Best Synthetic Data Generation Tools in China

Windocks provides on-demand Oracle, SQL Server, as well as other databases that can be customized for Dev, Test, Reporting, ML, DevOps, and DevOps. Windocks database orchestration allows for code-free end to end automated delivery. This includes masking, synthetic data, Git operations and access controls, as well as secrets management. Databases can be delivered to conventional instances, Kubernetes or Docker containers. Windocks can be installed on standard Linux or Windows servers in minutes. It can also run on any public cloud infrastructure or on-premise infrastructure. One VM can host up 50 concurrent database environments. When combined with Docker containers, enterprises often see a 5:1 reduction of lower-level database VMs.

With automated data quality profiling, and synthetic data generation, adopting data-centric AI is easier than ever. We help data scientists unlock the full potential of data. YData Fabric enables users to easily manage and understand data assets, synthetic data, for fast data access and pipelines, for iterative, scalable and iterative flows. Better data and more reliable models delivered on a large scale. Automated data profiling to simplify and speed up exploratory data analysis. Upload and connect your datasets using an easy-to-configure interface. Synthetic data can be generated that mimics real data's statistical properties and behavior. By replacing real data with synthetic data, you can enhance your datasets and improve your models' efficiency. Pipelines can be used to refine and improve processes, consume data, clean it up, transform your data and improve its quality.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

Statice is a data anonymization tool that draws on the most recent data privacy research. It processes sensitive data to create anonymous synthetic datasets that retain all the statistical properties of the original data. Statice's solution was designed for enterprise environments that are flexible and secure. It incorporates features that guarantee privacy and utility of data while maintaining usability.

CloudTDMS, your one stop for Test Data Management. Discover & Profile your Data, Define & Generate Test Data for all your team members : Architects, Developers, Testers, DevOPs, BAs, Data engineers, and more ... Benefit from CloudTDMS No-Code platform to define your data models and generate your synthetic data quickly in order to get faster return on your “Test Data Management” investments. CloudTDMS automates the process of creating test data for non-production purposes such as development, testing, training, upgrading or profiling. While at the same time ensuring compliance to regulatory and organisational policies & standards. CloudTDMS involves manufacturing and provisioning data for multiple testing environments by Synthetic Test Data Generation as well as Data Discovery & Profiling. CloudTDMS is a No-code platform for your Test Data Management, it provides you everything you need to make your data development & testing go super fast! Especially, CloudTDMS solves the following challenges : -Regulatory Compliance -Test Data Readiness -Data profiling -Automation

SKY ENGINE AI is a simulation and deep learning platform that generates fully annotated, synthetic data and trains AI computer vision algorithms at scale. The platform is architected to procedurally generate highly balanced imagery data of photorealistic environments and objects and provides advanced domain adaptation algorithms. SKY ENGINE AI platform is a tool for developers: Data Scientists, ML/Software Engineers creating computer vision projects in any industry. SKY ENGINE AI is a Deep Learning environment for AI training in Virtual Reality with Sensors Physics Simulation & Fusion for any Computer Vision applications.

KopiKat, a revolutionary tool for data augmentation, improves the accuracy and efficiency of AI models by modifying the network architecture. KopiKat goes beyond the standard methods of data enhancement by creating a photorealistic copy while preserving all data annotations. You can change the original image's environment, such as the weather, seasons, lighting, etc. The result is an extremely rich model, whose quality and variety are superior to those created using traditional data augmentation methods.

dbForge Data Generator is a powerful GUI tool that populates Oracle schemas with realistic test data. The tool has an extensive collection 200+ predefined and customizeable data generators for different data types. It delivers flawless and fast data generation, including random number generation, in an easy-to-use interface. The latest version of Devart's product is always available on their official website.

dbForge Data generator for MySQL is an advanced GUI tool that allows you to create large volumes of realistic test data. The tool contains a large number of predefined data generation tools with customizable configuration options. These allow you to populate MySQL databases with meaningful data.

Mask, generate, subset, virtualize, and automate your test data with the DATPROF Test Data Management Suite. Our solution helps managing Personally Identifiable Information and/or too large databases. Long waiting times for test data refreshes are a thing of the past.

