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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.
ActiveCampaign lets us send email campaigns, automate features, and manage contacts by staff group. ActiveCampaign is a complete email marketing tool remaining advanced automation capabilities. Active Campaign has created several Campaign types to simplify your marketing automation. Using Standard, Automated, Auto Responder, Split Testing, RSS Triggered, and Date Based campaigns provide a variety of specialized options. ActiveCampaign is a customer experience automation (CXA) platform that assists businesses in meaningfully engaging customers.
TiDB is a distributed SQL database that is designed to handle large-scale online transaction processing (OLTP) and online analytical processing (OLAP) workloads. It is an open-source, cloud-native database that is built to be highly available, scalable, and fault-tolerant. TiDB uses a distributed architecture that allows it to scale horizontally across multiple nodes, while also providing strong consistency guarantees. It supports SQL and offers compatibility with MySQL, which makes it easy for developers to migrate their existing applications to TiDB. TiDB is used by companies such as Didi Chuxing, Mobike, and Meituan-Dianping to power their mission-critical applications.
ActiveCampaign's API provides access to a wide range of data related to marketing automation and customer relationship management. The following are the categories of data that can be accessed through ActiveCampaign's API:
1. Contacts: This includes information about individual contacts such as their name, email address, phone number, and other contact details.
2. Lists: This includes information about the lists of contacts that are stored in ActiveCampaign, such as the name of the list, the number of contacts in the list, and other list-related details.
3. Campaigns: This includes information about the email campaigns that have been sent through ActiveCampaign, such as the subject line, the number of recipients, and other campaign-related details.
4. Automations: This includes information about the automations that have been set up in ActiveCampaign, such as the triggers, actions, and conditions that are used to automate marketing tasks.
5. Deals: This includes information about the deals that have been created in ActiveCampaign, such as the name of the deal, the value of the deal, and other deal-related details.
6. Forms: This includes information about the forms that have been created in ActiveCampaign, such as the name of the form, the fields that are included in the form, and other form-related details.
7. Tags: This includes information about the tags that have been applied to contacts in ActiveCampaign, such as the name of the tag, the number of contacts with the tag, and other tag-related details.
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.
