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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.
Yandex Metrica assists you to get narrative reports and record the actions of personal users, to detect what people are seeking for on your site. It is a web analytics tool that you can easily use to collect data about visitors to your website and their sessions. One can easily use Yandex Metrica web analytics tool to get visual reports and video recordings of user actions and track traffic sources. Yandex Metrica is the best plugin for WordPress.
Yandex Metrica's API provides access to a wide range of data related to website and mobile app performance. The types of data that can be accessed through the API can be categorized as follows:
1. User behavior data:
- Pageviews
- Sessions
- Bounce rate
- Time on site
- Clicks
- Goals and conversions
2. Traffic sources data:
- Referral sources
- Search engine traffic
- Direct traffic
- Social media traffic
- Paid traffic
3. Audience data:
- Demographics
- Geolocation
- Device type
- Browser type
- Language
4. Technical data:
- Page load time
- Error messages
- Server response time
- Browser and device compatibility
5. Custom data:
- Custom events
- Custom dimensions
- Custom metrics
Overall, Yandex Metrica's API provides a comprehensive set of data that can be used to analyze and optimize website and mobile app performance.
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.
Yandex Metrica assists you to get narrative reports and record the actions of personal users, to detect what people are seeking for on your site. It is a web analytics tool that you can easily use to collect data about visitors to your website and their sessions. One can easily use Yandex Metrica web analytics tool to get visual reports and video recordings of user actions and track traffic sources. Yandex Metrica is the best plugin for WordPress.
For huge analytical tables, Apache Iceberg is a high-performance format. Using Apache Iceberg, engines such as Spark, Trino, Flink, Presto, Hive and Impala can safely work with the same tables, at the same time, providing the reliability and simplicity of SQL tables to big data. With Apache Iceberg, you can merge new data, update existing rows, and delete specific rows. Data files can be eagerly rewritten or deleted deltas can be used to make updates faster.
1. First, you need to have a Yandex Metrica account and access to the API key. If you don't have one, you can create it by following the instructions on the Yandex Metrica website.
2. Once you have the API key, go to the Airbyte dashboard and click on "Sources" on the left-hand side menu.
3. Click on the "Create a new source" button and select "Yandex Metrica" from the list of available connectors.
4. Enter a name for your source and click on "Next".
5. In the "Connection Configuration" section, enter your Yandex Metrica API key in the "API Key" field.
6. Select the desired data range for your source in the "Date Range" field.
7. Choose the metrics and dimensions you want to include in your source by selecting them from the dropdown menus in the "Metrics" and "Dimensions" sections.
8. Click on "Test" to verify that the connection is working properly.
9. If the test is successful, click on "Create" to save your Yandex Metrica source connector on Airbyte.
1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Click on the "Apache Iceberg" destination connector and select "Create new connection."
3. Enter a name for your connection and provide the necessary credentials for your Apache Iceberg database, including the host, port, database name, username, and password.
4. Test the connection to ensure that it is successful. 5. Select the tables or data sources that you want to replicate to your Apache Iceberg database.
6. Configure any additional settings or options for your connection, such as the frequency of data replication or any transformations that you want to apply to your data.
7. Save your connection and start the replication process.
8. Monitor the progress of your data replication and troubleshoot any issues that may arise.
9. Once the replication process is complete, verify that your data has been successfully replicated to your Apache Iceberg database.
10. Use your Apache Iceberg database to analyze and query your data as needed.
With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.
We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
Ready to get started?
Frequently Asked Questions
Yandex Metrica's API provides access to a wide range of data related to website and mobile app performance. The types of data that can be accessed through the API can be categorized as follows:
1. User behavior data:
- Pageviews
- Sessions
- Bounce rate
- Time on site
- Clicks
- Goals and conversions
2. Traffic sources data:
- Referral sources
- Search engine traffic
- Direct traffic
- Social media traffic
- Paid traffic
3. Audience data:
- Demographics
- Geolocation
- Device type
- Browser type
- Language
4. Technical data:
- Page load time
- Error messages
- Server response time
- Browser and device compatibility
5. Custom data:
- Custom events
- Custom dimensions
- Custom metrics
Overall, Yandex Metrica's API provides a comprehensive set of data that can be used to analyze and optimize website and mobile app performance.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: