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- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
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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.
The Times Developer Network is our API clearinghouse and community. You need to read the API documentation and browse the application gallery to get the latest news about the New York Times API. If you do not agree to any of the terms below or the NYT Terms of Service, NYT does not grant you a license to use the NYT API. In the event of any inconsistency between these Terms of Use and the Terms of Service, these Terms of Use control.
Microsoft Power BI is a business analytics tool that allows users to visualize and analyze data from various sources. It is a cloud-based service that provides interactive dashboards, reports, and data visualizations that can be shared across an organization. Power BI can connect to a wide range of data sources, including Excel spreadsheets, cloud-based and on-premises data sources, and third-party applications. With Power BI, users can create custom dashboards and reports that provide insights into their business data. The tool offers a range of visualization options, including charts, graphs, and maps, that can be customized to suit specific needs. Users can also create interactive reports that allow them to drill down into their data and explore it in more detail. Power BI also includes features for data modeling and data preparation, allowing users to clean and transform their data before visualizing it. The tool also includes machine learning capabilities that can be used to create predictive models and identify trends in data. Overall, Microsoft Power BI is a powerful tool for businesses looking to gain insights into their data and make data-driven decisions.
The New York Times API provides access to a wide range of data categories, including:
1. Articles: Full-text articles from the New York Times, including news, opinion, and feature pieces.
2. Multimedia: Images, videos, and other multimedia content from the New York Times.
3. Best Sellers: Lists of best-selling books, both fiction and non-fiction, as compiled by the New York Times.
4. Movie Reviews: Reviews of movies from the New York Times, including ratings and summaries.
5. TimesTags: A comprehensive list of tags used by the New York Times to categorize articles and other content.
6. Times Newswire: A real-time feed of breaking news stories from the New York Times.
7. Top Stories: A list of the most popular articles on the New York Times website, updated in real-time.
8. Archive: Access to the New York Times archive, including articles dating back to 1851.
9. Times Insider: Exclusive content from the New York Times, including behind-the-scenes stories and interviews with journalists.
Overall, the New York Times API provides a wealth of data for developers and researchers interested in exploring the content and history of one of the world's most respected news organizations.
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.
