How to load data from Wikipedia Pageviews to Starburst Galaxy

Learn how to use Airbyte to synchronize your Wikipedia Pageviews data into Starburst Galaxy within minutes.

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Set up a Wikipedia Pageviews connector in Airbyte

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

Set up Starburst Galaxy for your extracted Wikipedia Pageviews data

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

Configure the Wikipedia Pageviews to Starburst Galaxy 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.

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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 Wikipedia Pageviews as a source connector (using Auth, or usually an API key)
  2. set up Starburst Galaxy 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 Wikipedia Pageviews

Page view statistics is a tool that is entirely available for Wikipedia pages, that helps to see how many people have visited an article during a given time period. Using Wikipedia Pageviews there are some limitations. There are many things which need to be considered before using such statistics to make conclusions about an ongoing discussion. There are also some software limitations and circumstances that may influence them, both from inside and outside Wikipedia. For aggregating per project and per project per country, a Pageview statistics are available.

What is Starburst Galaxy

Starburst Data is a data access and analytics company that offers a cloud-native, SQL-based query engine called Presto. Their mission is to enable organizations to access and analyze data across various sources efficiently and at scale. Starburst Data provides an enterprise-grade platform that leverages the power of Presto to query data residing in different databases, data lakes, and cloud storage systems, eliminating data silos and accelerating insights. With a focus on performance, security, and ease of use, Starburst Data empowers businesses to unlock the value of their data, enabling faster decision-making and advanced analytics capabilities.

Integrate Wikipedia Pageviews with Starburst Galaxy in minutes

Try for free now

Prerequisites

  1. A Wikipedia Pageviews account to transfer your customer data automatically from.
  2. A Starburst Galaxy 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 Wikipedia Pageviews and Starburst Galaxy, for seamless data migration.

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

Step 1: Set up Wikipedia Pageviews as a source connector

1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "Add Source" button and select "Wikipedia Pageviews" from the list of available connectors.
3. In the "Configuration" tab, enter the required credentials for your Wikipedia account, including the username and password.
4. Select the language and project for which you want to retrieve pageviews data.
5. Choose the date range for which you want to retrieve data, either by selecting a preset range or by entering custom start and end dates.
6. Click on the "Test" button to ensure that the connection is successful and that data is being retrieved.
7. Once the test is successful, click on the "Save" button to save the configuration and add the Wikipedia Pageviews source to your Airbyte workspace.
8. You can now use this source to create a pipeline and extract data from Wikipedia Pageviews.

Step 2: Set up Starburst Galaxy as a destination connector

1. First, navigate to the connectors page on Airbyte and select the Starburst Galaxy destination connector.
2. Next, enter the required credentials for your Starburst Galaxy account, including the host, port, database name, username, and password.
3. Once you have entered your credentials, click on the "Test Connection" button to ensure that the connection is successful.
4. If the connection is successful, you can then configure the settings for your destination connector, including the table name, schema, and any additional options.
5. After configuring your settings, you can then run a sync to transfer data from your source connector to your Starburst Galaxy destination.
6. You can monitor the progress of your sync and view any errors or warnings that may occur during the transfer process.
7. Once the sync is complete, you can then view your data in your Starburst Galaxy database and use it for analysis or other purposes.

Step 3: Set up a connection to sync your Wikipedia Pageviews data to Starburst Galaxy

Once you've successfully connected Wikipedia Pageviews as a data source and Starburst Galaxy 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 Wikipedia Pageviews from the dropdown list of your configured sources.
  3. Select your destination: Choose Starburst Galaxy 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 Wikipedia Pageviews objects you want to import data from towards Starburst Galaxy. 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 Wikipedia Pageviews to Starburst Galaxy according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Starburst Galaxy data warehouse is always up-to-date with your Wikipedia Pageviews data.

Use Cases to transfer your Wikipedia Pageviews data to Starburst Galaxy

Integrating data from Wikipedia Pageviews to Starburst Galaxy provides several benefits. Here are a few use cases:

  1. Advanced Analytics: Starburst Galaxy’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Wikipedia Pageviews data, extracting insights that wouldn't be possible within Wikipedia Pageviews alone.
  2. Data Consolidation: If you're using multiple other sources along with Wikipedia Pageviews, syncing to Starburst Galaxy 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: Wikipedia Pageviews has limits on historical data. Syncing data to Starburst Galaxy allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: Starburst Galaxy provides robust data security features. Syncing Wikipedia Pageviews data to Starburst Galaxy ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: Starburst Galaxy can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Wikipedia Pageviews data.
  6. Data Science and Machine Learning: By having Wikipedia Pageviews data in Starburst Galaxy, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While Wikipedia Pageviews provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Starburst Galaxy, providing more advanced business intelligence options. If you have a Wikipedia Pageviews table that needs to be converted to a Starburst Galaxy table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a Wikipedia Pageviews account as an Airbyte data source connector.
  2. Configure Starburst Galaxy as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from Wikipedia Pageviews to Starburst Galaxy 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:

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Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
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Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
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How to Sync Wikipedia Pageviews to Starburst Galaxy Manually

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How to load data from Wikipedia Pageviews to Starburst Galaxy

Learn how to use Airbyte to synchronize your Wikipedia Pageviews data into Starburst Galaxy within minutes.

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 Wikipedia Pageviews as a source connector (using Auth, or usually an API key)
  2. set up Starburst Galaxy 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 Wikipedia Pageviews

Page view statistics is a tool that is entirely available for Wikipedia pages, that helps to see how many people have visited an article during a given time period. Using Wikipedia Pageviews there are some limitations. There are many things which need to be considered before using such statistics to make conclusions about an ongoing discussion. There are also some software limitations and circumstances that may influence them, both from inside and outside Wikipedia. For aggregating per project and per project per country, a Pageview statistics are available.

