Transform Your Data with Tonic: A Complete Guide

Table of Contents

1. Introduction
2. What is Tonic?
3. Why Use Tonic?
4. Common Use Cases for Tonic Generated Data
5. How Tonic Works
6. The Tonic Workflow
7. Step 1: Connecting to Your Data
8. Step 2: Identifying Sensitive Data
9. Step 3: Configuration
10. Step 4: Generating Data
11. Conclusion

The Tonic Workflow

Tonic is a powerful platform that allows You to generate safe, secure, de-identified versions of your own data. This is incredibly useful for a variety of purposes, including software testing, development, and compliance with data privacy regulations. In this article, we'll take a closer look at the Tonic workflow and how it can help you transform your original data into realistic, de-identified data.

Introduction

Before we dive into the specifics of the Tonic workflow, let's take a moment to define what Tonic is and why you might want to use it.

What is Tonic?

Tonic is a platform that allows you to generate safe, secure, de-identified versions of your own data. This means that you can use your own data for a variety of purposes without risking the exposure of sensitive information. Tonic generates data that replicates the Shape of your original data, providing the same tables, columns, and data types, but uses realistic de-identification and synthesis to protect personal and other sensitive information.

Why Use Tonic?

There are many reasons why you might want to use Tonic. One common use case for Tonic-generated data is software testing. Effective testing requires realistic data, and Tonic-generated data provides just that. You can also use Tonic-generated data to populate development and staging environments and to ensure compliance with data privacy regulations.

Common Use Cases for Tonic Generated Data

As we've already Mentioned, there are many use cases for Tonic-generated data. Here are just a few examples:

• Software testing
• Development and staging environments
• Compliance with data privacy regulations
• Machine learning and AI training
• Data analysis and visualization
• Research and academic studies

How Tonic Works

Now that we've covered the basics of what Tonic is and why you might want to use it, let's take a closer look at how it works.

The Tonic workflow consists of four main steps:

1. Connecting to your data
2. Identifying sensitive data
3. Configuration
4. Generating data

Let's take a closer look at each of these steps.

Step 1: Connecting to Your Data

The first step in the Tonic workflow is to connect to your data. Tonic configuration and generation occurs in the Context of a Tonic workspace. You can Create different workspaces to work with different types and sets of data.

When you first set up your workspace, you tell Tonic about your data. Specifically, you need to provide information about the Type of database you're using, where your source data is located, and where Tonic should put the data that it generates.

Step 2: Identifying Sensitive Data

Once you've connected to your data, the next step is to identify sensitive data that needs to be transformed. Tonic automatically scans your source data for sensitive information such as names, email addresses, and other identifiers. This initial scan marks columns that contain sensitive information. You can also override the scan results to mark a column as sensitive or not sensitive.

Tonic's Privacy Hub shows the sensitivity and protection status for all of the columns in your source data. The At-Risk Columns panel identifies source data columns that contain sensitive information and that are not yet configured to be transformed in the destination data. Protected columns are columns that are configured to be transformed in the destination data. Non-sensitive columns are not transformed and are not flagged as containing sensitive information.

Step 3: Configuration

The configuration step tells Tonic how to perform the transformation. Configuration includes how to transform columns, how to populate records in destination tables, and whether to generate a smaller subset of data.

Configuration at the column level includes selecting which generator to Apply. The generator determines how to complete the transformation for that column. For example, a generator might scramble letters, shift timestamp values, or create new values.

You can configure a column from one of the following locations in the Privacy Hub:

• The database view
• The table view

The database view gives you access to every table in the database as well as each of the columns. Here, you can select the generator type and configure a particular column.

The table view is limited to one table at a time. Here, you can click the configuration drop-down and select which generator you'd like to use on that column.

Tonic's subsetting tool provides another option to configure data generation. Specifically, subsetting allows you to generate a smaller subset of the source data. For example, you can include a random 5% of transaction records along with the related records and other tables, or you could use a custom WHERE clause (e.g., transactions that occurred in the United States along with the related records and other tables).

Step 4: Generating Data

After you've completed your data configuration, the final step is to generate the data. The data generation process uses the table, column, and subsetting configurations to create your destination database. Before you start the generation, you can also configure actions to occur automatically after the data generation completes. Post-job scripts are custom SQL scripts that run when a job is complete. Webhooks send HTTP POST requests when a job completes, fails, or is canceled.

When you're ready to start the generation process, click "Generate Data." If nothing blocks the generation, you can start the job. The Jobs tab allows you to view the job history and track the generation and see details about a job and its results. This helps you to adjust your configurations and Rerun data generation as needed to fine-tune your results.

Conclusion

In conclusion, Tonic is a powerful platform that allows you to generate safe, secure, de-identified versions of your own data. The Tonic workflow consists of four main steps: connecting to your data, identifying sensitive data, configuration, and generating data. By following these steps, you can transform your original data into realistic, de-identified data that can be used for a variety of purposes.