQuery" destination connector and click on it.

3. Click the "Create Destination" button to begin setting up your BigQuery destination.

4. Enter your Google Cloud Platform project ID and service account credentials in the appropriate fields.

5. Next, select the dataset you want to use for your destination and enter the table prefix you want to use.

6. Choose the schema mapping for your data, which will determine how your data is organized in BigQuery.

7. Finally, review your settings and click the "Create Destination" button to complete the setup process.

8. Once your destination is created, you can begin configuring your source connectors to start syncing data to BigQuery.

9. To do this, navigate to the "Sources" tab on the left-hand side of the screen and select the source connector you want to use.

10. Follow the prompts to enter your source credentials and configure your sync settings.

11. When you reach the "Destination" step, select your BigQuery destination from the dropdown menu and choose the dataset and table prefix you want to use.

12. Review your settings and click the "Create Connection" button to start syncing data from your source to your BigQuery destination.

Step 3: Set up a connection to sync your Marketo data to BigQuery

Once you've successfully connected Marketo as a data source and BigQuery as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

  1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
  2. Choose your source: Select Marketo from the dropdown list of your configured sources.
  3. Select your destination: Choose BigQuery from the dropdown list of your configured destinations.
  4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
  5. Select the data to sync: Choose the specific Marketo objects you want to import data from towards BigQuery. You can sync all data or select specific tables and fields.
  6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
  7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
  8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Marketo to BigQuery according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your BigQuery data warehouse is always up-to-date with your Marketo data.

Use Cases to transfer your Marketo data to BigQuery

Integrating data from Marketo to BigQuery provides several benefits. Here are a few use cases:

  1. Advanced Analytics: BigQuery’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Marketo data, extracting insights that wouldn't be possible within Marketo alone.
  2. Data Consolidation: If you're using multiple other sources along with Marketo, syncing to BigQuery allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
  3. Historical Data Analysis: Marketo has limits on historical data. Syncing data to BigQuery allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: BigQuery provides robust data security features. Syncing Marketo data to BigQuery ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: BigQuery can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Marketo data.
  6. Data Science and Machine Learning: By having Marketo data in BigQuery, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While Marketo provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to BigQuery, providing more advanced business intelligence options. If you have a Marketo table that needs to be converted to a BigQuery table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a Marketo account as an Airbyte data source connector.
  2. Configure BigQuery as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from Marketo to BigQuery after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that supports both incremental and full refreshes, for databases of any size.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Jean-Mathieu Saponaro
Data & Analytics Senior Eng Manager

"The intake layer of Datadog’s self-serve analytics platform is largely built on Airbyte.Airbyte’s ease of use and extensibility allowed any team in the company to push their data into the platform - without assistance from the data team!"

Learn more
Chase Zieman headshot
Chase Zieman
Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more
Alexis Weill
Data Lead

“We chose Airbyte for its ease of use, its pricing scalability and its absence of vendor lock-in. Having a lean team makes them our top criteria.
The value of being able to scale and execute at a high level by maximizing resources is immense”

Learn more

Sync with Airbyte

1. First, navigate to the "Sources" tab on the Airbyte dashboard and click "New Source".

2. Select "Marketo" from the list of available sources.

3. Enter a name for your Marketo source connector and click "Next".

4. Enter your Marketo credentials, including your Client ID, Client Secret, and REST Endpoint URL. You can find these credentials in your Marketo account under "Admin" > "LaunchPoint".

5. Click "Test" to ensure that your credentials are correct and that Airbyte can connect to your Marketo account.

6. Once your credentials have been verified, select the objects you want to replicate from Marketo. You can choose from a variety of objects, including leads, opportunities, and campaigns.

7. Configure any additional settings, such as the replication frequency and the number of records to replicate per batch.

8. Click "Create Source" to save your Marketo source connector.

9. Your Marketo data will now be replicated to Airbyte, where you can use it to create pipelines and sync your data with other destinations.

1. First, navigate to the Airbyte dashboard and select the "Destinations" tab on the left-hand side of the screen.

2. Scroll down until you find the "BigQuery" destination connector and click on it.

3. Click the "Create Destination" button to begin setting up your BigQuery destination.

4. Enter your Google Cloud Platform project ID and service account credentials in the appropriate fields.

5. Next, select the dataset you want to use for your destination and enter the table prefix you want to use.

6. Choose the schema mapping for your data, which will determine how your data is organized in BigQuery.

7. Finally, review your settings and click the "Create Destination" button to complete the setup process.

8. Once your destination is created, you can begin configuring your source connectors to start syncing data to BigQuery.

9. To do this, navigate to the "Sources" tab on the left-hand side of the screen and select the source connector you want to use.

10. Follow the prompts to enter your source credentials and configure your sync settings.

11. When you reach the "Destination" step, select your BigQuery destination from the dropdown menu and choose the dataset and table prefix you want to use.

12. Review your settings and click the "Create Connection" button to start syncing data from your source to your BigQuery destination.

