Certified QA Professionals
Effectively managing test data can be the bane of any tester’s day. Another type of tool in the QA professional’s arsenal is test data management tools. These applications can generate synthetic data, perform data profiling, extract and scramble data, and refresh data. By using these tools, testers can be more efficient in their testing as well as protect sensitive information. Data storage requirements are reduced along with the normally lengthy database copying and manual data creation. Below are the test data management tools QA Mentor professionals use most often for projects large and small that use our Test Data Management Services.
Datamaker is the world’s most powerful synthetic Test Data Generation tool, allowing you to use synthetic test data creation techniques to make exactly the data you need to fully test your applications, faster! Using intelligent data profiling techniques, Datamaker is able to understand how your data is related, then create synthetic test data – which contains all of the characteristics of ‘live data’, but without the sensitive content – to enhance your existing data. This enables you to quickly make the data you need, rather than making the best out of what production offers. The result is more efficient test cycles, which enable you to detect defects earlier and produce quality software quickly.
IBM – InfoSphere Optim Test Data Management
Optimize and automate test data management to reduce cost, accelerate application delivery and lower risk. IBM InfoSphere Optim Test Data Management optimizes and automates the test data management process. Prebuilt workflows and services on demand facilitate continuous testing and Agile software development. IBM InfoSphere Optim Test Data Management helps development and testing teams use realistic, right-sized test databases or data warehouses to accelerate application development. InfoSphere Optim Test Data Management helps organizations to Streamline test data management processes to help reduce costs and speed application delivery.
LISA Solutions for Test Data Management
Test Data Management (TDM) represents a significant challenge for many QA and development teams resulting in time-consuming manual testing efforts, excessive costs and slipped delivery dates. LISA can automate the creation and management of test data by capturing and manipulating virtualized datasets from messaging streams and data sources. These unique capabilities help eliminate test data conflicts between teams and drives lower costs and manual effort.
HP Test Data Management
Discover how HP Test Data Management solution can help you accelerate test data management through rapid data preparation, sub-setting and masking. HP Test Data Management dramatically reduces time spent on test data preparation for testing and empowers your QA team and your overall IT organization to streamline application testing and mitigate the risk of compliance breeches. This holistic HP Test Data Management solution automates test data preparation and masking on a single platform and empowers QA teams to independently generate, scramble, and refresh test data—enabling them to generate test data faster and more frequently and to have test data masked and scrambled right from the first extraction.
Informatica Products for Test Data Management
Data Subset -Creates database subsets from large, complex databases to better manage nonproduction systems.
Data Masking -Secures sensitive or confidential data in production and nonproduction systems.
The Informatica solution for test data management enables your IT organization to create functionally intact, secure test data subsets of database applications. IT organizations supporting database applications often make multiple copies of production environments for development, testing, and training. However, as production databases grow, so do the copies, eating up costly storage space and system resources and putting companies at risk for financial penalties due to data breaches. With the Informatica solution for test data management, companies can avoid:
- Excessive data management costs
- Ineffective compliance with privacy regulations
- Loss of reputation, customers, and revenues due to a data breach
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