Gainsight PX is a product experience platform that helps companies understand user behavior, drive product adoption, and improve user engagement through analytics and in-app guides.
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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 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.
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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.
1. Customer information: Gainsight's API allows you to extract data related to customer information such as their name, email address, phone number, and other contact details.
2. Customer health score: You can extract data related to the health score of your customers, which is a metric that measures the overall health of your customer relationships.
3. Customer feedback: Gainsight's API allows you to extract data related to customer feedback, including survey responses, comments, and other feedback.
4. Customer usage data: You can extract data related to how your customers are using your product or service, including usage patterns, feature adoption, and other usage metrics.
5. Customer engagement data: Gainsight's API allows you to extract data related to customer engagement, including email opens, clicks, and other engagement metrics.
6. Customer support data: You can extract data related to customer support interactions, including tickets, chat logs, and other support-related metrics.
7. Customer revenue data: Gainsight's API allows you to extract data related to customer revenue, including subscription details, contract information, and other revenue-related metrics.
8. Customer churn data: You can extract data related to customer churn, including churn rates, reasons for churn, and other churn-related metrics.
9. Customer segmentation data: Gainsight's API allows you to extract data related to customer segmentation, including how customers are grouped based on various criteria such as industry, company size, and other segmentation metrics.
10. Customer success data: You can extract data related to customer success, including how successful your customers are in achieving their goals and how your product or service is helping them achieve those goals.
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.
1. Customer information: Gainsight's API allows you to extract data related to customer information such as their name, email address, phone number, and other contact details.
2. Customer health score: You can extract data related to the health score of your customers, which is a metric that measures the overall health of your customer relationships.
3. Customer feedback: Gainsight's API allows you to extract data related to customer feedback, including survey responses, comments, and other feedback.
4. Customer usage data: You can extract data related to how your customers are using your product or service, including usage patterns, feature adoption, and other usage metrics.
5. Customer engagement data: Gainsight's API allows you to extract data related to customer engagement, including email opens, clicks, and other engagement metrics.
6. Customer support data: You can extract data related to customer support interactions, including tickets, chat logs, and other support-related metrics.
7. Customer revenue data: Gainsight's API allows you to extract data related to customer revenue, including subscription details, contract information, and other revenue-related metrics.
8. Customer churn data: You can extract data related to customer churn, including churn rates, reasons for churn, and other churn-related metrics.
9. Customer segmentation data: Gainsight's API allows you to extract data related to customer segmentation, including how customers are grouped based on various criteria such as industry, company size, and other segmentation metrics.
10. Customer success data: You can extract data related to customer success, including how successful your customers are in achieving their goals and how your product or service is helping them achieve those goals.
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.
1. Customer information: Gainsight's API allows you to extract data related to customer information such as their name, email address, phone number, and other contact details.
2. Customer health score: You can extract data related to the health score of your customers, which is a metric that measures the overall health of your customer relationships.
3. Customer feedback: Gainsight's API allows you to extract data related to customer feedback, including survey responses, comments, and other feedback.
4. Customer usage data: You can extract data related to how your customers are using your product or service, including usage patterns, feature adoption, and other usage metrics.
5. Customer engagement data: Gainsight's API allows you to extract data related to customer engagement, including email opens, clicks, and other engagement metrics.
6. Customer support data: You can extract data related to customer support interactions, including tickets, chat logs, and other support-related metrics.
7. Customer revenue data: Gainsight's API allows you to extract data related to customer revenue, including subscription details, contract information, and other revenue-related metrics.
8. Customer churn data: You can extract data related to customer churn, including churn rates, reasons for churn, and other churn-related metrics.
9. Customer segmentation data: Gainsight's API allows you to extract data related to customer segmentation, including how customers are grouped based on various criteria such as industry, company size, and other segmentation metrics.
10. Customer success data: You can extract data related to customer success, including how successful your customers are in achieving their goals and how your product or service is helping them achieve those goals.
1. First, navigate to the Gainsight source connector page on Airbyte.com.
2. Click on the "Create a new connection" button.
3. Enter a name for your connection and click "Next".
4. Enter your Gainsight API credentials, including your API key and API secret.
5. Click "Test connection" to ensure that your credentials are correct and that Airbyte can connect to your Gainsight account.
6. Once your connection is successful, select the data you want to replicate from Gainsight.
7. Choose the replication frequency and any other settings you want to apply to your connection.
8. Click "Create connection" to finalize your Gainsight source connector on Airbyte.com.
9. You can now view and manage your Gainsight connection from the Airbyte dashboard, including monitoring replication status and making any necessary changes to your connection settings.
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.
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