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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.
Zendesk Talk is a cloud-based Voice over Internet Protocol (VoIP) system that enables phone communication for customer support teams from within the Zendesk support ticketing solution. Yet another way Zendesk successfully heightens the customer experience, Zendesk Talk offers the capability to access phone numbers in more than 40 countries, making global communication personal.
Zendesk Talk's API provides access to various types of data related to customer support and communication. The categories of data that can be accessed through the API are:
1. Call data: This includes information about incoming and outgoing calls, such as call duration, call recordings, and call transcripts.
2. Agent data: This includes information about agents, such as their availability, status, and performance metrics.
3. Ticket data: This includes information about support tickets, such as ticket status, priority, and customer information.
4. Voicemail data: This includes information about voicemails, such as voicemail transcripts and recordings.
5. Queue data: This includes information about call queues, such as queue status, wait times, and queue metrics.
6. Call routing data: This includes information about call routing, such as routing rules, routing history, and routing performance metrics.
7. IVR data: This includes information about IVR (Interactive Voice Response) systems, such as IVR menus, IVR prompts, and IVR performance metrics.
Overall, Zendesk Talk's API provides a comprehensive set of data that can be used to analyze and improve customer support and communication processes.
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.
Zendesk Talk is a cloud-based Voice over Internet Protocol (VoIP) system that enables phone communication for customer support teams from within the Zendesk support ticketing solution. Yet another way Zendesk successfully heightens the customer experience, Zendesk Talk offers the capability to access phone numbers in more than 40 countries, making global communication personal.
A fully managed data warehouse service in the Amazon Web Services (AWS) cloud, Amazon Redshift is designed for storage and analysis of large-scale datasets. Redshift allows businesses to scale from a few hundred gigabytes to more than a petabyte (a million gigabytes), and utilizes ML techniques to analyze queries, offering businesses new insights from their data. Users can query and combine exabytes of data using standard SQL, and easily save their query results to their S3 data lake.
1. First, you need to obtain your Zendesk Talk API credentials. You can do this by logging in to your Zendesk account and navigating to the Admin settings. From there, select the API option and generate a new API token. Make sure to copy the token as you will need it later.
2. Next, open the Airbyte platform and navigate to the Sources tab. Click on the "Create a new Source" button and select the Zendesk Talk connector from the list of available connectors.
3. In the configuration page, you will be prompted to enter your Zendesk Talk API credentials. Paste the API token you copied earlier into the appropriate field.
4. You will also need to enter the subdomain of your Zendesk account. This is the part of your Zendesk URL that comes before ".zendesk.com". For example, if your Zendesk URL is "https://example.zendesk.com", your subdomain would be "example".
5. Once you have entered your credentials, click on the "Check Connection" button to ensure that Airbyte can successfully connect to your Zendesk Talk account.
6. If the connection is successful, you can proceed to configure the specific data you want to sync from Zendesk Talk to Airbyte. This can include call logs, recordings, and other relevant data.
7. Finally, save your configuration and run your first sync to start pulling data from Zendesk Talk into Airbyte. You can schedule regular syncs to keep your data up-to-date and ensure that your analytics and reporting are accurate.
1. First, log in to your Airbyte account and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Click on the "Add Destination" button and select "Redshift" from the list of available connectors.
3. Enter your Redshift database credentials, including the host, port, database name, username, and password.
4. Choose the schema you want to use for your data in Redshift.
5. Select the tables you want to sync from your source connector to Redshift.
6. Map the fields from your source connector to the corresponding fields in Redshift.
7. Choose the sync mode you want to use, either "append" or "replace."
8. Set up any additional options or filters you want to use for your sync.
9. Test your connection to ensure that your data is syncing correctly.
10. Once you are satisfied with your settings, save your configuration and start your sync.
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:
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
Ready to get started?
Frequently Asked Questions
Zendesk Talk's API provides access to various types of data related to customer support and communication. The categories of data that can be accessed through the API are:
1. Call data: This includes information about incoming and outgoing calls, such as call duration, call recordings, and call transcripts.
2. Agent data: This includes information about agents, such as their availability, status, and performance metrics.
3. Ticket data: This includes information about support tickets, such as ticket status, priority, and customer information.
4. Voicemail data: This includes information about voicemails, such as voicemail transcripts and recordings.
5. Queue data: This includes information about call queues, such as queue status, wait times, and queue metrics.
6. Call routing data: This includes information about call routing, such as routing rules, routing history, and routing performance metrics.
7. IVR data: This includes information about IVR (Interactive Voice Response) systems, such as IVR menus, IVR prompts, and IVR performance metrics.
Overall, Zendesk Talk's API provides a comprehensive set of data that can be used to analyze and improve customer support and communication processes.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: