Google BigQuery + Google Translate Integration

This automation allows you to automatically detect the language when Newsletter is added in GetResponse, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated GetResponse messages for further analysis or record-keeping.

Here's how it works:
 1. GetResponse: Whenever Newsletter is added, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from GetResponse to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from GetResponse to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated GetResponse messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when SMS is received/sent in Twilio, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Twilio messages for further analysis or record-keeping.

Here's how it works:
 1. Twilio: Whenever SMS is received/sent, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Twilio to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Twilio to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Twilio messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Incoming SMS is received in ClickSend SMS, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated ClickSend SMS messages for further analysis or record-keeping.

Here's how it works:
 1. ClickSend SMS: Whenever Incoming SMS is received, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from ClickSend SMS to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from ClickSend SMS to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated ClickSend SMS messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Chat message is created in Ryver, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Ryver messages for further analysis or record-keeping.

Here's how it works:
 1. Ryver: Whenever Chat message is created, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Ryver to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Ryver to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Ryver messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Notification is created in Trello, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Trello messages for further analysis or record-keeping.

Here's how it works:
 1. Trello: Whenever Notification is created, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Trello to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Trello to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Trello messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when SMS is sent in Dialpad, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Dialpad messages for further analysis or record-keeping.

Here's how it works:
 1. Dialpad: Whenever SMS is sent, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Dialpad to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Dialpad to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Dialpad messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when SMS is delivered in Vonage SMS API, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Vonage SMS API messages for further analysis or record-keeping.

Here's how it works:
 1. Vonage SMS API: Whenever SMS is delivered, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Vonage SMS API to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Vonage SMS API to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Vonage SMS API messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when SMS is received in Octopush SMS, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Octopush SMS messages for further analysis or record-keeping.

Here's how it works:
 1. Octopush SMS: Whenever SMS is received, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Octopush SMS to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Octopush SMS to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Octopush SMS messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when SMS is delivered in Octopush SMS, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Octopush SMS messages for further analysis or record-keeping.

Here's how it works:
 1. Octopush SMS: Whenever SMS is delivered, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Octopush SMS to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Octopush SMS to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Octopush SMS messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Message is sent in Salesmsg, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Salesmsg messages for further analysis or record-keeping.

Here's how it works:
 1. Salesmsg: Whenever Message is sent, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Salesmsg to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Salesmsg to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Salesmsg messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Message is received in Salesmsg, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Salesmsg messages for further analysis or record-keeping.

Here's how it works:
 1. Salesmsg: Whenever Message is received, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Salesmsg to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Salesmsg to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Salesmsg messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Email is sent in Lemlist, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Lemlist messages for further analysis or record-keeping.

Here's how it works:
 1. Lemlist: Whenever Email is sent, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Lemlist to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Lemlist to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Lemlist messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Email is received in Parserr, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Parserr messages for further analysis or record-keeping.

Here's how it works:
 1. Parserr: Whenever Email is received, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Parserr to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Parserr to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Parserr messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Message received from whatsapp in WaliChat , translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated WaliChat messages for further analysis or record-keeping.

Here's how it works:
 1. WaliChat : Whenever Message received from whatsapp, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from WaliChat to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from WaliChat to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated WaliChat messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Message received from whatsapp in PulpoChat, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated PulpoChat messages for further analysis or record-keeping.

Here's how it works:
 1. PulpoChat: Whenever Message received from whatsapp, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from PulpoChat to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from PulpoChat to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated PulpoChat messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Message received from whatsapp in Bulldog-WP , translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Bulldog-WP messages for further analysis or record-keeping.

Here's how it works:
 1. Bulldog-WP : Whenever Message received from whatsapp, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Bulldog-WP to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Bulldog-WP to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Bulldog-WP messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Message received from whatsapp in WIIVO, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated WIIVO messages for further analysis or record-keeping.

Here's how it works:
 1. WIIVO: Whenever Message received from whatsapp, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from WIIVO to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from WIIVO to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated WIIVO messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Message is sent in Sakari SMS, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Sakari SMS messages for further analysis or record-keeping.

Here's how it works:
 1. Sakari SMS: Whenever Message is sent, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Sakari SMS to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Sakari SMS to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Sakari SMS messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Message is sent in Ringover, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Ringover messages for further analysis or record-keeping.

Here's how it works:
 1. Ringover: Whenever Message is sent, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Ringover to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Ringover to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Ringover messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.

This automation allows you to automatically detect the language when Reply is received in Instantly, translate it to a different language using Google Translate, and Create row in Google BigQuery with the translated content. It helps centralize and store translated Instantly messages for further analysis or record-keeping.

Here's how it works:
 1. Instantly: Whenever Reply is received, the automation will be triggered.
 2. {{Language Detection}}: Pass the text content from Instantly to Google Translate for language detection.
 3. Condition - You can add a condition that says, Language..... 'is not equal to'..... your desired language. So if the condition is met, the automation will proceed further.
 4. Google Translate: The automation will translate the text content from Instantly to your desired language.
5. Google BigQuery: The translated content will be used to Create row in Google BigQuery, allowing you to store and analyze the translated Instantly messages in a structured manner. Make sure you specify the Google BigQuery, and column values for storing the translated message.