--- description: Enterprise Test Data : avantages et inconvénients. Lisez les avis clients, consultez les prix et découvrez les fonctionnalités. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: Enterprise Test Data - Avis, notes, prix et abonnements - Capterra Canada 2026 --- Breadcrumb: [Accueil](/) > [Outils MDM (Master Data Management)](/directory/31019/master-data-management/software) > [Enterprise Test Data](/software/197661/test-data-automation) # Enterprise Test Data Canonical: https://fr.capterra.ca/software/197661/test-data-automation Page : 1/2\ Suivant: [Page suivante](https://fr.capterra.ca/software/197661/test-data-automation?page=2) > Un ensemble d'outils de TDM de pointe qui combine la recherche, la création et la préparation précise de données pour chaque test. > > Conclusion : 28 utilisateurs lui ont donné la note de **4.5/5**. Figure au meilleur classement pour **Probabilité de recommander le produit**. ----- ## Présentation ### Qui utilise Enterprise Test Data? Les équipes des opérations préparent les données rapidement à l'aide d'outils avancés. Les testeurs intègrent ensuite les processus réutilisables dans les tests automatisés et les pipelines CI/CD, tandis que les données de test conformes facilitent la tâche des DPO (Data Protection Officer). ## Statistiques et notes | Métrique | Notation | En détail | | **Note globale** | **4.5/5** | 28 Avis | | Simplicité | 4.3/5 | D'après l'ensemble des avis | | Support client | 4.5/5 | D'après l'ensemble des avis | | Rapport qualité-prix | 4.5/5 | D'après l'ensemble des avis | | Fonctionnalités | 4.5/5 | D'après l'ensemble des avis | | Pourcentage de recommandation | 90% | (9/10 Probabilité de recommander le produit) | ## À propos du vendeur - **Entreprise**: Curiosity Software Ireland - **Pays**: Bray, Irlande - **Fondé**: 2017 ## Contexte commercial - **Public cible**: 11–50, 51–200, 201–500, 501–1 000, 1 001–5 000, 5 001–10 000, 10 000+ - **Déploiement et plateformes**: Cloud, SaaS, web, Windows (ordinateur), Linux (ordinateur), Windows (sur site), Linux (sur site) - **Langues**: anglais - **Pays disponibles**: Afghanistan, Afrique du Sud, Albanie, Algérie, Allemagne, Andorre, Angola, Anguilla, Antigua-et-Barbuda, Arabie saoudite, Argentine, Arménie, Aruba, Australie, Autriche, Azerbaïdjan, Bahamas, Bahreïn, Bangladesh, Barbade et 208 de plus ## Fonctionnalités - API - Agrégation et publication de données - Alertes/Notifications - Analyse ad hoc - Analyse en libre-service - Analyse prédictive - Analyse visuelle - Cartographie des relations - Compatible avec divers languages de programmation - Connecteurs de données - Contrôles/Permissions d'accès - Conversion de bases de données - Créateur de requêtes - Création de tableaux de bord - Data discovery - ETL - Extract Transfer Load - Extraction d'images - Extraction de courriels - Extraction de documents - Extraction de données - Extraction de données web - Extraction de numéros de téléphone - Extraction des prix - Gestion des métadonnées - Identification des données sensibles - Importation et exportation de données - Intelligence artificielle et apprentissage automatique - Intégration de données - Mappage de données - Migration de données - Outils de collaboration - Prise en charge des bases de données - Profilage de données - Préparation des données en libre-service - Publishing/Sharing - Rapports et analyses - Rapports et statistiques - Recherche/Filtre - Réplication de données - Saisie et transfert de données - Sauvegarde et récupération - Sources de données multiples - Synchronisation de données - Tableau de bord - Transformation des données - Visualisation de données ## Intégrations (113 au total) - ADP DataCloud - Adobe Commerce - Airtable - Amazon DynamoDB - Amazon S3 - Apache JMeter - Apache Kafka - Appium - Applitools - Asana - Avalara - Azure Active Directory External Identities - Azure Data Catalog - Azure DevOps Server - Azure Synapse Analytics ... et 98 intégrations supplémentaires ## Ressources d'aide - Service client/courriel - FAQ/forums - Base de connaissances - Support téléphonique - Chat/Clavardage ## Category - [Outils MDM (Master Data Management)](https://fr.capterra.ca/directory/31019/master-data-management/software) ## Catégories connexes - [Logiciels de surveillance de bases de données](https://fr.capterra.ca/directory/31775/database-monitoring/software) - [Logiciels de catalogue des données](https://fr.capterra.ca/directory/33716/data-catalog/software) - [Logiciels d'extraction de données](https://fr.capterra.ca/directory/30619/data-extraction/software) - [Outils MDM (Master Data Management)](https://fr.capterra.ca/directory/31019/master-data-management/software) - [Logiciels d'analyse de données](https://fr.capterra.ca/directory/31077/data-analysis/software) ## Logiciels similaires 1. [SAS Viya](https://fr.capterra.ca/software/1043140/sas-viya) — 4.4/5 (12 reviews) 2. [Vantage](https://fr.capterra.ca/software/133231/teradata-database) — 4.3/5 (25 reviews) 3. [Tableau](https://fr.capterra.ca/software/77260/tableau) — 4.6/5 (2348 reviews) 4. [AWS for Data](https://fr.capterra.ca/software/1029723/aws-cloud-databases) — 4.9/5 (7 reviews) 5. [Google Cloud](https://fr.capterra.ca/software/170983/google-cloud-platform) — 4.7/5 (2262 reviews) ## Avis ### "Integration with difficult to access mainframe resources" — 5.0/5 > **John** | *31 décembre 2019* | Services et technologies de l'information | Taux de recommandation : 9.0/10 > > **Avantages**: We found the software extremely flexible in allowing us to set up various techniques to automate our data generation. In fact we couldn't find a use case that we couldn't manage to cover. While the access