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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
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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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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.
A YouTube Analytics is a group that is set of collection of up to 500 channels, videos, playlists, or assets. It aggregate data from competitor specific accounts, videos, and subscribers. As a generator, you can enable to detect the best time to publicize a video, how to increase the engagement of your subscribers, and the interests of the audience by viewing other channel analytics. For better understand your video and channel performance with key metrics and reports in YouTube Studio you can use analytics.
Teradata Vantage is a cloud-based analytics platform that enables businesses to analyze large amounts of data in real-time. It combines data warehousing, advanced analytics, and machine learning capabilities to provide a comprehensive solution for data-driven decision-making. Vantage allows users to access and analyze data from multiple sources, including structured and unstructured data, and provides a unified view of the data for better insights. It also offers advanced analytics tools such as predictive modeling, natural language processing, and graph analytics. With Vantage, businesses can make faster and more informed decisions, improve operational efficiency, and gain a competitive edge in their industry.
YouTube Analytics API provides access to a wide range of data related to YouTube channels and videos. The API allows developers to retrieve data on channel performance, video engagement, and audience demographics. Here are the categories of data that the YouTube Analytics API provides:
1. Channel data: This includes data related to the channel's views, subscribers, and watch time.
2. Video data: This includes data related to individual videos, such as views, likes, dislikes, comments, and shares.
3. Audience data: This includes data related to the demographics of the channel's audience, such as age, gender, and location.
4. Playback locations: This includes data related to where the videos are being played, such as on YouTube, embedded on other websites, or on mobile devices.
5. Traffic sources: This includes data related to how viewers are finding the channel's videos, such as through search, suggested videos, or external websites.
6. Ad performance: This includes data related to the performance of ads on the channel, such as impressions, clicks, and revenue.
7. Engagement data: This includes data related to how viewers are engaging with the channel's videos, such as watch time, average view duration, and audience retention.
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.
