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First, obtain an API key from News API by signing up on their website. This key will allow you to authenticate your requests and access the data. Familiarize yourself with the API documentation to understand the available endpoints and parameters you can use to fetch the required news data.
Use a programming language like Python to write a script that sends HTTP requests to the News API. Utilize libraries such as `requests` to make GET requests with your API key and fetch the data. Ensure you handle pagination if the API returns data in multiple pages.
Once you have the raw data from the API, parse it into a structured format. Use JSON parsing libraries like Python's built-in `json` module to convert the JSON response into a Python dictionary or list. Identify and extract the relevant fields you want to store in Teradata Vantage, such as headlines, publication dates, sources, etc.
Convert the structured data into a CSV format, which is straightforward to load into Teradata Vantage. Use libraries such as `csv` in Python to write the extracted data to a CSV file. Ensure the CSV file includes appropriate headers corresponding to the fields extracted from the API response.
Set up your Teradata Vantage environment to receive the new data. This involves creating a table with a schema that matches the structure of your CSV file. Use SQL commands to define the table structure, including field names and data types.
Transfer the CSV file to the Teradata server environment. This can be done using secure file transfer protocols like SFTP or SCP. Ensure that the file is placed in a directory accessible by the Teradata loading utilities.
Use Teradata's built-in utilities such as `FastLoad` or `TPT (Teradata Parallel Transporter)` to import the CSV data into the Teradata Vantage table. Configure the utility scripts to specify the input CSV file, the target table, and any necessary options for handling data types and error logging. Execute the load operation to move the data into the database.
By following these steps, you can effectively transfer data from News API into Teradata Vantage without relying on third-party connectors or integrations.
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 News API gives a lot of flexibility in how you create and manage your news content. This connector is a simple and easy-to-use REST API that offers JSON search results for recent and historical news articles published by over 80,000 sources worldwide. As a result, you can quickly show trending news headlines in your web application. Also, combining the Google News API is very easy. API is short for application programming interface, which is a software intermediary that permits two applications to talk to each other.
News API provides access to a wide range of data related to news articles and sources. The following are the categories of data that can be accessed through News API's API:
1. News articles: News API provides access to articles from various news sources around the world. These articles can be filtered by language, country, and category.
2. News sources: News API provides a list of news sources that can be used to filter articles. These sources can be filtered by language, country, and category.
3. Top headlines: News API provides access to the top headlines from various news sources around the world. These headlines can be filtered by language, country, and category.
4. Search results: News API provides access to search results based on a keyword or phrase. These search results can be filtered by language, country, and category.
5. Article metadata: News API provides metadata for each article, including the title, author, description, URL, and published date.
6. Image URLs: News API provides access to the URLs of images associated with each article.
7. Article content: News API provides access to the full content of each article, including the text and any embedded media.
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.
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