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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.
ChartMogul is an analytics platform to assist you run your subscription business. You get a complete overview of your global subscriber base; MRR, ARPU, ASP, churn and LTV are presented in a beautiful and easy to use dashboard. ChartMogul is a real time reporting and analytics solution for subscription businesses who use Stripe, PayPal, Chargify, Braintree, or Recurly. ChartMogul is an analytics platform to assist you run your subscription business. ChartMogul is a subscription analytics tool that provides real-time reporting on the most critical metrics.
CSV (Comma Separated Values) file is a tool used to store and exchange data in a simple and structured format. It is a plain text file that contains data separated by commas, where each line represents a record and each field is separated by a comma. CSV files are widely used in data analysis, data migration, and data exchange between different software applications. The CSV file format is easy to read and write, making it a popular choice for storing and exchanging data. It can be opened and edited using any text editor or spreadsheet software, such as Microsoft Excel or Google Sheets. CSV files can also be imported and exported from databases, making it a convenient tool for data management. CSV files are commonly used for storing large amounts of data, such as customer information, product catalogs, financial data, and scientific data. They are also used for data analysis and visualization, as they can be easily imported into statistical software and other data analysis tools. Overall, the CSV file is a simple and versatile tool that is widely used for storing, exchanging, and analyzing data.
Chartmogul's API provides access to a wide range of data related to subscription businesses. The following are the categories of data that can be accessed through Chartmogul's API:
1. Customer data: This includes information about customers such as their name, email address, and billing information.
2. Subscription data: This includes information about the subscription plans that customers have signed up for, including the plan name, price, and billing frequency.
3. Revenue data: This includes information about the revenue generated by the subscription business, including monthly recurring revenue (MRR), annual recurring revenue (ARR), and total revenue.
4. Churn data: This includes information about customer churn, including the number of customers who have cancelled their subscriptions and the reasons for cancellation.
5. Usage data: This includes information about how customers are using the subscription service, including the number of logins, the amount of data used, and the features that are being used.
6. Financial data: This includes information about the financial performance of the subscription business, including expenses, profits, and cash flow.
Overall, Chartmogul's API provides a comprehensive set of data that can be used to analyze and optimize subscription businesses.
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.