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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
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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
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Keep your data engineering costs in check
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- 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.
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Including for your Airbyte Open Source instance with our premium support.
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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.
The Okta Identity Cloud provides identification security for logins by enterprise employees. It simplifies the login process by making all of an individual’s logins across a company’s software applications the same. An Identity-as-a-Service (IDaaS), Okta ensures secure logins across multiple devices, including phone, tablet, desk computers and laptops. Okta offers a management systems for groups, devices, and applications, and allows the additions of applications to Workplace 365 for extreme versatility.
Amazon DynamoDB is a fully managed proprietary NoSQL database service that supports key–value and document data structures and is offered by Amazon.com as part of the Amazon Web Services portfolio. DynamoDB exposes a similar data model to and derives its name from Dynamo, but has a different underlying implementation.
Okta's API provides access to a wide range of data related to user authentication, authorization, and management. The following are the categories of data that can be accessed through Okta's API:
1. User data: This includes information about users such as their name, email address, phone number, and group membership.
2. Group data: This includes information about groups such as their name, description, and membership.
3. Application data: This includes information about applications such as their name, description, and configuration settings.
4. Authentication data: This includes information about authentication events such as successful and failed login attempts.
5. Authorization data: This includes information about access control policies and permissions.
6. Event data: This includes information about various events such as user creation, password reset, and group membership changes.
7. System data: This includes information about the Okta system itself such as its version, status, and configuration settings.
Overall, Okta's API provides a comprehensive set of data that can be used to manage and secure user access to various applications and resources.
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.
