Which diagnostic analytics technique works to ensure that there are no transactions that are recorded twice?

The diagnostic analytics technique that works to ensure that there are no transactions that are recorded twice is called "Duplicate Detection". This technique involves the use of algorithms and data analysis tools to identify and remove duplicate entries in a dataset.

Here are the steps on how it works:

1. Data Collection: The first step in duplicate detection is gathering the data. This could be transaction data from a financial system, customer data from a CRM system, etc.

2. Data Cleaning: The collected data is then cleaned. This involves removing any irrelevant data, correcting any errors, and standardizing the data into a common format.

3. Data Analysis: Once the data is cleaned, it is then analyzed. This involves using algorithms to compare each data entry with every other data entry in the dataset.

4. Duplicate Identification: If the algorithm finds two or more entries that are identical or very similar, it flags them as potential duplicates.

5. Duplicate Removal/Resolution: Once potential duplicates are identified, they are either removed from the dataset or resolved in some way. This could involve merging the duplicate entries, deleting one of the duplicates, or flagging the duplicate for further review.

6. Verification: The final step is to verify that the duplicate detection process has worked correctly. This could involve manually reviewing a sample of the data, or using additional data analysis tools to check for duplicates.

By using this technique, businesses can ensure the accuracy