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- Automated schema change handling, data normalization and more
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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.
Oura is a purpose to develop the way we live our lives. Oura helps us to understand our body completely. It’s a symbol of how much our life has changed. Oura takes data privacy seriously. We only use your data to power your experience and deliver your individual insights. We never sell your data to third parties or use your data to sell advertising to other companies. Oura makes a ring that tracks your health stats and aims to help you sleep better.
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.
Oura's API provides access to a wide range of data related to sleep, activity, and readiness. The following are the categories of data that can be accessed through the API:
1. Sleep data: This includes information about the duration and quality of sleep, as well as the different stages of sleep (REM, deep, light).
2. Activity data: This includes information about the number of steps taken, calories burned, and active time.
3. Readiness data: This includes information about the body's readiness for physical activity, based on factors such as heart rate variability, resting heart rate, and body temperature.
4. Recovery data: This includes information about the body's recovery from physical activity, based on factors such as heart rate variability and resting heart rate.
5. Body data: This includes information about the body's physical state, such as weight, body temperature, and respiratory rate.
6. Trends data: This includes information about how the body's sleep, activity, and readiness levels have changed over time, allowing for long-term analysis and tracking.
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.
