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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.
Freshdesk is a service provided by Freshworks for handling the entire spectrum of customer engagement. A customer support software based in the Cloud, Freshdesk provides a scalable solution for managing customer support simply and efficiently. Freshdesk enables teams to track incoming tickets from a variety of channels; provide support across multiple platforms including phone, chat, and other messaging apps; categorize, prioritize, and assign tickets; prepare preformatted answer to common customer support questions; and much more.
Freshdesk's API provides access to a wide range of data related to customer support and service management. The following are the categories of data that can be accessed through Freshdesk's API:
1. Tickets: Information related to customer support tickets, including ticket ID, status, priority, and requester details.
2. Contacts: Data related to customer contacts, including contact ID, name, email address, and phone number.
3. Agents: Information about support agents, including agent ID, name, email address, and role.
4. Companies: Data related to companies that use Freshdesk for customer support, including company ID, name, and domain.
5. Conversations: Information related to customer conversations, including conversation ID, status, and participants.
6. Knowledge base: Data related to the knowledge base, including articles, categories, and folders.
7. Surveys: Information related to customer satisfaction surveys, including survey ID, status, and responses.
8. Time entries: Data related to time entries for support agents, including time spent on tickets and activities.
9. Custom fields: Information related to custom fields created in Freshdesk, including field ID, name, and value.
Overall, Freshdesk's API provides access to a comprehensive set of data that can be used to improve customer support and service management.
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.
Freshdesk is a service provided by Freshworks for handling the entire spectrum of customer engagement. A customer support software based in the Cloud, Freshdesk provides a scalable solution for managing customer support simply and efficiently. Freshdesk enables teams to track incoming tickets from a variety of channels; provide support across multiple platforms including phone, chat, and other messaging apps; categorize, prioritize, and assign tickets; prepare preformatted answer to common customer support questions; and much more.
DuckDB is an in-process SQL OLAP database management system. It has strong support for SQL. DuckDB is borrowing the SQLite shell implementation. Each database is a single file on disk. It’s analogous to “ SQLite for analytical (OLAP) workloads” (direct comparison on the SQLite vs DuckDB paper here), whereas SQLite is for OLTP ones. But it can handle vast amounts of data locally. It’s the smaller, lighter version of Apache Druid and other OLAP technologies.
1. Open the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.
2. Click on the "Add Source" button and select "Freshdesk" from the list of available connectors.
3. Enter a name for the connector and click on "Next".
4. Enter your Freshdesk credentials, including your Freshdesk domain, API key, and password.
5. Click on "Test Connection" to ensure that the credentials are correct and the connection is successful.
6. Once the connection is successful, select the data you want to replicate from Freshdesk, including tickets, contacts, and companies.
7. Choose the replication frequency and the destination where you want to store the data.
8. Click on "Create Source" to save the configuration and start the replication process.
9. Monitor the replication process on the Airbyte dashboard and troubleshoot any errors that may occur.
10. Once the replication is complete, you can use the data in your destination of choice for analysis and reporting.
1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Click on the "Add Destination" button located in the top right corner of the screen.
3. Scroll down the list of available destinations until you find "DuckDB" and click on it.
4. Fill in the required information for your DuckDB database, including the host, port, database name, username, and password.
5. Test the connection to ensure that the information you provided is correct and that Airbyte can successfully connect to your DuckDB database.
6. If the connection is successful, click on the "Save" button to save your DuckDB destination connector.
7. You can now use this connector to transfer data from your source connectors to your DuckDB database. Simply select the DuckDB destination connector when setting up your data integration pipelines in Airbyte.
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
Freshdesk's API provides access to a wide range of data related to customer support and service management. The following are the categories of data that can be accessed through Freshdesk's API:
1. Tickets: Information related to customer support tickets, including ticket ID, status, priority, and requester details.
2. Contacts: Data related to customer contacts, including contact ID, name, email address, and phone number.
3. Agents: Information about support agents, including agent ID, name, email address, and role.
4. Companies: Data related to companies that use Freshdesk for customer support, including company ID, name, and domain.
5. Conversations: Information related to customer conversations, including conversation ID, status, and participants.
6. Knowledge base: Data related to the knowledge base, including articles, categories, and folders.
7. Surveys: Information related to customer satisfaction surveys, including survey ID, status, and responses.
8. Time entries: Data related to time entries for support agents, including time spent on tickets and activities.
9. Custom fields: Information related to custom fields created in Freshdesk, including field ID, name, and value.
Overall, Freshdesk's API provides access to a comprehensive set of data that can be used to improve customer support and service management.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: