What's New

• Data Profiling: Enhancing Streams Creation with Intelligent Regression Detection.
• Data Libraries: Introducing new parameters for mathematical distribution providers to enhance versatility.
• Data Generation: Implementing the ability to introduce duplicates and outliers at the Stream level, providing a more robust and realistic data generation process.
• Platform: Enabling 'always save to local' functionality by default for improved user experience (view sample data).

• Data Profiling: Introducing an upgraded profiling report to empower data experts in uncovering intricate patterns and data interconnections for improved synthetic data management.
  • Structure Analysis: A comprehensive assessment of data columns to establish the consistency of specific data attributes.
  • Content Discovery: Focused on data quality, this feature delves deeply into datasets, aiding users in pinpointing anomalies within specific rows and columns.
  • Relationship & Correlation Discovery: This functionality highlights interactions among numerical attributes, facilitating the identification of data relationships and establishing meaningful connections within the data.
• Data Libraries: With immense gratitude to our contributors, we proudly introduce new data libraries tailored for Health tests. This addition significantly expedites the creation of datasets specific to health-related assessments.
• Platform:
  • Addressed a minor issue within the Data Random Float Number Generator.
  • Enriched the data providers with novel date patterns to enhance data diversity.
• UX/UI: Refining the logged-in journey with few nhancements
  • Made few improvements to the logs within the data profiling module.
  • Streamlined workflows management to enhance user experience during data processing.

• Data libraries:Enhance and add more picklists to the Salesforce data library.
• Website:
  • Solutions - Adding 2 new use-cases : Synthetic Data for IoT and Synthetic Data for Telcos.
  • Explore - Adding a new page : Synthetic Data Evolution: Hype Cycle & Adoption Journey.
• Platform:Enhanced Front-End security for newsletter subscription IP throttling.

• Data libraries: Thanks to our contributors, we have been able to add new data libraries to accelerate datasets creation for the following categories
  • Health:
    • drug reviews
    • health facts
    • health human/robot chat
    • medical predictions
    • mental health counseling
    • reddit health posts
  • English:
    • multiple choice Q&A
    • conversation Q&A
    • quotes in English
  • Dev:
    • Maths Q&A
    • Python Q&A
    • SQL Q&A
• UX/UI: Adding newsletter subscription.
• Website: Adding Insurance and Heathcare use-cases (Solutions).

• Foundation Data: Able to read CSV files not properly formatted or having issues.
• Dashboard: Better caching mechanism.
• Platform: Improved email sending mechanism.
• Workflows:
  • When a storage is deactivated, skipping attributes related to that storage.
  • Possibility to view generated data.
• Attributes: Cancel button added.

• Design: A new and enhanced design for the log-in journey has been recently launched, resulting in a significantly improved user experience.
• Platform:
  • Successfully scaled up the platform and made it distributed with more nodes, ensuring seamless performance even with increased user activity.
  • Complete redesign of the logs management in both front-end and backend, providing a user-friendly view for users.
  • Introduced real-time email sending mechanism from the back-end.
• Workflows:
  • Real-time execution, leading to faster execution times of workflows, now measured in mere seconds.
  • Dynamic/real-time status for workflows in the queue.
• Foundation Data: Auto-completion and dynamic configuration of attributes.
• Dashboard: New dashboard with new Key Performance Indicators (KPIs) for improved data visualization.
• Profiling:
  • Adding discard patterns.
  • Dynamic/real-time status for profiling in the queue.
• Data Sources:
  • Auto-completion and dynamic configuration of attributes.
  • Added new data sources: MongoDB & MS-SQL.
  • Possibility to check status of connectivity to external databases while editing & viewing.

Adding deviation parameters as well as decimal places for Math functions.

New design for the anonymous journey has been released improving the user experience.

We are excited to announce that Data Profiling & Discovery feature has been significantly enhanced. You now have the ability to create new streams directly from your connections, including popular databases like MySQL, as well as SaaS platforms such as Salesforce and ServiceNow. These features allows for seamless integration of data from diverse sources into CloudTDMS.
Furthermore, we have upgraded Data Workflows engine to support the creation of data in a specific sequence. This means that you can now easily sort streams just as you would arrange attributes. This improvement was made possible thanks to the valuable feedback and enhancement requests from CloudTDMS users. We truly appreciate their contributions in making our platform even better.

It's live ! After 5 months of beta testing & ongoing enhancements of CloudTDMS, we are thankful to all our beta testers for their outstanding collaboration !

Platform seems to be stable and performaing well, here are the last requested features before we shall go live ! :
- Data sources management
- Local management of Foundation & Reference data

First of all, thanks to all our beta testers for your feedback & active support, it was really apreciated !
CloudTDMS team has been able to make good progress in terms of features requested such as :
- Upload/Download of data-model (creation of streams & attributes from json files)
- Creation of streams & attributes from Profiled Data
- Automatic detection of user’s timezone at creation
- Scheduled Workflows could be now managed with user’s timezone

Thanks to all our beta testers, after the onboarding, you have been able to iditify some minor bugs as well as features requiring some improvements such as :
- data providers with options (Date & time)
- Scheduling of data generation Workflows
- Templates for quick stream creations.
Bugs resolution : last/first name in lower case, Dynamic street addresses, Custom list, Profiling report with missing columns, hints.

Beta release is live now, we are onboarding beta testers.
If you want to try experimental features of CloudTDMS before they’re released, you can join the Beta Testing Programme. As a beta tester, you’ll become an important part of the app’s development.