Alternatives to Test Data Manager

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.

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.

Mask, generate, subset, virtualize, and automate your test data with the DATPROF Test Data Management Suite. Our solution helps managing Personally Identifiable Information and/or too large databases. Long waiting times for test data refreshes are a thing of the past.

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.

Qualibrate, the cloud solution for SAP & Web Apps test automation, is like Salesforce. It has the power to be simple, customized, and integrate with most CI/CD tools. Test cases can be reused many times and are easy to maintain. It is risky to embark on a journey of software transformation. We offer a simple, yet powerful, solution to reduce risk and implement resources up to 80%. Recording a Business Process is all you have to do: user actions, test data and technical information will all be recorded. This recording will serve as your only source of truth for Automated and Manual tests, as well for Learning. Visit the website to learn more about Qualibrate's innovative approach to SAP and web app testing.

Delphix is the industry leader for DataOps. It provides an intelligent data platform that accelerates digital change for leading companies around world. The Delphix DataOps Platform supports many systems, including mainframes, Oracle databases, ERP apps, and Kubernetes container. Delphix supports a wide range of data operations that enable modern CI/CD workflows. It also automates data compliance with privacy regulations such as GDPR, CCPA and the New York Privacy Act. Delphix also helps companies to sync data between private and public clouds, accelerating cloud migrations and customer experience transformations, as well as the adoption of disruptive AI technologies.

BMC Compuware presents a robust Test Data Management (TDM) solution that integrates technology, expertise, and best practices necessary for fostering a data protection and optimization strategy throughout the organization. By adopting a TDM solution, companies can effectively minimize their risk exposure, boost operational efficiency, and shrink the overall size of their test data, all while achieving cost savings in data management. A fundamental element of this solution is the BMC Compuware Test Data Management Best Practice, which offers essential guidelines for establishing or refining processes that create secure data environments tailored to support IT operations related to data usage and delivery under conditions that mimic production, such as in testing and training scenarios. This approach enables organizations to generate appropriately sized, anonymized, on-demand data sets. Additionally, the solution addresses the various technical, organizational, and political obstacles that may arise when safeguarding proprietary information, ensuring that enterprises can confidently navigate these complexities. Ultimately, this TDM framework not only enhances data security but also promotes a more agile and responsive IT infrastructure.

Oracle Data Guard is designed to provide high availability, protect data, and facilitate disaster recovery for enterprise-level information systems. It offers a robust array of services aimed at creating, managing, and overseeing one or more standby databases, ensuring that production Oracle databases can withstand disasters and prevent data corruption. The platform includes management and monitoring tools that automate the creation and upkeep of synchronized copies of a primary database, thus safeguarding Oracle data against failures, natural disasters, human mistakes, and data corruption, all while ensuring mission-critical applications maintain high availability. Included with Oracle Database Enterprise Edition, Data Guard is an essential feature for many organizations. Moreover, Active Data Guard serves as a licensed extension of Oracle Database Enterprise Edition, introducing advanced functionalities that enhance the core capabilities of Data Guard, thereby providing even greater resilience and operational efficiency. This combination empowers businesses to maintain uninterrupted access to their vital data assets.

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.

Envision extensive arrays of data entities, grasp their interconnections, and fine-tune associated data extractions to formulate ideal test datasets. Facilitate the comparison of files, even those located on different LPARs, thereby enhancing the capability to swiftly and routinely evaluate the repercussions of modifications. Streamline the intricate process of data management and test preparation by allowing developers and test engineers to execute data-related functions without the necessity of programming, scripting, SQL coding, or juggling multiple tools. Empower developers, test engineers, and analysts to achieve greater independence by allowing them to provision data as required, which lessens dependence on subject matter experts. Elevate application quality through improved testing scenarios, making the creation of comprehensive data extracts for testing more straightforward and enabling precise identification of the effects stemming from alterations in data components. By doing so, teams can respond more quickly to changes and enhance their overall productivity.

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

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.

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.

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.

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.

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.

OpenText Data Express manages the test data environment. It improves test results, lowers testing costs, secures customer data against loss or misuse and enables accelerated delivery. Data Express automates generation of test data environments to reduce elapsed times by up to 80%. By masking sensitive data, test data retains the value for testing and keeps it safe from unauthorized uses. Data Express is a repository for test data knowledge. It provides a variety of management tools that allow test managers to control the generation of test data.