Once you've successfully connected Marketo as a data source and BigQuery as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

  1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
  2. Choose your source: Select Marketo from the dropdown list of your configured sources.
  3. Select your destination: Choose BigQuery from the dropdown list of your configured destinations.
  4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
  5. Select the data to sync: Choose the specific Marketo objects you want to import data from towards BigQuery. You can sync all data or select specific tables and fields.
  6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
  7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
  8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Marketo to BigQuery according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your BigQuery data warehouse is always up-to-date with your Marketo data.

How to Sync Marketo to BigQuery Manually

FAQs

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

Marketo develops the marketing automation software underlying the capabilities of inbound marketing solutions, CRM, social marketing, and other services of the same type. A powerful yet simple-to-use solution for any size company, Marketo was built by marketers for marketers, so it is designed with the needs and solutions required by real businesses in mind. Marketo aims to simplify the marketing process with an all-in-one solution that includes social marketing, event management, marketing ROI and analytics reports, CRM integration, and more.

Marketo's API provides access to a wide range of data related to marketing automation and customer engagement. The following are the categories of data that can be accessed through Marketo's API:  

1. Lead data: This includes information about individual leads such as their name, email address, phone number, company, job title, and other demographic information.  

2. Campaign data: This includes information about marketing campaigns such as email campaigns, social media campaigns, and other types of marketing initiatives.  

3. Activity data: This includes information about the activities that leads have taken such as opening an email, clicking on a link, visiting a website, or filling out a form.  

4. Analytics data: This includes information about the performance of marketing campaigns such as open rates, click-through rates, conversion rates, and other metrics.  

5. Account data: This includes information about the companies that leads work for such as company size, industry, and other relevant information.  

6. Custom object data: This includes information about custom objects that have been created within Marketo such as events, webinars, and other types of marketing initiatives.  

Overall, Marketo's API provides access to a wealth of data that can be used to improve marketing automation and customer engagement efforts.

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: 
1. Set up Marketo to BigQuery as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Marketo to BigQuery and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Back to all tutorials
Warehouses and Lakes
Marketing Analytics

How to load data from Marketo to BigQuery

Learn how to use Airbyte to synchronize your Marketo data into BigQuery within minutes.

TL;DR
What is Marketo
What is BigQuery
Prerequisites
Step 1: Setup Marketo
Step 2: Setup BigQuery
Step 3: Setup a connectionUse CasesWrapping Up
Example H2
Example H3

Sync data between Marketo and BigQuery

Try Airbyte free

TL;DR

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

  1. set up Marketo as a source connector (using Auth, or usually an API key)
  2. set up BigQuery as a destination connector
  3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Marketo

Marketo develops the marketing automation software underlying the capabilities of inbound marketing solutions, CRM, social marketing, and other services of the same type. A powerful yet simple-to-use solution for any size company, Marketo was built by marketers for marketers, so it is designed with the needs and solutions required by real businesses in mind. Marketo aims to simplify the marketing process with an all-in-one solution that includes social marketing, event management, marketing ROI and analytics reports, CRM integration, and more.

What is BigQuery

BigQuery is an enterprise data warehouse that draws on the processing power of Google Cloud Storage to enable fast processing of SQL queries through massive datasets. BigQuery helps businesses select the most appropriate software provider to assemble their data, based on the platforms the business uses. Once a business’ data is acculumated, it is moved into BigQuery. The company controls access to the data, but BigQuery stores and processes it for greater speed and convenience.

Integrate Marketo with BigQuery in minutes

Try for free now

Prerequisites

  1. A Marketo account to transfer your customer data automatically from.
  2. A BigQuery account.
  3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Marketo and BigQuery, for seamless data migration.

When using Airbyte to move data from Marketo to BigQuery, it extracts data from Marketo using the source connector, converts it into a format BigQuery can ingest using the provided schema, and then loads it into BigQuery via the destination connector. This allows businesses to leverage their Marketo data for advanced analytics and insights within BigQuery, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Marketo as a source connector

1. First, navigate to the "Sources" tab on the Airbyte dashboard and click "New Source".

2. Select "Marketo" from the list of available sources.

3. Enter a name for your Marketo source connector and click "Next".

4. Enter your Marketo credentials, including your Client ID, Client Secret, and REST Endpoint URL. You can find these credentials in your Marketo account under "Admin" > "LaunchPoint".

5. Click "Test" to ensure that your credentials are correct and that Airbyte can connect to your Marketo account.

6. Once your credentials have been verified, select the objects you want to replicate from Marketo. You can choose from a variety of objects, including leads, opportunities, and campaigns.

7. Configure any additional settings, such as the replication frequency and the number of records to replicate per batch.

8. Click "Create Source" to save your Marketo source connector.

9. Your Marketo data will now be replicated to Airbyte, where you can use it to create pipelines and sync your data with other destinations.

