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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).
- Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.
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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.
RingCentral is a cloud-based communication and collaboration platform that provides businesses with a range of tools to manage their communication needs. The platform offers features such as voice and video conferencing, messaging, team collaboration, and online meetings. It also provides a virtual phone system that allows businesses to manage their phone calls, voicemails, and faxes from a single platform. RingCentral is designed to help businesses improve their communication and collaboration, increase productivity, and reduce costs. The platform is scalable and can be customized to meet the specific needs of businesses of all sizes and industries.
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.
RingCentral's API provides access to a wide range of data related to communication and collaboration. The following are the categories of data that can be accessed through RingCentral's API:
1. User data: This includes information about users such as their name, email address, phone number, and extension.
2. Call data: This includes information about calls such as call duration, call type, call recording, and call history.
3. Message data: This includes information about messages such as message content, message type, message status, and message history.
4. Meeting data: This includes information about meetings such as meeting details, meeting participants, and meeting history.
5. Fax data: This includes information about faxes such as fax content, fax status, and fax history.
6. Presence data: This includes information about a user's availability status, such as whether they are available, busy, or offline.
7. Account data: This includes information about the RingCentral account, such as account settings, billing information, and usage statistics.
Overall, RingCentral's API provides access to a comprehensive set of data that can be used to build powerful communication and collaboration applications.
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.
