How to load data from Apify Dataset to BigQuery

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

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About the source and destination

Apify Dataset

Apify is a web scraping and automation platform that can extract structured data from any website or automate any workflow on the web. For example, imagine you found a website selling shoes and want to get a spreadsheet with all the shoe sizes, colors, prices, etc., but the website doesn't make that information accessible in tabular form. Youcould certainly manually create such a spreadsheet using copy and paste, but that would take a lot of time and cause a lot of frustration. Or you can set up Apify to do this for you in a few seconds.

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.

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:

set up Apify Dataset as a source connector (using Auth, or usually an API key)
set up BigQuery as a destination connector
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 Apify Dataset

What is BigQuery

Integrate Apify Dataset with BigQuery in minutes

Try for free now

Prerequisites

A Apify Dataset account to transfer your customer data automatically from.
A BigQuery account.
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 Apify Dataset and BigQuery, for seamless data migration.

When using Airbyte to move data from Apify Dataset to BigQuery, it extracts data from Apify Dataset 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 Apify Dataset data for advanced analytics and insights within BigQuery, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Apify Dataset as a source connector

1. First, navigate to the Apify website and log in to your account.
2. Once you are logged in, click on the "API" tab in the top navigation bar.
3. Next, click on the "Credentials" tab and then click the "Create new token" button.
4. Give your token a name and select the appropriate permissions for your use case.
5. Copy the generated token to your clipboard.
6. Navigate to your Airbyte dashboard and click on the "Sources" tab.
7. Click on the "Add Source" button and select "Apify" from the list of available connectors.
8. In the "Connection Configuration" section, paste the token you copied from Apify into the "API Token" field.
9. Enter the name of the dataset you want to connect to in the "Dataset Name" field.
10. Click the "Test" button to ensure that the connection is successful.
11. If the test is successful, click the "Save" button to save your configuration.
12. You can now use the Apify source connector in Airbyte to extract data from your chosen dataset.

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 Apify Dataset data to BigQuery

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

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Apify Dataset from the dropdown list of your configured sources.
Select your destination: Choose BigQuery from the dropdown list of your configured destinations.
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.
Select the data to sync: Choose the specific Apify Dataset objects you want to import data from towards BigQuery. You can sync all data or select specific tables and fields.
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.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Apify Dataset 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 Apify Dataset data.

Use Cases to transfer your Apify Dataset data to BigQuery

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

Advanced Analytics: BigQuery’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Apify Dataset data, extracting insights that wouldn't be possible within Apify Dataset alone.
Data Consolidation: If you're using multiple other sources along with Apify Dataset, 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.
Historical Data Analysis: Apify Dataset has limits on historical data. Syncing data to BigQuery allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: BigQuery provides robust data security features. Syncing Apify Dataset data to BigQuery ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: BigQuery can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Apify Dataset data.
Data Science and Machine Learning: By having Apify Dataset data in BigQuery, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Apify Dataset 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 Apify Dataset 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:

Configure a Apify Dataset account as an Airbyte data source connector.
Configure BigQuery as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Apify Dataset 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!

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How to load data from Apify Dataset to BigQuery

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

Try Airbyte Cloud free

Deploy Airbyte Open Source

TL;DR

What is Apify Dataset

What is BigQuery

Prerequisites

Step 1: Setup Apify Dataset

Step 2: Setup BigQuery

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Apify Dataset and BigQuery

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Apify Dataset as a source connector (using Auth, or usually an API key)
set up BigQuery as a destination connector
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 Apify Dataset

What is BigQuery

Integrate Apify Dataset with BigQuery in minutes

Try for free now

Prerequisites

A Apify Dataset account to transfer your customer data automatically from.
A BigQuery account.
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.