Top companies trust Airbyte to centralize their Data
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Select your source
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Select your destination
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Sync your Data
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
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Cover your custom needs with our extensibility
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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
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Reliability at every level
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Airbyte Open Source
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Airbyte Cloud
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Airbyte Enterprise
Why choose Airbyte as the backbone of your data infrastructure?
Keep your data engineering costs in check
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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.
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White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
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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.
Dixa is the customer service platform that has everything you need for connected experiences. Dixa is also a conversational customer engagement software that connects brands with customers through real-time communication. It is The Customer Friendship Platform that helps brands to build stronger bonds with their customers and eliminate bad customer service through unifying all communication channels and customer data in one platform. Dixa is a rapid growing multichannel customer service software which provides the best experience for agents and customers alike.
Dixa's API provides access to a wide range of data related to customer interactions and support activities. The following are the categories of data that can be accessed through Dixa's API:
1. Conversations: This includes data related to customer conversations such as chat transcripts, call recordings, and email threads.
2. Customers: This includes data related to customer profiles such as contact information, purchase history, and preferences.
3. Agents: This includes data related to agent profiles such as performance metrics, availability, and skills.
4. Tickets: This includes data related to support tickets such as status, priority, and resolution time.
5. Analytics: This includes data related to performance metrics such as response time, resolution rate, and customer satisfaction.
6. Integrations: This includes data related to third-party integrations such as CRM systems, marketing automation tools, and payment gateways.
Overall, Dixa's API provides a comprehensive set of data that can be used to improve customer support operations and enhance the customer 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.