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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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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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- 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.
Wrike is an American project management application service provider which is based in San Jose, California. It is a cloud based association and project management tool that assists users to manage projects from start to finish, providing full visibility. Wrike is entirely a cloud-based project management platform for teams of 20+ which is suitable for both large program and SMBs. Wrike ransaks to discard complexity from work so people and teams can enforce at their best.
Weaviate is an open-source, cloud-native, real-time vector search engine that allows developers to build intelligent applications with natural language processing (NLP) capabilities. It uses machine learning algorithms to understand the meaning of unstructured data and provides a semantic search engine that can retrieve relevant information from large datasets. Weaviate can be used to build chatbots, recommendation systems, and other intelligent applications that require NLP capabilities. It is designed to be scalable, flexible, and easy to use, with a RESTful API that allows developers to integrate it into their applications quickly. Weaviate is built on top of Kubernetes and can be deployed on-premises or in the cloud.
Wrike's API provides access to a wide range of data related to project management and collaboration. The following are the categories of data that can be accessed through Wrike's API:
1. Tasks: Information related to tasks such as task name, description, due date, status, and assignee.
2. Projects: Data related to projects such as project name, description, start and end dates, and project status.
3. Users: Information about users such as user name, email address, and user role.
4. Time tracking: Data related to time tracking such as time spent on tasks, time entries, and billable hours.
5. Comments: Information related to comments such as comment text, author, and date.
6. Attachments: Data related to attachments such as attachment name, type, and size.
7. Custom fields: Information related to custom fields such as field name, type, and value.
8. Folders: Data related to folders such as folder name, description, and folder structure.
9. Reports: Information related to reports such as report name, description, and report data.
Overall, Wrike's API provides access to a comprehensive set of data that can be used to enhance project management and collaboration.
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.