Datanamic Data Generator allows developers to quickly populate databases with thousands upon rows of meaningful, syntactically correct data for database testing purposes. A blank database is useless for testing your application. Test data is essential. It is difficult to create your own test data generators and scripts. Datanamic Data Generator can help. This tool is available for developers, DBAs, and testers who require sample data to test a database-driven app. Datanamic Data Generator makes it easy to generate database test data. It will read your database and display tables and columns according to their data generation settings. To generate complete (realistic) test data, only a few entries are required. This tool can be used to create test data from scratch, or from existing data.

Create, transform, or analyze any text data within your spreadsheet. Automatically normalize addresses, separate column, extract entities, etc. Rewrite SEO content or blog posts. Generate product description variations. Create synthetic data such as first/last names and phone numbers. Create bullet-point summaries and rewrite content in fewer words. Sort product feedback into categories, prioritize sales leads, find new trends, etc. Charm provides several templates to help people complete common tasks faster. Use the Summarize With Bullet Points Template to create short bullet-point summaries for long content. Use the Translate Language Template to translate existing content in another language.

Our AI-powered platform for data generation allows data analysts and machine-learning engineers to maximize their analytical data sets. Datomize allows users to create the exact analytical data they need by leveraging behavior extracted from existing data. With data that accurately reflects real-world scenarios and allows users to make better decisions, they can now get a more accurate picture of reality. Take advantage of your data to develop AI solutions that are state-of-the art. Datomize's AI powered, generative models create superior synthesized replicas by extracting behavior from your existing datasets. Advanced augmentation tools allow for unlimited resizing, while dynamic validation tools show the similarity of original and replicated data. Datomize's machine learning approach is data-centric and addresses the primary constraints of training high-performing ML model.

Synth is a data-as code tool that offers a simple CLI workflow to generate consistent data in an scalable manner. Synth can be used to generate data that is correct and anonymized, but still looks and sounds like production. Create test data fixtures to support your continuous integration, testing and development. Create data that tells you the story you wish to tell. Specify constraints and relations. Seed development, environments and CI. Anonymize sensitive production data. Create realistic data according to your specifications. Synth's declarative configuration language allows you to specify the entire data model in code. Synth can import existing data and create accurate data models. Synth is database-agnostic and supports semistructured data. It works well with SQL and NoSQL. Synth can generate thousands of semantic types, such as email addresses, credit card numbers and more.

The Synthetic Data vault (SDV) was designed as a Python library that allows you to create tabular synthetic data. The SDV uses machine learning algorithms to emulate patterns in synthetic data. The SDV offers a variety of models, from classical statistical methods to deep learning methods. Create data for single tables or multiple connected tables. Compare the synthetic data with the real data using a variety measures. Diagnose problems and create a quality report for more insights. Control data processing to enhance the quality of synthetic information, choose different types of anonymization and define business rules as logical constraints. Use synthetic data to replace real data or as an enhancement. The SDV is a comprehensive ecosystem of synthetic data models, metrics, and benchmarks.

RNDGen Random Data Generator, a user-friendly tool to generate test data, is free. The data creator customizes an existing data model to create a mock table structure that meets your needs. Random Data Generator is also known as dummy data, csv, sql, or mock data. Data Generator by RNDGen lets you create dummy data that is representative of real-world scenarios. You can choose from a variety of fake data fields, including name, email address, zip code, location and more. You can customize generated dummy information to meet your needs. With just a few mouse clicks, you can generate thousands of fake rows of data in different formats including CSV SQL, JSON XML Excel.

OneView creates next-generation virtual synthetic datasets for ML algorithm training. We provide ready-to-use datasets for all objects in any environment, with a focus on satellite and aerial imagery. VSD is computer-generated, real-like imagery. It can be used to replace real imagery. It is a cost-effective, scalable, and highly accurate training material for ML algorithm. OneView bridges the gap between increasing availability of earth observation data, and the limited ability to use it for intelligence gathering. We provide the tools to improve data analysis and enable geospatial imagery to yield new and valuable insights. It doesn't matter if you have long-tail or rare objects, or if you don't have enough data. We can generate a dataset for every object. We can generate any environment. High-detailed, customized environment for model training.

Our proprietary labeling platform allows us to label your data with higher quality standards in order to meet the requirements of complex AI projects. Now you can create the products that your customers love.

