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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.
Taking the customer relationship management (CRM) platform up a notch, Zendesk Sunshine makes it possible for businesses to connect the dots to build the full picture of their customer from data anywhere. Offering much more than the old legacy CRM platform, Zendesk Sunshine takes a new and more modern approach, native to AWS, that provides the tools needed for developers and admins to create superior customer experiences.
Zendesk Sunshine's API provides access to a wide range of data categories, including:
1. Customer data: This includes information about customers such as their name, email address, phone number, and other contact details.
2. Ticket data: This includes information about customer support tickets, such as the status of the ticket, the customer's issue, and any notes or comments added by support agents.
3. Agent data: This includes information about support agents, such as their name, email address, and performance metrics.
4. Analytics data: This includes data about customer support performance, such as response times, ticket volume, and customer satisfaction ratings.
5. Integration data: This includes data about integrations with other systems, such as CRM or marketing automation platforms.
6. Custom data: This includes any custom data fields that have been added to the Zendesk platform, such as customer preferences or product information.
Overall, Zendesk Sunshine's API provides access to a wide range of data that can be used to improve customer support performance, gain insights into customer behavior, and integrate with other systems for a more seamless 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 should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
