Best Test Data Management Tools for Small Business

Parasoft's mission is to provide automated testing solutions and expertise that empower organizations to expedite delivery of safe and reliable software. A powerful unified C and C++ test automation solution for static analysis, unit testing and structural code coverage, Parasoft C/C++test helps satisfy compliance with industry functional safety and security requirements for embedded software systems.

QATTS stands out as the industry's most all-encompassing provider of cloud-based test automation solutions from start to finish. We guarantee the exceptional quality of your software applications and products through our customizable and ready-to-use automation testing offerings. Our team consists of experienced QA analysts, automation test engineers, and other IT specialists who collaborate closely to ensure timely delivery of dependable services and immediate results. With expertise in both manual and automated testing, our QA professionals are skilled in utilizing the latest web, desktop, and mobile technologies, along with a variety of testing tools. Our in-depth understanding of automation trends has established us as the ultimate destination for all your test automation requirements, including RESTful and SOAP-based web services, as well as IBM, Attachmate, and Hummingbird emulators. We are committed to continuously evolving our services to meet the ever-changing demands of the industry and our clients.

IRI RowGen generates rows ... billions of rows of safe, intelligent test data in database, flat-file, and formatted report targets ... using metadata, not data. RowGen synthesizes and populates accurate, relational test data with the same characteristics of production data. RowGen uses the metadata you already have (or create on the fly) to randomly generate structurally and referentially correct test data, and/or randomly select data from real sets. RowGen lets you customize data formats, volumes, ranges, distributions, and other properties on the fly or with re-usable rules that support major goals like application testing and subsetting. RowGen uses the IRI CoSort engine to deliver the fastest generation, transformation, and bulk-load movement of big test data on the market. RowGen was designed by data modeling, integration, and processing experts to save time and energy in the creation of perfect, compliant test sets in production and custom formats. With RowGen, you can produce and provision safe, smart, synthetic test data for: DevOps, DB, DV, and DW prototypes, demonstrations, application stress-testing, and benchmarking -- all without needing production data.

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

ERBuilder Data Modeler, a GUI data modeling tool, allows developers to visualize, design and model databases using entity relationship diagrams. It automatically generates the most common SQL databases. Share the data model documentation with your team. You can optimize your data model with advanced features like schema comparison, schema synchronization, and test data generation.

IRI FieldShield® is a powerful and affordable data discovery and de-identification package for masking PII, PHI, PAN and other sensitive data in structured and semi-structured sources. Front-ended in a free Eclipse-based design environment, FieldShield jobs classify, profile, scan, and de-identify data at rest (static masking). Use the FieldShield SDK or proxy-based application to secure data in motion (dynamic data masking). The usual method for masking RDB and other flat files (CSV, Excel, LDIF, COBOL, etc.) is to classify it centrally, search for it globally, and automatically mask it in a consistent way using encryption, pseudonymization, redaction or other functions to preserve realism and referential integrity in production or test environments. Use FieldShield to make test data, nullify breaches, or comply with GDPR. HIPAA. PCI, PDPA, PCI-DSS and other laws. Audit through machine- and human-readable search reports, job logs and re-ID risks scores. Optionally mask data when you map it; FieldShield functions can also run in IRI Voracity ETL and federation, migration, replication, subsetting, and analytic jobs. To mask DB clones run FieldShield in Windocks, Actifio or Commvault. Call it from CI/CD pipelines and apps.

Testing and managing test data for IBM i, IBM iSeries, and AS/400 systems requires thorough validation of complex applications, extending down to the underlying data. TestBench for IBM i offers a robust and reliable solution for test data management, verification, and unit testing, seamlessly integrating with other tools to ensure overall application quality. Instead of duplicating the entire live database, you can focus on the specific data that is essential for your testing needs. By selecting or sampling data while maintaining complete referential integrity, you can streamline the testing process. You can easily identify which fields require protection and employ various obfuscation techniques to safeguard your data effectively. Additionally, you can monitor every insert, update, and delete action, including the intermediate states of the data. Setting up automatic alerts for data failures through customizable rules can significantly reduce manual oversight. This approach eliminates the tedious save and restore processes and helps clarify any inconsistencies in test results that stem from inadequate initial data. While comparing outputs is a reliable way to validate test results, it often involves considerable effort and is susceptible to mistakes; however, this innovative solution can significantly reduce the time spent on testing, making the entire process more efficient. With TestBench, you can enhance your testing accuracy and save valuable resources.

