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You can use CData Connect AI to query Twitter Ads data through a SQL Server interface. Follow the procedure below to create a virtual database for Twitter Ads in Connect AI and start querying using Node.js.
CData Connect AI provides a pure MySQL, cloud-to-cloud interface for Twitter Ads, allowing you to easily query live Twitter Ads data in Node.js โ without replicating the data to a natively supported database. As you query data in Node.js, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc) directly to Twitter Ads, leveraging server-side processing to quickly return Twitter Ads data.
Connectivity to Twitter Ads from NodeJS is made possible through CData Connect AI. To work with Twitter Ads data from NodeJS, we start by creating and configuring a Twitter Ads connection.
All tables require authentication. You must use OAuth to authenticate with Twitter. OAuth requires the authenticating user to interact with Twitter using the browser. For more information, refer to the OAuth section in the Help documentation.
๐ Configuring a connection (Salesforce is shown)When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.
With the connection configured and a PAT generated, you are ready to connect to Twitter Ads data from Node.js.
The following example shows how to define a connection and execute queries to Twitter Ads with the SQL Server module. You will need the following information:
Connect to Twitter Ads data and start executing queries with the code below:
var sql = require('mssql')
var config = {
server: 'tds.cdata.com',
port: 14333,
user: '[email protected]', //update me
password: 'CONNECT_USER_PAT', //update me
options: {
encrypt: true,
database: 'TwitterAds1'
}
}
sql.connect(config, err => {
if(err){
throw err ;
}
new sql.Request().query('SELECT * FROM AdStats', (err, result) => {
console.dir(result)
})
});
sql.on('error', err => {
console.log("SQL Error: " ,err);
})
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