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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.
Linnworks is one of the world's leading commerce automation platforms, integrated with the world's most popular marketplaces and selling channels. Businesses can sell wherever their customers are with Linnworks, which connects, manages, and automates commerce operations. Online sales can be managed from a central platform, which allows you to list across multiple selling channels, handle large volumes of orders, and monitor business performance.
An object-relational database management system, PostgreSQL is able to handle a wide range of workloads, supports multiple standards, and is cross-platform, running on numerous operating systems including Microsoft Windows, Solaris, Linux, and FreeBSD. It is highly extensible, and supports more than 12 procedural languages, Spatial data support, Gin and GIST Indexes, and more. Many web, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.
Linnworks's API provides access to a wide range of data related to e-commerce operations. The following are the categories of data that can be accessed through Linnworks's API:
1. Inventory Management: This category includes data related to inventory levels, stock movements, and product information.
2. Order Management: This category includes data related to orders, such as order details, shipping information, and payment information.
3. Shipping Management: This category includes data related to shipping, such as shipping rates, tracking information, and carrier information.
4. Customer Management: This category includes data related to customers, such as customer details, order history, and contact information.
5. Sales Management: This category includes data related to sales, such as sales reports, revenue data, and product performance data.
6. Accounting Management: This category includes data related to accounting, such as invoices, payments, and financial reports.
7. Marketing Management: This category includes data related to marketing, such as promotional campaigns, customer segmentation, and advertising data.
Overall, Linnworks's API provides access to a comprehensive set of data that can help businesses streamline their e-commerce operations and make data-driven decisions.
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.
