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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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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.
Paystack is a payment gateway that allows businesses to accept payments from customers online. It provides a secure and easy-to-use platform for businesses to receive payments from customers using various payment methods such as debit/credit cards, bank transfers, and mobile money. Paystack also offers features such as automated invoicing, subscription billing, and fraud detection to help businesses manage their payments efficiently. With Paystack, businesses can easily integrate payment options into their websites or mobile apps, making it easier for customers to pay for products and services. Paystack is available in Nigeria and Ghana, and it has become a popular payment gateway for businesses in these countries.
Redis is an open-source, in-memory data structure store that can be used as a database, cache, and message broker. It supports a wide range of data structures such as strings, hashes, lists, sets, and sorted sets. Redis is known for its high performance, scalability, and flexibility. It can handle millions of requests per second and can be used in a variety of applications such as real-time analytics, messaging, and session management. Redis also provides advanced features such as pub/sub messaging, Lua scripting, and transactions. It is widely used by companies such as Twitter, GitHub, and StackOverflow.
Paystack's API provides access to a wide range of data related to payment processing and transactions. The following are the categories of data that Paystack's API gives access to:
1. Transactions: This includes data related to successful and failed transactions, such as transaction ID, amount, status, and date.
2. Customers: This includes data related to customers who have made transactions, such as customer ID, name, email, and phone number.
3. Banks: This includes data related to banks that are supported by Paystack, such as bank name, code, and country.
4. Cards: This includes data related to cards that have been used for transactions, such as card type, last four digits, and expiration date.
5. Subscriptions: This includes data related to recurring payments, such as subscription ID, amount, and frequency.
6. Disputes: This includes data related to disputes raised by customers, such as dispute ID, status, and reason.
7. Refunds: This includes data related to refunds issued to customers, such as refund ID, amount, and date.
Overall, Paystack's API provides comprehensive access to data related to payment processing and transactions, enabling businesses to manage their payments more effectively.
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.
