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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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- 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.
Outreach is a sales engagement platform that accelerates revenue growth by optimizing every interaction throughout the customer lifecycle. The platform manages all customer interactions across email, voice and social, and leverages machine learning to guide reps to take the right actions.
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.
Outreach's API provides access to a wide range of data related to sales and marketing activities. Here are some of the categories of data that can be accessed through the API:
1. Prospects and leads: Information about potential customers, including their contact details, job titles, and company information.
2. Accounts: Data related to the companies that prospects and leads work for, including company size, industry, and location.
3. Activities: Information about sales and marketing activities, such as emails, calls, and meetings, including details about the participants, duration, and outcomes.
4. Templates and sequences: Data related to email templates and sequences used in outreach campaigns, including open and click-through rates.
5. Analytics: Metrics related to sales and marketing performance, such as conversion rates, pipeline value, and revenue generated.
6. Integrations: Information about third-party tools and services integrated with Outreach, including data related to those integrations.
Overall, Outreach's API provides a wealth of data that can be used to optimize sales and marketing strategies, improve customer engagement, and drive revenue growth.
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.