What is Starburst Galaxy

Starburst Data is a data access and analytics company that offers a cloud-native, SQL-based query engine called Presto. Their mission is to enable organizations to access and analyze data across various sources efficiently and at scale. Starburst Data provides an enterprise-grade platform that leverages the power of Presto to query data residing in different databases, data lakes, and cloud storage systems, eliminating data silos and accelerating insights. With a focus on performance, security, and ease of use, Starburst Data empowers businesses to unlock the value of their data, enabling faster decision-making and advanced analytics capabilities.

Integrate Wikipedia Pageviews with Starburst Galaxy in minutes

Try for free now

Prerequisites

  1. A Wikipedia Pageviews account to transfer your customer data automatically from.
  2. A Starburst Galaxy 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 Wikipedia Pageviews and Starburst Galaxy, for seamless data migration.

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

Step 1: Set up Wikipedia Pageviews as a source connector

1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "Add Source" button and select "Wikipedia Pageviews" from the list of available connectors.
3. In the "Configuration" tab, enter the required credentials for your Wikipedia account, including the username and password.
4. Select the language and project for which you want to retrieve pageviews data.
5. Choose the date range for which you want to retrieve data, either by selecting a preset range or by entering custom start and end dates.
6. Click on the "Test" button to ensure that the connection is successful and that data is being retrieved.
7. Once the test is successful, click on the "Save" button to save the configuration and add the Wikipedia Pageviews source to your Airbyte workspace.
8. You can now use this source to create a pipeline and extract data from Wikipedia Pageviews.

Step 2: Set up Starburst Galaxy as a destination connector

1. First, navigate to the connectors page on Airbyte and select the Starburst Galaxy destination connector.
2. Next, enter the required credentials for your Starburst Galaxy account, including the host, port, database name, username, and password.
3. Once you have entered your credentials, click on the "Test Connection" button to ensure that the connection is successful.
4. If the connection is successful, you can then configure the settings for your destination connector, including the table name, schema, and any additional options.
5. After configuring your settings, you can then run a sync to transfer data from your source connector to your Starburst Galaxy destination.
6. You can monitor the progress of your sync and view any errors or warnings that may occur during the transfer process.
7. Once the sync is complete, you can then view your data in your Starburst Galaxy database and use it for analysis or other purposes.

Step 3: Set up a connection to sync your Wikipedia Pageviews data to Starburst Galaxy

Once you've successfully connected Wikipedia Pageviews as a data source and Starburst Galaxy 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 Wikipedia Pageviews from the dropdown list of your configured sources.
  3. Select your destination: Choose Starburst Galaxy 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 Wikipedia Pageviews objects you want to import data from towards Starburst Galaxy. 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 Wikipedia Pageviews to Starburst Galaxy according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Starburst Galaxy data warehouse is always up-to-date with your Wikipedia Pageviews data.

Use Cases to transfer your Wikipedia Pageviews data to Starburst Galaxy

Integrating data from Wikipedia Pageviews to Starburst Galaxy provides several benefits. Here are a few use cases:

  1. Advanced Analytics: Starburst Galaxy’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Wikipedia Pageviews data, extracting insights that wouldn't be possible within Wikipedia Pageviews alone.
  2. Data Consolidation: If you're using multiple other sources along with Wikipedia Pageviews, syncing to Starburst Galaxy 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: Wikipedia Pageviews has limits on historical data. Syncing data to Starburst Galaxy allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: Starburst Galaxy provides robust data security features. Syncing Wikipedia Pageviews data to Starburst Galaxy ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: Starburst Galaxy can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Wikipedia Pageviews data.
  6. Data Science and Machine Learning: By having Wikipedia Pageviews data in Starburst Galaxy, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While Wikipedia Pageviews provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Starburst Galaxy, providing more advanced business intelligence options. If you have a Wikipedia Pageviews table that needs to be converted to a Starburst Galaxy table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a Wikipedia Pageviews account as an Airbyte data source connector.
  2. Configure Starburst Galaxy as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from Wikipedia Pageviews to Starburst Galaxy 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 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

Frequently Asked Questions

What data can you extract from Wikipedia Pageviews?

The Wikipedia Pageviews API provides access to various types of data related to the pageviews of Wikipedia articles. Some of the categories of data that can be accessed through this API are:  

1. Pageviews: The API provides access to the number of pageviews for a particular Wikipedia article over a specific time period.  
2. Language: The API allows users to filter the data by language, enabling them to retrieve pageviews for articles in a specific language.  
3. Device type: The API provides data on the type of device used to access the Wikipedia article, such as desktop, mobile, or tablet.  
4. Geographic location: The API allows users to filter the data by geographic location, enabling them to retrieve pageviews for articles in a specific country or region.  
5. Time period: The API provides data on pageviews over a specific time period, such as hourly, daily, weekly, or monthly.  
6. Referrer: The API provides data on the source of the pageview, such as whether it was from a search engine or a social media platform.  

Overall, the Wikipedia Pageviews API provides a wealth of data related to the popularity and usage of Wikipedia articles, which can be used for various research and analytical purposes.

What data can you transfer to Starburst Galaxy?

You can transfer a wide variety of data to Starburst Galaxy. 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 Wikipedia Pageviews to Starburst Galaxy?

The most prominent ETL tools to transfer data from Wikipedia Pageviews to Starburst Galaxy include:

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

These tools help in extracting data from Wikipedia Pageviews and various sources (APIs, databases, and more), transforming it efficiently, and loading it into Starburst Galaxy 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