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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 300+ 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 connector builder.
Configure the connection in Airbyte
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
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
Airbyte Enterprise
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.
Talkdesk Explore is an leading business brilliance tool, supported with Talkdesk IQ and built with various customizable reports. Talkdesk provides a full portfolio of contact center automation tools as part of its and reporting builder. Talkdesk Explore is one kinds of reporting tool that permits you more performance and flexibility to manage your historical data. It is also a business analytics tool that features flexible filtering, scheduling, and customization options for a 360-degree view.
TalkDesk Explore's API provides access to a wide range of data related to customer interactions and contact center performance. The following are the categories of data that can be accessed through the API:
1. Agent Performance: This category includes data related to the performance of individual agents, such as their call volume, average handle time, and customer satisfaction ratings.
2. Call Metrics: This category includes data related to the calls made and received by the contact center, such as call volume, call duration, and call outcome.
3. Customer Experience: This category includes data related to the customer experience, such as customer satisfaction ratings, customer feedback, and customer demographics.
4. Queue Metrics: This category includes data related to the performance of the contact center queues, such as queue volume, wait time, and abandonment rate.
5. Service Level: This category includes data related to the contact center's service level, such as the percentage of calls answered within a certain time frame.
6. Team Performance: This category includes data related to the performance of teams within the contact center, such as team call volume, team handle time, and team customer satisfaction ratings.
Overall, TalkDesk Explore's API provides a comprehensive set of data that can be used to analyze and optimize contact center performance and improve the customer experience.
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.
Talkdesk Explore is an leading business brilliance tool, supported with Talkdesk IQ and built with various customizable reports. Talkdesk provides a full portfolio of contact center automation tools as part of its and reporting builder. Talkdesk Explore is one kinds of reporting tool that permits you more performance and flexibility to manage your historical data. It is also a business analytics tool that features flexible filtering, scheduling, and customization options for a 360-degree view.
TalkDesk Explore's API provides access to a wide range of data related to customer interactions and contact center performance. The following are the categories of data that can be accessed through the API:
1. Agent Performance: This category includes data related to the performance of individual agents, such as their call volume, average handle time, and customer satisfaction ratings.
2. Call Metrics: This category includes data related to the calls made and received by the contact center, such as call volume, call duration, and call outcome.
3. Customer Experience: This category includes data related to the customer experience, such as customer satisfaction ratings, customer feedback, and customer demographics.
4. Queue Metrics: This category includes data related to the performance of the contact center queues, such as queue volume, wait time, and abandonment rate.
5. Service Level: This category includes data related to the contact center's service level, such as the percentage of calls answered within a certain time frame.
6. Team Performance: This category includes data related to the performance of teams within the contact center, such as team call volume, team handle time, and team customer satisfaction ratings.
Overall, TalkDesk Explore's API provides a comprehensive set of data that can be used to analyze and optimize contact center performance and improve the customer experience.
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.
Talkdesk Explore is an leading business brilliance tool, supported with Talkdesk IQ and built with various customizable reports. Talkdesk provides a full portfolio of contact center automation tools as part of its and reporting builder. Talkdesk Explore is one kinds of reporting tool that permits you more performance and flexibility to manage your historical data. It is also a business analytics tool that features flexible filtering, scheduling, and customization options for a 360-degree view.
TalkDesk Explore's API provides access to a wide range of data related to customer interactions and contact center performance. The following are the categories of data that can be accessed through the API:
1. Agent Performance: This category includes data related to the performance of individual agents, such as their call volume, average handle time, and customer satisfaction ratings.
2. Call Metrics: This category includes data related to the calls made and received by the contact center, such as call volume, call duration, and call outcome.
3. Customer Experience: This category includes data related to the customer experience, such as customer satisfaction ratings, customer feedback, and customer demographics.
4. Queue Metrics: This category includes data related to the performance of the contact center queues, such as queue volume, wait time, and abandonment rate.
5. Service Level: This category includes data related to the contact center's service level, such as the percentage of calls answered within a certain time frame.
6. Team Performance: This category includes data related to the performance of teams within the contact center, such as team call volume, team handle time, and team customer satisfaction ratings.
Overall, TalkDesk Explore's API provides a comprehensive set of data that can be used to analyze and optimize contact center performance and improve the customer experience.
1. First, navigate to the TalkDesk Explore source connector page on Airbyte.com.
2. Click on the "Configure Source" button to begin setting up the connector.
3. In the "Connection Configuration" section, enter the required credentials for your TalkDesk Explore account, including the API key and API secret.
4. Once the credentials have been entered, click on the "Check Connection" button to ensure that the connection is successful.
5. In the "Sync Configuration" section, select the tables and columns that you want to sync from TalkDesk Explore to Airbyte.
6. Choose the frequency at which you want the data to be synced, and set any other relevant options.
7. Click on the "Save & Test" button to save your configuration and test the connection.
8. If the test is successful, you can then activate the connector to begin syncing data from TalkDesk Explore to Airbyte.
9. You can monitor the progress of the sync in the "Jobs" section of the Airbyte dashboard, and view the synced data in the "Destinations" section.
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.