It can quickly generate data based on table names, column specifications, field sizes, data types, and other predefined constraints. These generators can easily be tailored to suit your specific needs. You can produce substantial amounts of data within just a few clicks in SQL Server Management Studio. The system allows for column-aware data generation, enabling the creation of data in one column that depends on the values in another. Users benefit from enhanced flexibility and manual oversight when crafting foreign key data. Custom generators that can be shared with your team are also available, allowing you to save regular expressions and SQL statement generators for collaborative use. Furthermore, you can write your own generators in Python, giving you the ability to create any additional data required. With seeded random data generation, you can ensure that the same dataset is produced consistently each time. Moreover, foreign key support helps maintain data consistency across various tables, making the process even more efficient and reliable. This versatility in data generation significantly streamlines workflows and enhances productivity for database management tasks.

Database design, implementation, debugging of stored routines, generation of test data, auditing, logging of data changes, performance monitoring, data transfers, and the import/export of data are essential DBA tasks that facilitate effective reporting, performance testing, and database release management. An advanced test data generation tool creates realistic data for integration into databases or data files, enhancing testing accuracy. Additionally, the only all-encompassing and current monitoring tool for Firebird servers is available in the market today. Database Workbench provides a unified development platform that supports various database engines, equipped with engine-specific features, robust tools, and a user-friendly interface that boosts productivity from the outset. This makes it an invaluable asset for developers looking to streamline their workflow and enhance their database management capabilities.

Creating a valuable UI prototype can be challenging without performing actual API requests. Engaging in real requests helps identify issues related to application flow, timing, and API structure at an early stage, which ultimately enhances both user experience and API quality. With Mockaroo, you have the ability to create customized mock APIs, giving you control over URLs, responses, and error scenarios. By working on UI and API development simultaneously, you can accelerate your application delivery and enhance its overall quality. Numerous excellent data mocking libraries exist for nearly every programming language and platform; however, not everyone is a developer or has the time to familiarize themselves with a new framework. Mockaroo simplifies the process by enabling you to quickly download extensive amounts of randomly generated test data tailored to your specifications, which can then be easily imported into your testing environment using formats like SQL or CSV. This flexibility not only streamlines your workflow but also ensures that your testing processes are robust and efficient.

Datanamic Data Generator serves as an impressive tool for developers, enabling them to swiftly fill databases with thousands of rows of relevant and syntactically accurate test data, which is essential for effective database testing. An empty database does little to ensure the proper functionality of your application, highlighting the need for appropriate test data. Crafting your own test data generators or scripts can be a tedious process, but Datanamic Data Generator simplifies this task significantly. This versatile tool is beneficial for DBAs, developers, and testers who require sample data to assess a database-driven application. By making the generation of database test data straightforward and efficient, it provides an invaluable resource. The tool scans your database, showcasing tables and columns along with their respective data generation configurations, and only a few straightforward entries are required to produce thorough and realistic test data. Moreover, Datanamic Data Generator offers the flexibility to create test data either from scratch or by utilizing existing data, making it even more adaptable to various testing needs. Ultimately, this tool not only saves time but also enhances the reliability of your application through comprehensive testing.

DataLark is an SAP-centric data management platform that helps enterprises migrate, maintain, and integrate business-critical data on-premise and in the cloud more quickly, securely, and cost-effectively using its extensible plugins and connectivities. The DataLark platform works across a wide range of industries and types of enterprise data. Solutions: -Data Management -ERP -Data Validation and Profiling -Data Integration

The IRI Data Manager suite from IRI, The CoSort Company, provides all the tools you need to speed up data manipulation and movement. IRI CoSort handles big data processing tasks like DW ETL and BI/analytics. It also supports DB loads, sort/merge utility migrations (downsizing), and other data processing heavy lifts. IRI Fast Extract (FACT) is the only tool that you need to unload large databases quickly (VLDB) for DW ETL, reorg, and archival. IRI NextForm speeds up file and table migrations, and also supports data replication, data reformatting, and data federation. IRI RowGen generates referentially and structurally correct test data in files, tables, and reports, and also includes DB subsetting (and masking) capabilities for test environments. All of these products can be licensed standalone for perpetual use, share a common Eclipse job design IDE, and are also supported in IRI Voracity (data management platform) subscriptions.

