WorkRamp is an all-in-one learning platform that enables organizations to train employees, customers, and partners effectively, enhancing skills and driving growth.
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.
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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.
WorkRamp is the leading unified training and learning Platform built for the modern enterprise that your employees, customers, and partners will love. WorkRamp assist you cross-pollinate content and resources across teams to save time & money, grow revenue performance. WorkRamp continuously seeks to upgrade their platform and listens profoundly to their customers. WorkRamp advances learning and teaching as a growth engine for your business with a maleable platform which empowers teams to promote top talent, exceed revenue targets.
Workramp's API provides access to a wide range of data related to employee training and development. The following are the categories of data that can be accessed through Workramp's API:
1. User data: This includes information about individual users, such as their name, email address, and job title.
2. Course data: This includes information about the courses available on Workramp, such as the course name, description, and duration.
3. Assessment data: This includes information about the assessments available on Workramp, such as the assessment name, description, and passing score.
4. Progress data: This includes information about the progress of individual users in completing courses and assessments, such as the percentage of the course completed and the score achieved on an assessment.
5. Certification data: This includes information about the certifications earned by individual users, such as the certification name, date earned, and expiration date.
6. Analytics data: This includes information about the usage of Workramp, such as the number of users, courses completed, and assessments passed.
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.
WorkRamp is the leading unified training and learning Platform built for the modern enterprise that your employees, customers, and partners will love. WorkRamp assist you cross-pollinate content and resources across teams to save time & money, grow revenue performance. WorkRamp continuously seeks to upgrade their platform and listens profoundly to their customers. WorkRamp advances learning and teaching as a growth engine for your business with a maleable platform which empowers teams to promote top talent, exceed revenue targets.
Workramp's API provides access to a wide range of data related to employee training and development. The following are the categories of data that can be accessed through Workramp's API:
1. User data: This includes information about individual users, such as their name, email address, and job title.
2. Course data: This includes information about the courses available on Workramp, such as the course name, description, and duration.
3. Assessment data: This includes information about the assessments available on Workramp, such as the assessment name, description, and passing score.
4. Progress data: This includes information about the progress of individual users in completing courses and assessments, such as the percentage of the course completed and the score achieved on an assessment.
5. Certification data: This includes information about the certifications earned by individual users, such as the certification name, date earned, and expiration date.
6. Analytics data: This includes information about the usage of Workramp, such as the number of users, courses completed, and assessments passed.
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.
WorkRamp is the leading unified training and learning Platform built for the modern enterprise that your employees, customers, and partners will love. WorkRamp assist you cross-pollinate content and resources across teams to save time & money, grow revenue performance. WorkRamp continuously seeks to upgrade their platform and listens profoundly to their customers. WorkRamp advances learning and teaching as a growth engine for your business with a maleable platform which empowers teams to promote top talent, exceed revenue targets.
Workramp's API provides access to a wide range of data related to employee training and development. The following are the categories of data that can be accessed through Workramp's API:
1. User data: This includes information about individual users, such as their name, email address, and job title.
2. Course data: This includes information about the courses available on Workramp, such as the course name, description, and duration.
3. Assessment data: This includes information about the assessments available on Workramp, such as the assessment name, description, and passing score.
4. Progress data: This includes information about the progress of individual users in completing courses and assessments, such as the percentage of the course completed and the score achieved on an assessment.
5. Certification data: This includes information about the certifications earned by individual users, such as the certification name, date earned, and expiration date.
6. Analytics data: This includes information about the usage of Workramp, such as the number of users, courses completed, and assessments passed.
1. First, navigate to the Workramp source connector page on Airbyte.com.
2. Click on the "Create new connection" button.
3. Enter a name for your connection and click "Next".
4. Enter your Workramp API key and subdomain in the appropriate fields.
5. Click "Test connection" to ensure that your credentials are correct and the connection is successful.
6. Once the connection is successful, click "Next".
7. Select the tables you want to replicate from Workramp to Airbyte.
8. Choose the replication frequency and the initial sync mode.
9. Click "Create connection" to finalize the setup.
10. Your Workramp source connector is now connected to Airbyte and ready to replicate data.
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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