The Solix Enterprise Data Management Suite (Solix EDMS) consolidates all necessary tools to implement a successful Information Lifecycle Management (ILM) strategy. Accessible through a single web interface, this platform features top-tier solutions for database archiving, test data management, data masking, and application retirement. Solix EDMS aims to manage expenses, enhance the performance and availability of applications, and fulfill compliance requirements. It provides business users universal access to archived data via full-text searches, structured SQL queries, and various forms and reports. Furthermore, Solix EDMS enables users to swiftly pinpoint rarely accessed historical data from production applications and securely transfer it to an archive while maintaining data integrity and access. The system's retention management feature ensures that archived data remains stored for a specified duration and can be deleted automatically or manually once it complies with the data retention policy. With these capabilities, organizations can streamline their data management processes effectively.

Qlik Gold Client enhances the management of test data in SAP settings by boosting efficiency, cutting costs, and ensuring security. This tool is specifically crafted to remove the need for development workarounds by allowing for the straightforward transfer of configuration, master, and transactional data subsets into testing environments. Users can swiftly define, duplicate, and synchronize transactional data from production systems to non-production targets. It also offers functionality to identify, select, and eliminate non-production data as required. The interface is designed to manage significant and complex data transformations with ease. Additionally, it automates the selection of data and facilitates effortless test data refresh cycles, thereby minimizing the time and effort invested in data management. One of the key features of Qlik Gold Client is its ability to safeguard personally identifiable information (PII) in non-production environments through effective data masking. This masking process utilizes a defined set of rules to "scramble" production data during its replication to non-production settings, thereby ensuring data privacy and compliance. Overall, Qlik Gold Client streamlines the testing process, making it more efficient and secure for organizations.

Enterprise synthetic test data solutions. It is essential that test data accurately reflects the structure of your database or application. This means it must be easy for you to model and maintain each project. Respect the referential integrity of parent/child/sibling relations across data domains within an app database or across multiple databases used for multiple applications. Ensure consistency and integrity of synthetic attributes across applications, data sources, and targets. A customer name must match the same customer ID across multiple transactions simulated by real-time synthetic information generation. Customers need to quickly and accurately build their data model for a test project. GenRocket offers ten methods to set up your data model. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.

As interactions with customers increasingly transition from physical to digital environments, it becomes necessary to move beyond traditional face-to-face conversations. Instead, customers now convey their preferences and requirements through data. Gaining insights into customer behavior and validating our preconceptions about them also relies heavily on data-driven approaches. However, stringent privacy laws like GDPR and CCPA complicate this deep understanding even further. The MOSTLY AI synthetic data platform effectively addresses this widening gap in customer insights. This reliable and high-quality synthetic data generator supports businesses across a range of applications. Offering privacy-compliant data alternatives is merely the starting point of its capabilities. In terms of adaptability, MOSTLY AI's synthetic data platform outperforms any other synthetic data solution available. The platform's remarkable versatility and extensive use case applicability establish it as an essential AI tool and a transformative resource for software development and testing. Whether for AI training, enhancing explainability, mitigating bias, ensuring governance, or generating realistic test data with subsetting and referential integrity, MOSTLY AI serves a broad spectrum of needs. Ultimately, its comprehensive features empower organizations to navigate the complexities of customer data while maintaining compliance and protecting user privacy.

Syntho is generally implemented within our clients' secure environments to ensure that sensitive information remains within a trusted setting. With our ready-to-use connectors, you can establish connections to both source data and target environments effortlessly. We support integration with all major databases and file systems, offering more than 20 database connectors and over 5 file system connectors. You have the ability to specify your preferred method of data synthetization, whether it involves realistic masking or the generation of new values, along with the automated identification of sensitive data types. Once the data is protected, it can be utilized and shared safely, upholding compliance and privacy standards throughout its lifecycle, thus fostering a secure data handling culture.

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.

