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Description
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
Description
The Synthetic Data Vault (SDV) is a comprehensive Python library crafted for generating synthetic tabular data with ease. It employs various machine learning techniques to capture and replicate the underlying patterns present in actual datasets, resulting in synthetic data that mirrors real-world scenarios. The SDV provides an array of models, including traditional statistical approaches like GaussianCopula and advanced deep learning techniques such as CTGAN. You can produce data for individual tables, interconnected tables, or even sequential datasets. Furthermore, it allows users to assess the synthetic data against real data using various metrics, facilitating a thorough comparison. The library includes diagnostic tools that generate quality reports to enhance understanding and identify potential issues. Users also have the flexibility to fine-tune data processing for better synthetic data quality, select from various anonymization techniques, and establish business rules through logical constraints. Synthetic data can be utilized as a substitute for real data to increase security, or as a complementary resource to augment existing datasets. Overall, the SDV serves as a holistic ecosystem for synthetic data models, evaluations, and metrics, making it an invaluable resource for data-driven projects. Additionally, its versatility ensures it meets a wide range of user needs in data generation and analysis.
API Access
Has API
API Access
Has API
Integrations
Amazon Redshift
Amazon S3
Apache Cassandra
Dropbox
Elastic
Google Drive
MongoDB
MySQL
Neo4j
PostgreSQL
Integrations
Amazon Redshift
Amazon S3
Apache Cassandra
Dropbox
Elastic
Google Drive
MongoDB
MySQL
Neo4j
PostgreSQL
Pricing Details
Starter Plan : Always free
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Cloud Innovation Partners
Founded
2016
Country
United Kingdom
Website
www.cloudtdms.com
Vendor Details
Company Name
DataCebo
Website
sdv.dev/
