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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
Reliability at every level
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- Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
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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.
Plaid is a technology platform that makes it possible for companies to develop digitally-enabled financial systems. It enables developers to build financial services and applications safely and easily for financial institutions of any size. Plaid powers many financial apps including Venmo, Betterment, Chime, and Dave, encrypting your data before sharing it with your chosen app to keep your connection secure.
RabbitMQ is an open-source message broker software that enables communication between different applications and systems. It acts as a mediator between the sender and receiver of messages, ensuring that messages are delivered reliably and efficiently. RabbitMQ uses a messaging protocol called Advanced Message Queuing Protocol (AMQP) to facilitate communication between different applications. It supports multiple messaging patterns such as point-to-point, publish-subscribe, and request-reply. RabbitMQ is highly scalable and can handle large volumes of messages, making it a popular choice for enterprise-level applications. It also provides features such as message routing, message persistence, and message acknowledgments to ensure reliable message delivery.
Plaid's API provides access to a wide range of financial data, including:
1. Account Information: Plaid's API allows access to account information such as account balances, transaction history, and account holder details.
2. Transactions: Plaid's API provides access to transaction data, including transaction amounts, dates, and descriptions.
3. Investments: Plaid's API allows access to investment account data, including holdings, transactions, and performance metrics.
4. Loans: Plaid's API provides access to loan account data, including loan balances, payment history, and interest rates.
5. Identity Verification: Plaid's API allows for identity verification through bank account information, including name, address, and account ownership.
6. Authentication: Plaid's API provides authentication services to verify account ownership and prevent fraud.
7. Payment Initiation: Plaid's API allows for payment initiation through bank accounts, enabling users to make payments directly from their accounts.
Overall, Plaid's API provides a comprehensive suite of financial data services that can be used by developers to build innovative financial applications and services.
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.
