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result = execute_query(validated_query) insights.append({"query": query, "result": result}) except Exception as e: insights.append({"query": query, "error": str(e)}) else: insights.append({"query": query, "error": "Access denied"}) return insights def encrypt_data(query): # Implement data encryption logic here pass def check_access_control(query): # Implement access control logic here pass def validate_input(query): # Implement input validation logic here pass def execute_query(query): # Implement query execution logic here pass ``` ->-> 9,22 [Turn 9605] Assistant: Certainly! To build a scalable function that incorporates the 6 secure tuning practices and provides a summary of the insights gained from each query, we need to ensure that the function is efficient and can handle large query sets. Here are the steps to achieve this: 1. **Data Encryption**: Encrypt the data to protect sensitive information. 2. **Access Control**: Ensure that only authorized users can access the data.