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As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
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Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
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Keep your data engineering costs in check
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- Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
- Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.
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Including for your Airbyte Open Source instance with our premium support.
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.
EmailOctopus provides simple and powerful tools to increase your business at affordable pricing and it can easily build relationships, accelerate lead generation and transform subscribers into customers. EmailOctopus is a low-cost email marketing platform that provides businesses, creators and marketers with the essential features they need to grow their mailing list and engage their audience. You can manage and email your subscribers for far cheaper through EmailOctopus. It provides clear analytics on campaign performance, allowing users to track every open, click, bounce and unsubscribe to optimize marketing efforts.
BigQuery is an enterprise data warehouse that draws on the processing power of Google Cloud Storage to enable fast processing of SQL queries through massive datasets. BigQuery helps businesses select the most appropriate software provider to assemble their data, based on the platforms the business uses. Once a business’ data is acculumated, it is moved into BigQuery. The company controls access to the data, but BigQuery stores and processes it for greater speed and convenience.
EmailOctopus's API provides access to a wide range of data related to email marketing campaigns. The following are the categories of data that can be accessed through the API:
1. Lists: Information about the email lists created in EmailOctopus, including the number of subscribers, list name, and list ID.
2. Subscribers: Data related to the subscribers on the email lists, including their email address, name, and subscription status.
3. Campaigns: Information about the email campaigns created in EmailOctopus, including the campaign name, ID, and status.
4. Reports: Data related to the performance of email campaigns, including open rates, click-through rates, and bounce rates.
5. Templates: Information about the email templates created in EmailOctopus, including the template name, ID, and content.
6. Automations: Data related to the automated email campaigns created in EmailOctopus, including the automation name, ID, and status.
7. Webhooks: Information about the webhooks set up in EmailOctopus, including the webhook URL, event type, and status.
Overall, EmailOctopus's API provides access to a comprehensive set of data that can be used to analyze and optimize email marketing campaigns.
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.
