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- Automated schema change handling, data normalization and more
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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.
Google Analytics is a web service that provides integrated analytical tools and essential statistics to aid companies in understanding data and performing search engine optimization (SEO) to improve marketing. Google Analytics provides a range of free marketing tools that help businesses track their website performance and gather insights from visitors. Analytics’ integration with other Google solutions like Google’s advertising and publishing products promotes a seamless workflow that saves time and increases efficiency and insights.
Elasticsearch is a powerful search and analytics engine that is designed to handle large amounts of data in real-time. It is an open-source, distributed, and scalable search engine that is built on top of the Apache Lucene search library. Elasticsearch is used to search, analyze, and visualize data in real-time, making it an ideal tool for businesses and organizations that need to process large amounts of data quickly. Elasticsearch is designed to be highly scalable and can be used to index and search data across multiple servers. It is also highly customizable, allowing users to configure it to meet their specific needs. Elasticsearch is commonly used for log analysis, full-text search, and business analytics. One of the key features of Elasticsearch is its ability to handle unstructured data, such as text, images, and videos. It uses a powerful search algorithm to analyze and index this data, making it easy to search and retrieve information quickly. Elasticsearch also supports a wide range of data formats, including JSON, CSV, and XML, making it easy to integrate with other data sources. Overall, Elasticsearch is a powerful tool that can help businesses and organizations to process and analyze large amounts of data quickly and efficiently.
Google Analytics API provides access to a wide range of data related to website traffic and user behavior. The following are the categories of data that can be accessed through the API:
1. Audience data: This includes information about the demographics, interests, and behavior of website visitors.
2. Acquisition data: This includes data related to how visitors are finding the website, such as through search engines, social media, or referral links.
3. Behavior data: This includes data related to how visitors are interacting with the website, such as which pages they are visiting, how long they are staying on the site, and which actions they are taking.
4. Conversion data: This includes data related to the goals and conversions on the website, such as the number of purchases, form submissions, or other desired actions.
5. E-commerce data: This includes data related to online sales, such as revenue, average order value, and product performance.
6. Real-time data: This includes data related to the current activity on the website, such as the number of active users and the pages they are currently viewing.
Overall, the Google Analytics API provides a wealth of data that can be used to gain insights into website performance and user behavior.
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.
