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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.
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.
ClickHouse is an open-source, column-oriented OLAP database management system that allows users to generate analytical reports using SQL queries. Also offered as a secure and scalable service in the cloud, ClickHouse Cloud allows anyone to effortlessly take advantage of efficient real time analytical processing.
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.