Data management software is predominantly utilized by enterprise business teams, necessitating a design that prioritizes user-friendliness, automation, and intelligence. Furthermore, it is essential for the software to comply with a variety of industry-specific regulations and data protection mandates. To ensure that business teams can make informed, data-driven strategic decisions, the data must maintain standards of adequacy, accuracy, consistency, high quality, and secure accessibility. The software promotes an integrated methodology for managing data privacy, ensuring data quality, overseeing test data management, facilitating data analytics, and supporting data modeling. Additionally, it effectively manages escalating data volumes through a service engine-based architecture, while also addressing specialized data processing needs beyond standard functionalities via a user-defined function framework and Python adapter. Moreover, it establishes a streamlined governance framework that focuses on data privacy and quality management, enhancing overall data integrity. As a result, organizations can confidently rely on this software to support their evolving data requirements.

The EMS Data Generator for MySQL is a remarkable application designed to create test data for MySQL database tables, offering options to save and modify scripts. This versatile utility enables users to replicate a production-like database environment, facilitating the simultaneous filling of multiple MySQL tables with test data. Users can specify which tables and columns to target for data generation, establish ranges of values, and create MySQL character fields based on specific patterns. Additionally, it allows for the input of custom value lists or the selection of values through SQL queries, along with tailored generation parameters for each type of field. With its diverse features, the tool simplifies the process of generating MySQL test data effectively. Furthermore, the Data Generator for MySQL includes a user-friendly console application, enabling one-click generation of test data using pre-defined templates. This added functionality streamlines workflows and enhances productivity for database developers.

We assist you in uncovering, generating, and customizing test data while also enabling you to visualize coverage and ensure data security, allowing you to concentrate on development tasks. Automate the generation of masked, tailored, and synthetic data to fulfill your development and testing requirements seamlessly. Quickly pinpoint sensitive data locations by implementing uniform masking across various databases. Enhance testers’ productivity by storing, expanding, sharing, and reusing test datasets effectively. Deliver smaller datasets to lessen infrastructure demands and enhance overall performance. Employ our extensive range of masking methods to ensure consistent data protection across all applications. Provide support for packaged applications to maintain solution integrity and accelerate deployment processes. Collaborate with risk, compliance, and audit teams to synchronize with data governance strategies. Boost test efficiency by utilizing dependable, trusted production data sets while simultaneously reducing server and storage demands with appropriately sized datasets for each team. This holistic approach not only streamlines the testing process but also fortifies the data management practices of your organization.

Sixpack is an innovative data management solution designed to enhance the creation of synthetic data specifically for testing scenarios. In contrast to conventional methods of test data generation, Sixpack delivers a virtually limitless supply of synthetic data, which aids testers and automated systems in sidestepping conflicts and avoiding resource constraints. It emphasizes adaptability by allowing for allocation, pooling, and immediate data generation while ensuring high standards of data quality and maintaining privacy safeguards. Among its standout features are straightforward setup procedures, effortless API integration, and robust support for intricate testing environments. By seamlessly fitting into quality assurance workflows, Sixpack helps teams save valuable time by reducing the management burden of data dependencies, minimizing data redundancy, and averting test disruptions. Additionally, its user-friendly dashboard provides an organized overview of current data sets, enabling testers to efficiently allocate or pool data tailored to the specific demands of their projects, thereby optimizing the testing process further.

Testing serves as a crucial technical process during product development, manufacturing, and maintenance. It significantly contributes to enhancing product performance, prolonging product lifespan, elevating product quality, and managing expenses effectively. Despite its importance, many enterprises find themselves with a vast amount of unorganized test data that remains underutilized. The challenge lies in how to efficiently manage and structure this diverse and complex test data, which poses a significant hurdle for test managers. Additionally, the rational allocation of testing resources, optimal utilization of test benches and equipment, and the standardization of testing procedures are essential to ensure both accuracy and efficiency, yet these issues often hinder the overall testing capabilities and efficiency within the organization. In light of these challenges faced by companies in their testing operations, the Test Data Management (TDM) system was developed to provide a comprehensive solution. This system aims to streamline the testing process and enhance overall productivity.

Our software is designed to efficiently manage the megabytes to terabytes worth of Product Quality and Test Data in any format that comes from R&D, Supply Chain, Repair, and Manufacturing Environments. Our dedicated and talented team has more than 100 years of combined experience. They have been working with Fortune 1000 companies in Aerospace & Defense and Consumer Electronics and Industrial Device industries since 2006.

In today's fast-paced Agile DevOps environment, teams are increasingly required to enhance their speed and efficiency. BMC Compuware File-AID offers a versatile solution for file and data management across various platforms, allowing developers and QA personnel to swiftly and easily retrieve essential data and files without the need for exhaustive searches. This results in developers spending significantly less time on data management tasks and more time focused on creating new features and addressing production issues. By optimizing your test data, you can confidently implement code modifications without worrying about unforeseen effects. File-AID supports all standard file types, regardless of record length or format, facilitating seamless application integration. Additionally, it aids in comparing data files or objects, streamlining the process of validating test results. Users can also reformat existing files with ease, eliminating the need to start from the ground up. Furthermore, it supports the extraction and loading of relevant data subsets from various databases and files, enhancing overall productivity and effectiveness.

