[
Tumult ... Reviews
](https://www.g2.com/products/tumult-analytics/reviews)

[
Tumult ... Reviews
](https://www.g2.com/products/tumult-analytics/reviews)

# Tumult Analytics Features

##### ## Compliance (2)

GDPR compliant

Meets GDPR requirements for pseudonymisation under the Data Protection by Design and by Default requirements.

CCPA compliant

Meets de-identification requirements under the CCPA.

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##### ## Functionality (3)

Static pseudonymization

Offers traditional static de-identification (also known as consistent replacement), where the pseudonymized data uses the same pseudonyms across multiple data sets. For example, John Smith is replaced with Robert Fox and the Robert Fox name is used multiple times. This type of pseudonymization carries some risks of re-identification if paired with enough datasets.

Dynamic pseudonymization

Offers dynamic de-identification (also known as random replacement), where the pseudonymized data uses different pseudonyms across multiple data sets. For example, John Smith is replaced with Robert Fox once, and then the next time the data is used the name changes to Michael Jones. This type of pseudonymization carries lesser risk of re-identification if paired with many datasets.

Batch de-identification

Offers methods to de-identify large volumes of data using batch files.

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##### ## Connectivity (2)

Mobile SDK

Connects to mobile platforms using a mobile SDK.

Web services APIs

Offers APIs to connect products.

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##### ## Data Type (3)

Structured Data

Provides users the ability to generate synthetic structured data.

Image Data

Provides user the ability to generate synthetic image data.

Data Labeling/Annotation

Can provide accurate annotations for synthesized image data.

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##### ## Data Transformation (5)

Data Utility

Allows user to gain insight and utility into the data.

Data Quality

Provides automated reports of the quality of the synthesized data.

Privacy

Gives user the ability to remove sensitive data from your workflows without sacrificing data utility using techniques such as differential privacy.

Data Formats

Allows for the ingestion of a variety of data formats (e.g. CSV, Hadoop, etc.)

Scale

Has the ability to consume and synthesize large quantities of data effectively and efficiently.

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##### ## Synthesis Type (2)

Full Synthesis

Has capabilities for creating a completely new dataset with no actual data from original dataset.

Partial Synthesis

Can synthesize part of a dataset, leaving in data which is not private or sensitive.

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##### Categories on G2

[Data De-Identification](https://www.g2.com/categories/data-de-identification)[Synthetic Data](https://www.g2.com/categories/synthetic-data)

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