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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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- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
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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).
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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.
SmartEngage is a multi-award-winning retail, travel and hospitality loyalty platform of Collinson. SmartEngage is the worldwide first and only Engagement Service Provider which is the first ever platform to combine Email Marketing with Facebook Messenger, and Push Notifications. SmartEngage is Free Symptom Checker and it is also a cross-channel autoresponder tool for marketing automation that assists organizations to develop their average percentage of opens by sending their message at the right time, and through the right platform.
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.
SmartEngage's API provides access to a wide range of data related to customer engagement and behavior. The following are the categories of data that can be accessed through SmartEngage's API:
1. User data: This includes information about individual users such as their name, email address, phone number, and location.
2. Behavioral data: This includes data related to user behavior such as their browsing history, purchase history, and engagement with marketing campaigns.
3. Campaign data: This includes data related to marketing campaigns such as email open rates, click-through rates, and conversion rates.
4. Segmentation data: This includes data related to user segmentation such as demographic information, interests, and behavior.
5. Analytics data: This includes data related to website and app analytics such as page views, bounce rates, and session duration.
6. Personalization data: This includes data related to personalization such as user preferences, interests, and behavior.
Overall, SmartEngage's API provides access to a comprehensive set of data that can be used to improve customer engagement and drive business 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.
