DATPROF
Test Data Management solutions like data masking, synthetic data generation, data subsetting, data discovery, database virtualization, data automation are our core business.
We see and understand the struggles of software development teams with test data. Personally Identifiable Information? Too large environments? Long waiting times for a test data refresh? We envision to solve these issues:
- Obfuscating, generating or masking databases and flat files;
- Extracting or filtering specific data content with data subsetting;
- Discovering, profiling and analysing solutions for understanding your test data,
- Automating, integrating and orchestrating test data provisioning into your CI/CD pipelines and
- Cloning, snapshotting and timetraveling throug your test data with database virtualization.
We improve and innovate our test data software with the latest technologies every single day to support medium to large size organizations in their Test Data Management.
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IBM Databand
Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems.
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QuerySurge
QuerySurge leverages AI to automate the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Apps/ERPs with full DevOps functionality for continuous testing.
Use Cases
- Data Warehouse & ETL Testing
- Hadoop & NoSQL Testing
- DevOps for Data / Continuous Testing
- Data Migration Testing
- BI Report Testing
- Enterprise App/ERP Testing
QuerySurge Features
- Projects: Multi-project support
- AI: automatically create datas validation tests based on data mappings
- Smart Query Wizards: Create tests visually, without writing SQL
- Data Quality at Speed: Automate the launch, execution, comparison & see results quickly
- Test across 200+ platforms: Data Warehouses, Hadoop & NoSQL lakes, databases, flat files, XML, JSON, BI Reports
- DevOps for Data & Continuous Testing: RESTful API with 60+ calls & integration with all mainstream solutions
- Data Analytics & Data Intelligence: Analytics dashboard & reports
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iCEDQ
iCEDQ is a DataOps platform for testing and monitoring. iCEDQ is an agile rules engine for automated ETL Testing, Data Migration Testing, and Big Data Testing. It improves the productivity and shortens project timelines of testing data warehouse and ETL projects with powerful features. Identify data issues in your Data Warehouse, Big Data and Data Migration Projects. Use the iCEDQ platform to completely transform your ETL and Data Warehouse Testing landscape by automating it end to end by letting the user focus on analyzing and fixing the issues. The very first edition of iCEDQ designed to test and validate any volume of data using our in-memory engine. It supports complex validation with the help of SQL and Groovy. It is designed for high-performance Data Warehouse Testing. It scales based on the number of cores on the server and is 5X faster than the standard edition.
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