Databases changes, can trigger automated workflow actions like sending notifications, generating reports, or integrating with other business systems - streamlining operations and reducing administrative overhead. Workflow actions can also execute database commands, lookup from databases and execute custom SQL and more.
Enhance your database automation with AI-powered intelligence using ThinkAutomation. Automatically process incoming data, then use AI to classify, analyze, or extract insights before updating your database. For example, incoming customer inquiries can be categorized using AI sentiment analysis, with urgent requests flagged for priority handling. AI can also extract key details from unstructured text, summarize reports before storing them, or even translate entries for multilingual databases. You can use AI to generate SQL queries from natural language, which can then be executed in your workflow. By combining AI with ThinkAutomation's powerful database automation, businesses can streamline data processing, improve accuracy, and unlock deeper insights - without manual intervention.
ThinkAutomation can monitor your local (on-premises) or cloud databases for new or updated records. When a new or updated record is found, the content of the record will be passed to your Automation for processing. Within your Automation you can access individual column values. For example: You could monitor a 'customer' table for new customers. When a new customer is found, use the 'Name' and 'Email' columns to send the customer a welcome email. Your Automation can also use the data to update another database.
ThinkAutomation supports native acces to: Microsoft SQL Server, MySQL, MariaDB, PostgreSQL, Oracle, DB3, Firebird, SQLite, MS Access, MongoDB PLUS any ODBC or OLE/DB database.
ThinkAutomation reads records from a database at scheduled intervals
Query results are checked against your pre-defined rules and conditions
Triggered actions will then be performed against each record returned
Database automation can incorporate as many lookups and actions as you can conceive. It might be simple, scheduled record cleansing, periodic extractions, or timed and tiered communication workflows. You build your database pull rules using logical select statements and conditional processing. (Straightforward ‘if’, ‘then’, and ‘else’ type rules.) For example:
| Select | If | Then |
| Select all new accounts created in the last 24 hours | The customer has given contact consent | Send them a welcome email |
| Select all records created over X years ago | The account is still active | Send the customer a loyalty offer |
| Select all customers located within the UK | The contact number does not begin with +44 | Change the number to the correct format |
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