We can no longer rely upon real-life conversations as physical customer interactions shift to digital. Customers communicate their intentions and share their needs using data. Data is a key tool for understanding customers and testing our assumptions. Privacy regulations like GDPR and CCPA make deep understanding more difficult. This gap in customer understanding is bridged by the MOSTLY AI synthetic dataset platform. Businesses can benefit from a reliable, high-quality generator of synthetic data in many different applications. The story doesn't end there. MOSTLY AI's synthetic dataset platform is more versatile than any other synthetic data generator. MOSTLY AI's versatility makes it an indispensable tool for software development and testing. From AI training to explainability and bias mitigation, governance to realistic test data, with subsetting, referential integrity.

A self-service platform for synthetic data, with a focus on object and human data. The Datagen Platform gives you granular control over the data generation process. Analyzing your neural networks can help you understand what data is required to improve them. You can then easily generate the data that you need to train your network. Datagen is a powerful platform that can help you solve your problems. It allows you to generate high-quality, high-variety, domain-specific, simulated artificial data. Advanced capabilities include the ability to simulate dynamic people and objects within their context. Datagen gives CV teams unprecedented flexibility to control visual outcomes in a variety of 3D environments.

Amazon SageMaker lets you identify raw data, such as images, text files and videos. You can also add descriptive labels to generate synthetic data and create high-quality training data sets to support your machine learning (ML). SageMaker has two options: Amazon SageMaker Ground Truth Plus or Amazon SageMaker Ground Truth. These options allow you to either use an expert workforce or create and manage your data labeling workflows. data labeling. SageMaker GroundTruth allows you to manage and create your data labeling workflows. SageMaker Ground Truth, a data labeling tool, makes data labeling simple. It also allows you to use human annotators via Amazon Mechanical Turk or third-party providers.

Share your production data securely with ML, data scientists, and analytics teams, while maintaining customer trust. Stop wasting time with regexes and free models. Private AI anonymizes 50+ entities PII PCI and PHI in 49 languages, with unmatched accuracy, across GDPR, CPRA and HIPAA. Synthetic data can be used to replace PII, PCI and PHI text in order to create model training data that looks exactly like production data. This will not compromise customer privacy. Remove PII in 10+ file formats such as PDFs, DOCXs, PNGs, and audios to protect customer data and comply privacy regulations. Private AI uses the most advanced transformer architectures for remarkable accuracy right out of the box. No third-party processing required. Our technology outperforms every other redaction service available on the market. Please feel free to request a copy of the evaluation toolkit for you to test with your own data.

A flexible and accurate platform for the generation of synthetic data. Create the data you require for your perception system within minutes. Design scenarios with infinite variations for your use case. Create your datasets on the cloud. Anyverse is a scalable software platform that allows you to train, validate or fine-tune a perception system. It offers unparalleled computing power to generate all of the data you require in a fraction the time and cost as compared to other real-world workflows. Anyverse is a modular platform which enables efficient scene creation and dataset production. Anyverse™, Studio is a standalone application with a graphical interface that manages All Anyverse functions including scenario definition, variability setting, asset behavior, dataset settings and inspection. Data is stored on the cloud and the Anyverse cloud is responsible for scene generation, simulation and rendering.

As enterprise data explodes and is scattered across multiple systems, the oversight of privacy, data security and governance has become a very difficult task. Businesses are exposed to significant risks, including data breaches, privacy suits, and penalties. It takes months to find data privacy risks within an organization. A team of data engineers is involved in the effort. Data breaches and privacy legislation are forcing companies to better understand who has access to data and how it is used. Enterprise data is complex. Even if a team works for months to isolate data privacy risks, they may not be able to quickly find ways to reduce them.

Sixpack is an automated data management platform that streamlines synthetic data for testing. Sixpack, unlike traditional test data generation methods, provides an unlimited supply of synthetic data to help testers and automated testing avoid conflicts and resource bottlenecks. It focuses on flexibility, enabling data allocation, pooling and instant generation, while maintaining data quality and privacy. The key features are the ease of setup, seamless integration with APIs, and the support for complex test environments. Sixpack integrates directly into QA processes so that teams can save time managing data dependencies and minimize data overlap. Its dashboard provides a clear view into active data sets. Testers can also allocate or pool data based on project needs.