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Synthetic Data

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Synthetic data is artificial data that is generated from original data and a model that is trained to reproduce the characteristics and structure of the original data. This means that synthetic data and original data should deliver very similar results when undergoing the same statistical analysis. The degree to which synthetic data is an accurate proxy for the original data is a measure of the utility of the method and the model.

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Discover how customized Synthetic Data can improve your software development and debugging processes.

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There are several types of data we provide our clients: “Open Data” vs. “Green Data” vs. “Red Data.”

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Open Data

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refers to data freely available from both academic and government agencies.

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Green Data

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This is Synthetic Data we generate to closely match the specific requirements defined in the metadata (see our Metadata Repository platform for details).

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Red Data

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This is Synthetic Data purposefully created outside of the boundaries and parameters defined in the metadata.

Industries we serve

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Telecom and Infrastructure

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Explore datasets related to telecommunications and infrastructure, including network coverage, broadband accessibility, and infrastructure development metrics.

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Environmental

Utilize environmental datasets covering climate patterns, pollution levels, and ecological metrics.

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Life Sciences and MedTech

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Access comprehensive datasets from trusted sources such as the FDA, ClinicalTrials.gov, and Medicare.

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Finance and Insurance

Access financial and insurance datasets encompassing market trends, economic indicators, and risk assessments.

Geography and population Health

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Leverage geospatial and population health datasets that provide insights into demographic distributions, health disparities, and regional health outcomes.

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Example

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For example: let’s say you need large amounts of Synthetic Data to develop, debug, and demo your EDC (“Electronic Data Capture”) software platform. Here’s how each type of data can be useful to your organization:

First, we define all the data types your software uses into our Metadata Repository (“MDR”). From individual fields up to forms (CRFs) and study definitions (based off Protocols).

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Develop phase

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we generate “Green Data” that matches the specific parameters defined in the MDR. For a particular CRF, we can generate hundreds or even thousands of records that match the exact field structure, field type, and allowed values for each field. For a field “Age”, defined as integer, with a range between 0 and 120, we’ll generate integer values between 0-120 as expected

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Debug / Test phase

we generate “Red Data” that explicitly falls outside the expected values. For the “Age” field we’d generate records with string data as opposed to integers. And with integer values above 120. The goal of using “Red Data” is to verify that the system performs the expected checks and validations.

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Demo phase

your sales team can showcase your software pre-loaded with large amounts of Green Data. Your team will then showcase all areas of your software with realistic, yet totally fake data.

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