To generate synthetic data from CSV or Parquet files, check the guidelines below to learn how to best prepare your files. |
We recommend synthesizing datasets in Parquet format. For more information, see CSV requirements. |
A subject is an entity or individual whose privacy you are going to protect. A subject table, therefore, contains records that describe these subjects.
Each row in a subject table describes the profile of a unique subject. They contain fields that tell something about them, such as their name, gender, height, place of residence, or income.
In practice, two or more real-world entities may have identical features when they’re described as subjects in the subject table. Conversely, a customer can make several online purchases using different accounts or without logging in to their account. This results in a subject table that contains multiple records with different identifiers for the same person.
MOSTLY AI delivers the most accurate results if the subject table reflects the real world as closely as possible. If real-world entities share identical properties, then this should be left as such. But if multiple records contain the same contact details, it’s plausible that it’s the same person and could be considered for merging.
Below you’ll find an example of a subject table. You can use it as a guideline to create your own.
MOSTLY AI can process lists, sequences, or time-series data when they’re formatted as subject table-linked table datasets. Here you can think of shopping lists, insurance claims, patient health records, or time-series data, such as online shopping journeys, purchase histories, or financial transactions.
Linked tables contain events, and MOSTLY AI processes these as properties of the subjects in your subject table. Therefore, they cannot exist without subjects, but subjects can have zero events. This relationship guarantees the subjects` privacy during synthesization, which is why these types of data need to be formatted into a subject table and a separate linked table.
The image below shows the columns that these tables must have to make this relationship. Each record in your linked table must have a field that specifies to which subject it belongs.
If you’re working with CSV or Parquet files, MOSTLY AI automatically links two tables if the subject table contains a column called id and the second table contains _id in the name of a column (for instance, players_id ).
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Below you’ll find an example of a basic customer journey dataset with two subjects. Alice Doe made a purchase after visiting the store twice, and Bob Joe was flagged as a churned customer after he no longer showed up for five days.
id firstName lastName
1 Alice Doe
2 Bob Joe
users_id event_time event_type
1 2020-04-01 visit
1 2020-04-03 visit
1 2020-04-05 purchase
2 2020-03-13 visit
2 2020-03-18 churn
If you have a single table with event data, please split it into a subject and linked table accordingly. |