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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.
An open-source database management system for online analytical processing (OLAP), ClickHouse takes the innovative approach of using a column-based database. It is easy to use right out of the box and is touted as being hardware efficient, extremely reliable, linearly scalable, and “blazing fast”—between 100-1,000x faster than traditional databases that write rows of data to the disk—allowing analytical data reports to be generated in real-time.
MongoDB is a database that powers crucial applications and systems for global businesses. Designed for developers and specializing in the areas of open source, software development, and databases, it offers functionality such as horizontal scaling, automatic failover, and the capability to assign data to a location.
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.