High-quality test data plays a crucial role in enhancing both application development and testing processes, which is why top-tier development teams often insist on regularly populating their test environments with data sourced from production databases. Typically, a robust Test Data Management (TDM) strategy involves maintaining several full clones—usually between six to eight—of the production database to serve as test and development platforms. However, without the right automation tools, the process of provisioning test data becomes not only inefficient and labor-intensive but also poses significant risks, such as the potential exposure of sensitive information to unauthorized users, which can lead to compliance violations. The resource drain and challenges associated with data governance during the cloning process often result in test and development databases not being refreshed frequently enough, which can lead to unreliable test outcomes or outright test failures. Consequently, as defects are identified later in the development cycle, the overall costs associated with application development tend to rise, further complicating project timelines and resource allocation. Ultimately, addressing these issues is essential for maintaining both the integrity of the testing process and the overall efficiency of application development.

Have you ever found yourself in dire need of specifically formatted sample or test data? This is precisely the purpose of this script. It is a free and open-source utility developed using JavaScript, PHP, and MySQL, designed to enable users to swiftly create substantial amounts of customized data in multiple formats, which can be utilized for software testing, database population, and more. The script comes equipped with the essential features that most users typically require. However, since every situation is unique, you might find yourself needing to generate quirky mathematical equations, retrieve random tweets, or showcase random images from Flickr that include "Red-backed vole" in their titles. The possibilities are endless, demonstrating that each user's needs can vary significantly. Ultimately, this tool aims to adapt to those diverse requirements seamlessly.

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.

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.

You have complete authority over the encryption of your information at all times, ensuring there are no hidden backdoors. One solution encompasses all systems. With the innovative template concept, the eperi® Gateway can be customized for all your cloud applications, aligning perfectly with your data protection needs. Your team can maintain their usual workflow as the eperi® Gateway seamlessly encrypts data, allowing essential application functionalities like searching and sorting to remain intact. This allows you to leverage the benefits of cloud applications while adhering to rigorous financial industry regulations, including privacy-preserving analytics. The rise of IoT introduces intelligent machines and products that autonomously gather data. With encryption, you can not only secure data privacy but also meet compliance standards effectively. By integrating such robust encryption measures, you can confidently navigate the complexities of data management in today’s digital landscape.

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.

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.

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.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

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.

Xeotek accelerates the development and exploration of data applications and streams for businesses through its robust desktop and web applications. The Xeotek KaDeck platform is crafted to cater to the needs of developers, operations teams, and business users equally. By providing a shared platform for business users, developers, and operations, KaDeck fosters a collaborative environment that minimizes misunderstandings, reduces the need for revisions, and enhances overall transparency for the entire team. With Xeotek KaDeck, you gain authoritative control over your data streams, allowing for significant time savings by obtaining insights at both the data and application levels during projects or routine tasks. Easily export, filter, transform, and manage your data streams in KaDeck, simplifying complex processes. The platform empowers users to execute JavaScript (NodeV4) code, create and modify test data, monitor and adjust consumer offsets, and oversee their streams or topics, along with Kafka Connect instances, schema registries, and access control lists, all from a single, user-friendly interface. This comprehensive approach not only streamlines workflow but also enhances productivity across various teams and projects.

The BiG EVAL platform offers robust software tools essential for ensuring and enhancing data quality throughout the entire information lifecycle. Built on a comprehensive and versatile code base, BiG EVAL's data quality management and testing tools are designed for peak performance and adaptability. Each feature has been developed through practical insights gained from collaborating with our clients. Maintaining high data quality across the full lifecycle is vital for effective data governance and is key to maximizing business value derived from your data. This is where the BiG EVAL DQM automation solution plays a critical role, assisting you with all aspects of data quality management. Continuous quality assessments validate your organization’s data, furnish quality metrics, and aid in addressing any quality challenges. Additionally, BiG EVAL DTA empowers you to automate testing processes within your data-centric projects, streamlining operations and enhancing efficiency. By integrating these tools, organizations can achieve a more reliable data environment that fosters informed decision-making.

As enterprise data explodes and is scattered across multiple systems, the oversight of privacy, data security and governance has become a very difficult task. Businesses are exposed to significant risks, including data breaches, privacy suits, and penalties. It takes months to find data privacy risks within an organization. A team of data engineers is involved in the effort. Data breaches and privacy legislation are forcing companies to better understand who has access to data and how it is used. Enterprise data is complex. Even if a team works for months to isolate data privacy risks, they may not be able to quickly find ways to reduce them.

