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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.
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.
Set up a source connector to extract data from in Airbyte
Choose from one of 400 sources where you want to import data from. This can be any API tool, cloud data warehouse, database, data lake, files, among other source types. You can even build your own source connector in minutes with our no-code no-code connector builder.
Configure the connection in Airbyte
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The only open solution empowering data teams to meet growing business demands in the new AI era.
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Move large volumes, fast.
Change Data Capture.
Security from source to destination.
We support the CDC methods your company needs
Log-based CDC
Timestamp-based CDC
Airbyte Open Source
Airbyte Cloud
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Why choose Airbyte as the backbone of your data infrastructure?
Keep your data engineering costs in check
Get Airbyte hosted where you need it to be
- Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
- Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.
White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of sources, including API tools, cloud data warehouses, lakes, databases, and files, or even custom sources you can build.
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FAQs
What is ETL?
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.
1. Call logs: The API allows you to extract call logs, including the date and time of the call, the duration, the caller ID, and the call type (incoming or outgoing).
2. Voicemail: You can extract voicemail messages, including the date and time of the message, the caller ID, and the duration of the message.
3. Contacts: The API allows you to extract contact information, including the name, phone number, email address, and other relevant details.
4. Call recordings: You can extract call recordings, including the date and time of the call, the duration, and the audio file.
5. User information: The API allows you to extract user information, including the user's name, email address, phone number, and other relevant details.
6. Analytics: You can extract analytics data, including call volume, call duration, call type, and other relevant metrics.
7. Call routing: The API allows you to extract call routing information, including the rules and settings for call routing.
8. Messaging: You can extract messaging data, including the date and time of the message, the sender and recipient, and the message content.
9. Presence: The API allows you to extract presence information, including the user's availability status and location.
10. Call center data: You can extract call center data, including call queue information, agent performance metrics, and other relevant data.
What is ELT?
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.
Difference between ETL and ELT?
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.
What is ETL?
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.
1. Call logs: The API allows you to extract call logs, including the date and time of the call, the duration, the caller ID, and the call type (incoming or outgoing).
2. Voicemail: You can extract voicemail messages, including the date and time of the message, the caller ID, and the duration of the message.
3. Contacts: The API allows you to extract contact information, including the name, phone number, email address, and other relevant details.
4. Call recordings: You can extract call recordings, including the date and time of the call, the duration, and the audio file.
5. User information: The API allows you to extract user information, including the user's name, email address, phone number, and other relevant details.
6. Analytics: You can extract analytics data, including call volume, call duration, call type, and other relevant metrics.
7. Call routing: The API allows you to extract call routing information, including the rules and settings for call routing.
8. Messaging: You can extract messaging data, including the date and time of the message, the sender and recipient, and the message content.
9. Presence: The API allows you to extract presence information, including the user's availability status and location.
10. Call center data: You can extract call center data, including call queue information, agent performance metrics, and other relevant data.
What is ELT?
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.
Difference between ETL and ELT?
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.
What is ETL?
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.
1. Call logs: The API allows you to extract call logs, including the date and time of the call, the duration, the caller ID, and the call type (incoming or outgoing).
2. Voicemail: You can extract voicemail messages, including the date and time of the message, the caller ID, and the duration of the message.
3. Contacts: The API allows you to extract contact information, including the name, phone number, email address, and other relevant details.
4. Call recordings: You can extract call recordings, including the date and time of the call, the duration, and the audio file.
5. User information: The API allows you to extract user information, including the user's name, email address, phone number, and other relevant details.
6. Analytics: You can extract analytics data, including call volume, call duration, call type, and other relevant metrics.
7. Call routing: The API allows you to extract call routing information, including the rules and settings for call routing.
8. Messaging: You can extract messaging data, including the date and time of the message, the sender and recipient, and the message content.
9. Presence: The API allows you to extract presence information, including the user's availability status and location.
10. Call center data: You can extract call center data, including call queue information, agent performance metrics, and other relevant data.
1. Open the Dialpad source connector page on Airbyte.com.
2. Click on the "Create new connection" button.
3. Enter a name for your connection.
4. Enter your Dialpad API credentials, including your API key and API secret.
5. Click on the "Test" button to ensure that your credentials are correct.
6. Select the data you want to replicate from Dialpad, such as call logs or voicemails.
7. Choose the frequency at which you want your data to be replicated.
8. Click on the "Create connection" button to save your settings and start replicating your data.
It is important to note that the specific steps may vary depending on the version of Airbyte and Dialpad you are using. For more detailed instructions, refer to the documentation provided by Airbyte and Dialpad.
What is ELT?
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.
Difference between ETL and ELT?
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.
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