Tabular Synthetic Data
What is Tabular Synthetic Data
Synthetic data is the data that is synthetically created, typically by applying Artificial Intelligence
Synthetic data is very similar to the real data. It mirrors the statistical properties of the real data. However, none of the record in synthetic data matches with the original real data
Synthetic data is a close proxy for the real data as it has the same patterns and correlations.
A tabular synthetic dataset is the one which is in tabular form as opposed to unstructured images and video data etc.
Why Tabular Synthetic Data
- Synthetic data is safe and fully anonymous. As it is created from scratch using random numbers, original data cannot be re-created from it
- Synthetic data can in fact help in correcting the original real data by way of removing bias, imbalance etc.
- Synthetic data will replace real data. Gartner has predicted that by 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated
- You can generate, use and discard synthetic data as per need or choice. It is as good as original data but at the same time does not contain any sensitive information as it is not real.
How Synthetic Data is generated
- Synthetic data is generated from scratch, typically with the help of AI technology such as GAN.
- Using adversarial learning, GAN model is trained to learn all the structures and patterns in the real data.
- After training, the model is used to generate new synthetic data. This artificially generated data is highly representative, yet completely anonymous.
- It does not contain any one-to-one relationships to actual data
Tabular Synthetic Data - Use Cases
- AI-generated synthetic tabular data can be used for training machine learning models.
- AI-generated synthetic tabular data can be used for test cases preparation in Software Development.
- AI-generated synthetic tabular data can be used for simulating business scenarios, customer behavior etc.
- We can engage with you to understand your data issues and tabular synthetic data requirements
- We can provide consultancy to you to draw strategic roadmap for meeting your tabular synthetic data requirements
- We provide customized solutions for tabular synthetic data generation with high degree of accuracy
Flexibility to choose
- Choice of choosing the synthetic data records to generate. There is technically no upper bound on the synthetic data we can generate
- Choice between cloud-based and on-prem based solution
- Choice of add-on features in synthetic data such as privacy-preserving, fair data, data imbalance handling etc.
- Choice of choosing detail level of validation reports which can be used as validation and evidence for our high-quality synthetic data
- Fair Synthetic Data: We can remove unethical bias in your data based on any attribute such as race, gender, religion etc. while generating the synthetic data without compromising on the quality and accuracy
- Privacy Preserving: We can ensure that the synthetic data so generated is privacy-preserving. That is, original data cannot be derived out of the synthetic data
- Data Imbalance: We can fix data imbalance while generating the synthetic data
- We are a team of industry veterans and research scholars with deep expertise and extensive industry experience
- The AI & Machine Learning unit of our company is exclusively focused on Tabular Synthetic Data Generation and Fair AI giving us distinctive edge in this area of work
- Our business model allow us to remain cost-effective but at the same time deliver high-quality solutions
- Our commitment for on-time and high-quality solutions
- Our global exposure enables us to provide effective solutions across the globe
- https://mostly.ai/((We are doing very similar. However, we do not have any ready platform of product. We provide customizable solution service) )