Locate, construct, oversee, and distribute test data to all members of your team with Test Data Manager, which aids in tackling data privacy and compliance challenges linked to regulatory requirements and company policies. The TDM Discovery and Profiling tool enables the detection of personally identifiable information (PII) from various data sources, while a heat map categorizes this information based on its level of severity. Furthermore, test data engineers and compliance specialists can evaluate and label the data for appropriate action. Detailed reports can be produced in PDF format, providing evidence of compliance for stakeholders. This comprehensive approach not only enhances data management but also instills confidence in compliance efforts across the organization. By utilizing Test Data Manager, teams can ensure they remain vigilant and proactive regarding data privacy concerns.

The BiG EVAL solution platform offers robust software tools essential for ensuring and enhancing data quality throughout the entire information lifecycle. Built on a comprehensive code foundation, BiG EVAL's data quality management and testing software provides high performance and flexibility for effective data validation. The features included are developed from real-world experience gained through collaboration with clients. Maintaining high data quality across the life cycle of your information is a vital aspect of data governance, significantly impacting the business value derived from your data. To facilitate this, the automation solution BiG EVAL DQM assists in all aspects of data quality management. Continuous quality assessments validate your organization's data, delivering quality metrics and helping to address any quality challenges that arise. Additionally, BiG EVAL DTA enables the automation of testing tasks within your data-centric projects, streamlining the process further. With these solutions, organizations can maximize their data's integrity and reliability effectively.

Tonic provides an automated solution for generating mock data that retains essential features of sensitive datasets, enabling developers, data scientists, and sales teams to operate efficiently while ensuring confidentiality. By simulating your production data, Tonic produces de-identified, realistic, and secure datasets suitable for testing environments. The data is crafted to reflect your actual production data, allowing you to convey the same narrative in your testing scenarios. With Tonic, you receive safe and practical data designed to emulate your real-world data at scale. This tool generates data that not only resembles your production data but also behaves like it, facilitating safe sharing among teams, organizations, and across borders. It includes features for identifying, obfuscating, and transforming personally identifiable information (PII) and protected health information (PHI). Tonic also ensures the proactive safeguarding of sensitive data through automatic scanning, real-time alerts, de-identification processes, and mathematical assurances of data privacy. Moreover, it offers advanced subsetting capabilities across various database types. In addition to this, Tonic streamlines collaboration, compliance, and data workflows, delivering a fully automated experience to enhance productivity. With such robust features, Tonic stands out as a comprehensive solution for data security and usability, making it indispensable for organizations dealing with sensitive information.

Effectively managing data throughout its lifecycle enables organizations to better achieve their business objectives while minimizing potential risks. It is essential to archive data from obsolete applications and past transaction records, ensuring that access remains available for compliance-related queries and reporting. By scaling data across various applications, databases, operating systems, and hardware platforms, organizations can enhance the security of their testing environments, speed up release cycles, and lower costs. Without proper data archiving, the performance of critical enterprise systems can suffer significantly. Addressing data growth directly at the source not only boosts efficiency but also reduces the risks tied to managing structured data over time. Additionally, safeguarding unstructured data within testing, development, and analytics environments across the organization is crucial for maintaining operational integrity. Ultimately, the absence of a robust data archiving strategy can hinder the effectiveness of vital business systems. Taking proactive steps to manage data effectively is key to fostering a more agile and resilient enterprise.

Implementing standardized testing and data management practices within a division or organization can prove to be a challenging and lengthy endeavor. To ensure data accuracy and facilitate the successful implementation of extensive projects, numerous companies conduct data quality assurance assessments prior to launching initiatives in field force automation or enterprise asset management. Doble offers a variety of data-centric solutions designed to minimize manual tasks and redundant workflows, enabling you to streamline the collection, storage, and organization of your asset testing information. Additionally, Doble is equipped to offer clients comprehensive supervisory services for data governance project management, promoting effective data management methodologies. For further assistance, reach out to your Doble Representative to access self-help resources and further training opportunities. Moreover, the Doble Database enhances robust data governance by systematically capturing data and securely backing up files within a well-structured network folder system. This structured approach not only safeguards data but also facilitates easy retrieval and organization.