Genesys is a customer experience platform offering omnichannel communication, contact center solutions, and AI-driven insights to enhance customer service and operational efficiency.
Top companies trust Airbyte to centralize their Data
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
The Airbyte Open Data Movement Platform
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
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.
Fnatic, based out of London, is the world's leading esports organization, with a winning legacy of 16 years and counting in over 28 different titles, generating over 13m USD in prize money. Fnatic has an engaged follower base of 14m across their social media platforms and hundreds of millions of people watch their teams compete in League of Legends, CS:GO, Dota 2, Rainbow Six Siege, and many more titles every year.
Ready to get started?
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.
Genesys is a cloud-based customer experience platform that helps businesses improve their customer interactions across all channels, including voice, email, chat, and social media. The platform provides a range of tools and features, including intelligent routing, self-service options, and real-time analytics, to help businesses deliver personalized and efficient customer experiences. Genesys also offers integrations with popular CRM and marketing automation systems, as well as AI-powered chatbots and virtual assistants to automate routine tasks and improve customer engagement. With Genesys, businesses can streamline their customer service operations, reduce costs, and increase customer satisfaction.
Genesys's API provides access to a wide range of data related to customer interactions and contact center operations. The following are the categories of data that can be accessed through Genesys's API:
1. Customer data: This includes information about customers such as their name, contact details, and previous interactions with the contact center.
2. Interaction data: This includes data related to customer interactions such as call recordings, chat transcripts, and email conversations.
3. Agent data: This includes information about agents such as their availability, skills, and performance metrics.
4. Queue data: This includes data related to the queues in the contact center such as the number of calls waiting, average wait time, and service level.
5. Routing data: This includes data related to the routing of interactions such as the routing strategy, routing rules, and routing statistics.
6. Reporting data: This includes data related to contact center performance such as call volume, handle time, and customer satisfaction scores.
7. Configuration data: This includes data related to the configuration of the contact center such as the IVR menu, agent groups, and business hours.
Overall, Genesys's API provides access to a comprehensive set of data that can be used to improve customer experience, optimize contact center operations, and drive business outcomes.
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.
Genesys is a cloud-based customer experience platform that helps businesses improve their customer interactions across all channels, including voice, email, chat, and social media. The platform provides a range of tools and features, including intelligent routing, self-service options, and real-time analytics, to help businesses deliver personalized and efficient customer experiences. Genesys also offers integrations with popular CRM and marketing automation systems, as well as AI-powered chatbots and virtual assistants to automate routine tasks and improve customer engagement. With Genesys, businesses can streamline their customer service operations, reduce costs, and increase customer satisfaction.
Genesys's API provides access to a wide range of data related to customer interactions and contact center operations. The following are the categories of data that can be accessed through Genesys's API:
1. Customer data: This includes information about customers such as their name, contact details, and previous interactions with the contact center.
2. Interaction data: This includes data related to customer interactions such as call recordings, chat transcripts, and email conversations.
3. Agent data: This includes information about agents such as their availability, skills, and performance metrics.
4. Queue data: This includes data related to the queues in the contact center such as the number of calls waiting, average wait time, and service level.
5. Routing data: This includes data related to the routing of interactions such as the routing strategy, routing rules, and routing statistics.
6. Reporting data: This includes data related to contact center performance such as call volume, handle time, and customer satisfaction scores.
7. Configuration data: This includes data related to the configuration of the contact center such as the IVR menu, agent groups, and business hours.
Overall, Genesys's API provides access to a comprehensive set of data that can be used to improve customer experience, optimize contact center operations, and drive business outcomes.
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.
Genesys is a cloud-based customer experience platform that helps businesses improve their customer interactions across all channels, including voice, email, chat, and social media. The platform provides a range of tools and features, including intelligent routing, self-service options, and real-time analytics, to help businesses deliver personalized and efficient customer experiences. Genesys also offers integrations with popular CRM and marketing automation systems, as well as AI-powered chatbots and virtual assistants to automate routine tasks and improve customer engagement. With Genesys, businesses can streamline their customer service operations, reduce costs, and increase customer satisfaction.
Genesys's API provides access to a wide range of data related to customer interactions and contact center operations. The following are the categories of data that can be accessed through Genesys's API:
1. Customer data: This includes information about customers such as their name, contact details, and previous interactions with the contact center.
2. Interaction data: This includes data related to customer interactions such as call recordings, chat transcripts, and email conversations.
3. Agent data: This includes information about agents such as their availability, skills, and performance metrics.
4. Queue data: This includes data related to the queues in the contact center such as the number of calls waiting, average wait time, and service level.
5. Routing data: This includes data related to the routing of interactions such as the routing strategy, routing rules, and routing statistics.
6. Reporting data: This includes data related to contact center performance such as call volume, handle time, and customer satisfaction scores.
7. Configuration data: This includes data related to the configuration of the contact center such as the IVR menu, agent groups, and business hours.
Overall, Genesys's API provides access to a comprehensive set of data that can be used to improve customer experience, optimize contact center operations, and drive business outcomes.
1. First, navigate to the Airbyte website and create an account.
2. Once you have logged in, click on the ""Sources"" tab on the left-hand side of the screen.
3. Scroll down until you find the Genesys source connector and click on it.
4. You will be prompted to enter your Genesys API credentials. Enter these and click ""Test Connection"" to ensure that the credentials are correct.
5. Once the connection has been established, you can configure the connector to select the data you want to sync.
6. Choose the tables or data sources you want to sync and set any relevant filters or parameters.
7. Click ""Save"" to save your configuration.
8. You can now run a sync to start pulling data from your Genesys source into Airbyte.
9. Monitor the sync to ensure that it is running smoothly and troubleshoot any issues that arise.
10. Once the sync is complete, you can use Airbyte's destination connectors to send the data to your desired destination.
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.
.svg)
.svg)