to standard data sources was great, what most impressed us was the ability to access difficult mainframe data sources such as VSAM, IMS and DB2 and we were even able to generate data into a CICS program and an MQ queue. We haven't seen that flexibility with other software. > > **Inconvénients**: It was a little finicky to get up and runing in house but with excellent support, we got there \! > > With the advent of GDPR within the EU it's imperative that we clean up our datasets and this tool which generates functionally and logically accurate data which represents no real person is ideal for this and particularly on our mainframe systems. ----- ### "The Software you Need to Test your Business IT Systems" — 5.0/5 > **Albert** | *28 novembre 2022* | Art/artisanat | Taux de recommandation : 7.0/10 > > **Avantages**: The IT system of our organization has been one of our greatest capital investment. Before going live with this new system, we decided to implement Test Modeller to test the effectiveness of the system and we are grateful that we did so as the software was able to detect certain problems, bugs and errors that were present in the system which would have caused a lot of problems if we had implemented it without testing it. We recommend Test Modeller to any business. > > **Inconvénients**: A small suggestion would be for the software to have a more informative user manual to understand how the software really works as it may be a bit overwhelming for a person with a lack of IT knowledge. > > The experience has been great. The software has helped us test our new system which we implemented and it was very effective in detecting problems. ----- ### "Video Tutorial" — 3.0/5 > **Jerome** | *22 mars 2019* | Services et technologies de l'information | Taux de recommandation : 5.0/10 > > **Avantages**: It seems good to watch this video tutorial. Its easy way to under stand the flow like how to create and how to map the values etc.. Total I would rate this VIP to 3/5 > > **Inconvénients**: Must have all videos with full set like how to add test data. for instance: I have tried to create an automates script with this modular with the help of the video and one point I have created and mapped the variable and generated the script. but we don't know how to run. late we became to know to use the server but we didn't see the such a explanation from the videos. we would suggest to explain with set of video. > > fine ----- ### "Ultimate Toolkit for Intelligent Automation (AIOps) / GATED AI testing" — 5.0/5 > **Jonathon** | *16 avril 2019* | Vente au détail | Taux de recommandation : 10.0/10 > > **Avantages**: Ease of use, SaaS based modelling (MBT) capabilities, powerful robotic process automation (RPA), synthetic data generation across the platform, automatic generation of functional / non-functional artefacts (e.g. selenium, restassured, taurus, wiremock), extensive support for continuous delivery \& deployment (i.e. Jenkins CI/CD) and ChatOps toolchains (i.e. Slack). > > **Inconvénients**: Lack of current support for container technologies (i.e. docker) > > After evaluating a number of different tool vendors, Volo.ai selected Curiosity software as they provide next generation capabilities that leading vendors (i.e. Magic Quadrant) was unable to provide our landscape is testing next generation A.I platforms (e.g. Neo4J, OpenCV, Kafka / Zookeeper, MongoDB, VectorFlow) which other vendors had limited native support for any of these technologies. The ability to generate A.I. ready test data lakes to help train and prove our algorithms and the ability to provide test data coverage and built in code dependency analysis was a game changer. ----- ### "Outstanding tool for test automation" — 5.0/5 > **Tord** | *29 janvier 2021* | Assurance | Taux de recommandation : 10.0/10 > > **Avantages**: Visual modelling generally reveals more test cases by showing which paths through the system under test are being visited. Testers and other stakeholders can easily do the modelling while engineers overlay the automation. Complex applications can be broken down to manageable models in a hierarchy Great connectivity to test frameworks and other applications. > > **Inconvénients**: Some of our requirements (Cypress, Docker) gave some challenges, but with very good support from the vendor it all came to work well. > > TestModeller is an outstanding tool for test automation and test data management. We have run a PoC for 6 months using an on-premise installation (in Azure), utilizing the Cypress framework. Tests are run in docker containers when generated from TestModeller and updated to Gitlab. Also, the ability to separate models and generated tests from the functional representation of the elements in the system under test, enables us to generate tests even before code is written to implement an element in the DOM for in-sprint testing. This of course also eliminates the extensive maintenance you normally must conduct to test automation frameworks. ----- Page : 1/2\ Suivant: [Page suivante](https://fr.capterra.ca/software/197661/test-data-automation?page=2) ## Liens - [Afficher sur Capterra](https://fr.capterra.ca/software/197661/test-data-automation) ## Cette page est disponible dans les langues suivantes. | Langue | URL | | de | | | de-AT | | | de-CH | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-IL | | | en-IN | | | en-NZ | | | en-SG | | | en-ZA | | | es | | | es-AR | | | es-CL | | | es-CO | | | es-CR | | | es-DO | | | es-EC | | | es-MX | | | es-PA | | | es-PE | | | fr | | | fr-BE | | | fr-CA | | | fr-LU | | | it | | | nl | | | nl-BE | | | pl | | | pt | | | pt-PT | | | sv | | ----- ## Données structurées