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Cover your custom needs with our extensibility
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- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
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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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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.
Greenhouse is a software company that specializes in helping businesses acquire talent. It offers a variety of software tools and services to help businesses throughout all aspects of the hiring process, from applicant tracking systems to recruiting software. With the goal of helping businesses find and hire the ideal candidate, Greenhouse helps employers improve the efficiency and effectiveness of the recruitment and hiring process.
A communication solutions agency, Kafka is a cloud-based / on-prem distributed system offering social media services, public relations, and events. For event streaming, three main functionalities are available: the ability to (1) subscribe to (read) and publish (write) streams of events, (2) store streams of events indefinitely, durably, and reliably, and (3) process streams of events in either real-time or retrospectively. Kafka offers these capabilities in a secure, highly scalable, and elastic manner.
Greenhouse's API provides access to a wide range of data related to the recruitment process. The following are the categories of data that can be accessed through the API:
1. Candidates: Information about candidates who have applied for a job, including their name, contact details, resume, and application status.
2. Jobs: Details about the job openings, including the job title, location, department, and job description.
3. Applications: Information about the applications submitted by candidates, including the date of submission, the source of the application, and the status of the application.
4. Interviews: Details about the interviews scheduled with candidates, including the date, time, location, and interviewer.
5. Offers: Information about the job offers made to candidates, including the salary, benefits, and start date.
6. Users: Details about the users who have access to the Greenhouse account, including their name, email address, and role.
7. Departments: Information about the departments within the organization, including the name, description, and manager.
8. Sources: Details about the sources of the candidates, including job boards, referrals, and social media.
Overall, Greenhouse's API provides a comprehensive set of data that can be used to streamline the recruitment process and make data-driven decisions.
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.
