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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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Why choose Airbyte as the backbone of your data infrastructure?
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.
White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
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.
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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.
Fullstory is a digital experience analytics platform that helps businesses understand how users interact with their websites and applications. It captures every user interaction, including clicks, scrolls, and keystrokes, and provides insights into user behavior, preferences, and pain points. Fullstory's features include session replay, which allows businesses to watch recordings of user sessions to identify issues and opportunities for improvement, as well as heatmaps, funnels, and conversion analytics. The platform also integrates with other tools such as Google Analytics and Salesforce to provide a comprehensive view of user behavior across the entire customer journey. Overall, Fullstory helps businesses optimize their digital experiences to improve customer satisfaction and drive business growth.
Google Pub/Sub is an asynchronous messaging service built to be both highly reliable and scalable. Based on a component of Google’s infrastructure, Pub/Sub offers the capabililty of sending more than 500 million messages (over 1 TB of data) per second.
Fullstory's API provides access to a wide range of data related to user behavior on a website or application. The following are the categories of data that can be accessed through Fullstory's API:
1. Session data: This includes information about user sessions, such as session ID, start and end time, and duration.
2. Page data: This includes data related to the pages that users visit, such as page URL, title, and referrer.
3. Event data: This includes data related to user interactions with the website or application, such as clicks, form submissions, and page scrolls.
4. User data: This includes data related to user attributes, such as user ID, email address, and location.
5. Device data: This includes data related to the devices that users are accessing the website or application from, such as device type, operating system, and browser.
6. Error data: This includes data related to errors that occur on the website or application, such as error messages and stack traces.
Overall, Fullstory's API provides a comprehensive set of data that can be used to gain insights into user behavior and improve the user 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.
