How to load data from Newsdata to Google Sheets

Learn how to use Airbyte to synchronize your Newsdata data into Google Sheets within minutes.

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Set up a Newsdata connector in Airbyte

Connect to Newsdata or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Google Sheets for your extracted Newsdata data

Select Google Sheets where you want to import data from your Newsdata source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Newsdata to Google Sheets in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
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How to Sync Newsdata to Google Sheets Manually

How to Sync Newsdata to Google Sheets Manually - Method 2:

FAQs

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.

NewsData is an online platform that provides updated news and information related to energy policy affairs in California and the Southwest. News data is one kinds of information that is collected using web scraping tools from a large number of news sources and outlets from across the internet. News Data Network is a reliable source of lifestyle news content. NewsData offers a common frame of reference for thousands of energy professionals, keeping them well-informed on Western energy policy, markets, resources, and other topics essential to their work.

Newsdata's API provides access to a wide range of data related to news and media. The following are the categories of data that can be accessed through the API:  

1. News articles: The API provides access to news articles from various sources, including major news outlets and smaller publications.  
2. News sources: The API provides information about news sources, including their names, URLs, and other relevant details.  
3. News topics: The API provides information about news topics, including their names, descriptions, and other relevant details.  
4. News events: The API provides information about news events, including their names, dates, locations, and other relevant details.  
5. News sentiment: The API provides information about the sentiment of news articles, including whether they are positive, negative, or neutral.  
6. News trends: The API provides information about news trends, including which topics are currently popular and which are declining in popularity.  
7. News analytics: The API provides access to various analytics related to news, including traffic data, engagement metrics, and other relevant information.  

Overall, Newsdata's API provides a comprehensive set of data related to news and media, making it a valuable resource for journalists, researchers, and other professionals in the industry.

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: 
1. Set up Newsdata to Google Sheets as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Newsdata to Google Sheets and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

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.

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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Connectors Used

Newsdata
Google Sheets

Related Syncs with Newsdata

Newsdata to CSV File
Newsdata to Google Sheets
Newsdata to JSON File

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Newsdata to Google Sheets