Step 2: Set up BigQuery as a destination connector

1. First, navigate to the Airbyte dashboard and select the "Destinations" tab on the left-hand side of the screen.

2. Scroll down until you find the "BigQuery" destination connector and click on it.

3. Click the "Create Destination" button to begin setting up your BigQuery destination.

4. Enter your Google Cloud Platform project ID and service account credentials in the appropriate fields.

5. Next, select the dataset you want to use for your destination and enter the table prefix you want to use.

6. Choose the schema mapping for your data, which will determine how your data is organized in BigQuery.

7. Finally, review your settings and click the "Create Destination" button to complete the setup process.

8. Once your destination is created, you can begin configuring your source connectors to start syncing data to BigQuery.

9. To do this, navigate to the "Sources" tab on the left-hand side of the screen and select the source connector you want to use.

10. Follow the prompts to enter your source credentials and configure your sync settings.

11. When you reach the "Destination" step, select your BigQuery destination from the dropdown menu and choose the dataset and table prefix you want to use.

12. Review your settings and click the "Create Connection" button to start syncing data from your source to your BigQuery destination.

Step 3: Set up a connection to sync your Marketo data to BigQuery

Once you've successfully connected Marketo as a data source and BigQuery as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

  1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
  2. Choose your source: Select Marketo from the dropdown list of your configured sources.
  3. Select your destination: Choose BigQuery from the dropdown list of your configured destinations.
  4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
  5. Select the data to sync: Choose the specific Marketo objects you want to import data from towards BigQuery. You can sync all data or select specific tables and fields.
  6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
  7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
  8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Marketo to BigQuery according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your BigQuery data warehouse is always up-to-date with your Marketo data.

Use Cases to transfer your Marketo data to BigQuery

Integrating data from Marketo to BigQuery provides several benefits. Here are a few use cases:

  1. Advanced Analytics: BigQuery’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Marketo data, extracting insights that wouldn't be possible within Marketo alone.
  2. Data Consolidation: If you're using multiple other sources along with Marketo, syncing to BigQuery allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
  3. Historical Data Analysis: Marketo has limits on historical data. Syncing data to BigQuery allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: BigQuery provides robust data security features. Syncing Marketo data to BigQuery ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: BigQuery can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Marketo data.
  6. Data Science and Machine Learning: By having Marketo data in BigQuery, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While Marketo provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to BigQuery, providing more advanced business intelligence options. If you have a Marketo table that needs to be converted to a BigQuery table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a Marketo account as an Airbyte data source connector.
  2. Configure BigQuery as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from Marketo to BigQuery after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

Marketo
BigQuery

Related Syncs with Marketo

Tags

Analytical Platforms

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

Marketo
BigQuery

Related Syncs with Marketo

Marketo to AWS Datalake
Marketo to BigQuery
Marketo to Databricks Lakehouse
Marketo to Firebolt
Marketo to Redshift
Marketo to S3
Marketo to S3 Glue
Marketo to Snowflake Data Cloud

Tags

Analytical Platforms

Ready to get started?

Try Airbyte Cloud freeTalk to our team

Frequently Asked Questions

What data can you extract from Marketo?

Marketo's API provides access to a wide range of data related to marketing automation and customer engagement. The following are the categories of data that can be accessed through Marketo's API:  

1. Lead data: This includes information about individual leads such as their name, email address, phone number, company, job title, and other demographic information.  

2. Campaign data: This includes information about marketing campaigns such as email campaigns, social media campaigns, and other types of marketing initiatives.  

3. Activity data: This includes information about the activities that leads have taken such as opening an email, clicking on a link, visiting a website, or filling out a form.  

4. Analytics data: This includes information about the performance of marketing campaigns such as open rates, click-through rates, conversion rates, and other metrics.  

5. Account data: This includes information about the companies that leads work for such as company size, industry, and other relevant information.  

6. Custom object data: This includes information about custom objects that have been created within Marketo such as events, webinars, and other types of marketing initiatives.  

Overall, Marketo's API provides access to a wealth of data that can be used to improve marketing automation and customer engagement efforts.

What data can you transfer to BigQuery?

You can transfer a wide variety of data to BigQuery. This usually includes structured, semi-structured, and unstructured data like transaction records, log files, JSON data, CSV files, and more, allowing robust, scalable data integration and analysis.

What are top ETL tools to transfer data from Marketo to BigQuery?

The most prominent ETL tools to transfer data from Marketo to BigQuery include:

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • Talend Data Integration

These tools help in extracting data from Marketo and various sources (APIs, databases, and more), transforming it efficiently, and loading it into BigQuery and other databases, data warehouses and data lakes, enhancing data management capabilities.

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

Marketo
BigQuery

Related Syncs with Marketo

Marketo to AWS Datalake
Marketo to BigQuery
Marketo to Databricks Lakehouse
Marketo to Firebolt
Marketo to Redshift
Marketo to S3
Marketo to S3 Glue
Marketo to Snowflake Data Cloud

Tags

Analytical Platforms

Connectors Used

Marketo
BigQuery

Related Syncs with Marketo

Marketo to AWS Datalake
Marketo to BigQuery
Marketo to Databricks Lakehouse
Marketo to Firebolt
Marketo to Redshift
Marketo to S3
Marketo to S3 Glue
Marketo to Snowflake Data Cloud

Tags

Analytical Platforms