Sequence model

Note: Before using this feature, make sure your data is set up as described in the Prepare your sequence data section.

Syntho is capable of processing data in the form of lists, sequences, or time-series when structured in entity table-linked table structure.

Syntho's synthetic data sequence models allows you to capture relational information between any entity table and linked table. Entity tables contain the profiles of data entities, while linked tables reference them.

Entity tables can be identified by their attributes, which describe privacy-sensitive information about data entities, such as names, birthdates, phone numbers, addresses, and more. Linked tables often contain event information about a referenced entity, which can span multiple rows per entity, such as a monthly salary payment.

Let's consider the Patients and PatientMedications tables shown below. Here, the Patients table is the entity table. The PatientMedications tables is the linked table.

To synthesize these tables using Syntho's sequence models:

1. Syntho starts by synthesizing the Patients table.

2. Then, it synthesizes the PatientMedications table using the synthetic Patients table as context.

How to apply Syntho's synthetic data sequence model

To use Syntho's synthetic data sequence models, you can do the following:

1. On the Job Configuration panel, drag the related entity table and linked table under Synthesize.

2. Drag any other tables under De-identify or Exclude.

3. On the Job configuration panel, select Generate.

4. On the Job configuration panel, enable the Enable sequence modeling toggle**.**

5. Finally, select Start generating.

Drag and drop tables

Enable sequence modeling

Sequence model parameters

Before initiating the generation process, you have the option to modify sequence model parameters. Here's an overview:

• Max sequence length: Sets a cap on sequence lengths, truncating any sequence that exceeds this limit.

• Rare long sequence protection threshold: Defines a limit for the length of data sequences used in training, adjusting the longest sequences to the length of the Nth sequence.

• N generated entities: Determines the number of entities to generate, each associated with a sequence.

• Read batch size: The quantity of rows read from each source table per batch.

• Write batch size: The quantity of rows inserted into each destination table per batch.

• N connections: Specifies the number of connections.

Sequence Model Parameters

Limitations & Recommendations

It is important to consider the following when using Syntho's sequence models:

• 2 tables: Syntho has limited the use of its sequence models to 2 tables that are structured according to the entity table-linked structure to maximize the synthetic data utility.

• Order of rows: For your linked table, it is recommended to store the rows in the correct order. This information will be used by Syntho's generative AI models.

• Resource Consumption: This feature is resource-intensive and may slow down your data generation process. Consider reducing your input data or adjust the sequence model parameters to reduce time and resources for your job.

Understanding these limitations and recommendations will help you make the most of Syntho.