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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.
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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.
Merge is a puzzle game where players combine matching blocks to create new ones and clear the board. The game starts with simple blocks, but as players progress, they encounter more complex shapes and colors. The goal is to merge as many blocks as possible to earn points and advance to higher levels. The game also includes power-ups and special blocks that can help players clear the board more quickly. Merge is a fun and addictive game that challenges players to think strategically and quickly to achieve high scores.
Google Firestore is a cloud-based NoSQL document database that allows developers to store, sync, and query data for their web, mobile, and IoT applications. It is designed to provide real-time updates and offline support, making it ideal for applications that require fast and responsive data access. Firestore offers a flexible data model, allowing developers to store data in collections and documents, and supports complex queries and transactions. It also integrates with other Google Cloud services, such as Cloud Functions and Cloud Storage, to provide a complete backend solution for building scalable and reliable applications.
Merge's API provides access to a wide range of healthcare data, including:
1. Patient Data: This includes demographic information, medical history, and clinical notes.
2. Imaging Data: This includes medical images such as X-rays, CT scans, and MRIs.
3. Clinical Trial Data: This includes information on clinical trials, including study design, patient enrollment, and outcomes.
4. Medical Device Data: This includes data from medical devices such as pacemakers, insulin pumps, and blood glucose monitors.
5. Electronic Health Record (EHR) Data: This includes data from EHR systems, such as medication lists, lab results, and vital signs.
6. Genomic Data: This includes genetic information, such as DNA sequencing data and gene expression data.
7. Research Data: This includes data from research studies, such as survey data and clinical trial data.
Overall, Merge's API provides access to a comprehensive set of healthcare data, enabling developers to build innovative applications and solutions that improve patient care and outcomes.
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.
