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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.
Google Search Console is a Google service that helps site owners get the most out of their website. It offers ways for site owners to monitor, troubleshoot, and improve a site’s position on Google Search. It also provides reports and tools for measuring a site’s Search performance and traffic; learning what search queries lead to a site; optimizing website content; monitoring, testing, and tracking AMP pages; and much more, including the ability to test a site’s mobile usability.
JSON File is a tool that is used to store and exchange data in a structured format. JSON stands for JavaScript Object Notation, and it is a lightweight data interchange format that is easy for humans to read and write, and easy for machines to parse and generate. JSON files are commonly used in web applications to transfer data between the server and the client, and they are also used in many other programming languages and platforms. JSON files consist of key-value pairs, where each key is a string and each value can be a string, number, boolean, array, or another JSON object. The syntax of JSON is similar to that of JavaScript, but it is a separate language that can be used independently of JavaScript. JSON File is a tool that allows users to create, edit, and view JSON files. It provides a user-friendly interface for working with JSON data, and it can be used by developers, data analysts, and anyone else who needs to work with structured data. With JSON File, users can easily create and modify JSON files, and they can also validate the syntax of their JSON data to ensure that it is well-formed and error-free.
Google Search Console's API provides access to a wide range of data related to a website's performance in Google search results. The following are the categories of data that can be accessed through the API:
1. Search Analytics: This category includes data related to search queries, impressions, clicks, and click-through rates.
2. Sitemaps: This category includes data related to the sitemap of a website, such as the number of URLs submitted, indexed, and any errors encountered.
3. Crawl Errors: This category includes data related to any crawl errors encountered by Google while crawling a website, such as 404 errors, server errors, and soft 404 errors.
4. Security Issues: This category includes data related to any security issues detected by Google, such as malware or phishing.
5. Indexing: This category includes data related to the indexing status of a website, such as the number of pages indexed and any indexing errors encountered.
6. Structured Data: This category includes data related to the structured data markup on a website, such as the number of pages with structured data and any errors encountered.
7. Mobile Usability: This category includes data related to the mobile usability of a website, such as the number of pages with mobile usability issues and any errors encountered.
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.