GxQuality™ is an automated quality assurance application that ensures thorough project validation by generating test scenarios and data while integrating with CI/CD and CV processes. This solution enhances traceability between test conditions and data, supported by managed services from both onshore and offshore teams. Our expertise encompasses a wide range of testing solutions across the enterprise, focusing on DevOps practices, continuous integration and delivery, computer vision, and effective release management strategies. With GxQuality™, organizations can achieve a seamless quality control process, ensuring that all aspects of software deliverables meet the highest standards.

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.

XDM offers a quicker, more efficient, and easier method for data duplication. By intelligently creating and executing tasks, it ensures that both Test and QA teams receive the necessary data promptly, enhancing their workflow and productivity.

The rapid test data generation engine, equipped with approximately 70 integrated functions and an expression processor, allows users to create intricate test data that encompasses dependencies, internal structures, and relationships. This innovative product automatically examines existing database schemas and identifies the master-detail key relationships without requiring user intervention. Additionally, the Value Library offers a collection of predefined datasets that include names, countries, cities, streets, currencies, companies, industries, and departments. Features like Variables and Named Generators facilitate the sharing of data generation attributes across similar columns. Furthermore, the intelligent schema analyzer enhances the realism of your data without necessitating further modifications to the project, while the "data by example" capability streamlines the process of making data more lifelike with minimal effort. Overall, this tool stands out for its user-friendly approach in generating high-quality test data efficiently.

Service Virtualization enables the replication and simulation of the functionalities of constrained or inaccessible systems, facilitating quicker parallel testing while enhancing the quality and dependability of applications. In scenarios where APIs, micro-services, mainframes, or third-party systems cannot be accessed for testing, Service Virtualization equips DevOps and testing teams within the application development and delivery framework with a suite of automated and easily maintainable API testing capabilities, which optimizes both time and resources. Our solution is adept at virtualizing APIs and executing API tests across various layers, even when dealing with unavailable or isolated systems. By generating simulations of essential systems, Service Virtualization removes limitations, ensuring these simulations are accessible throughout the software development lifecycle. This seamless integration allows developers, testers, and performance teams to collaborate simultaneously, leading to accelerated delivery, reduced costs, and improved quality of cutting-edge software applications. Ultimately, this method fosters a more efficient development process that can adapt to the unpredictable nature of system availability.

Gretel provides privacy engineering solutions through APIs that enable you to synthesize and transform data within minutes. By utilizing these tools, you can foster trust with your users and the broader community. With Gretel's APIs, you can quickly create anonymized or synthetic datasets, allowing you to handle data safely while maintaining privacy. As development speeds increase, the demand for rapid data access becomes essential. Gretel is at the forefront of enhancing data access with privacy-focused tools that eliminate obstacles and support Machine Learning and AI initiatives. You can maintain control over your data by deploying Gretel containers within your own infrastructure or effortlessly scale to the cloud using Gretel Cloud runners in just seconds. Leveraging our cloud GPUs significantly simplifies the process for developers to train and produce synthetic data. Workloads can be scaled automatically without the need for infrastructure setup or management, fostering a more efficient workflow. Additionally, you can invite your team members to collaborate on cloud-based projects and facilitate data sharing across different teams, further enhancing productivity and innovation.

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.

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.

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

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.

Datagen offers a self-service platform designed for creating synthetic data tailored specifically for visual AI applications, with an emphasis on both human and object data. This platform enables users to exert detailed control over the data generation process, facilitating the analysis of neural networks to identify the precise data required for enhancement. Users can effortlessly produce that targeted data to train their models effectively. To address various challenges in data generation, Datagen equips teams with a robust platform capable of producing high-quality, diverse synthetic data that is specific to particular domains. It also includes sophisticated features that allow for the simulation of dynamic humans and objects within their respective contexts. With Datagen, computer vision teams gain exceptional flexibility in managing visual results across a wide array of 3D environments, while also having the capability to establish distributions for every element of the data without any inherent biases, ensuring a fair representation in the generated datasets. This comprehensive approach empowers teams to innovate and refine their AI models with precision and efficiency.

HCL OneTest offers software testing tools to support a DevOps strategy: API testing, functional and UI testing, performance testing, and service virtualization. It allows you to automate and run tests faster and more often to find errors sooner, which is when they are cheaper to fix. HCL also offers a bundled offering that can be used under a new consumption model. This will change the way you use and deploy DevOps Software. This new offering simplifies your planning for the adoption and growth critical DevOps products.

To locate, classify, and manage data to protect sensitive information and mitigate privacy risks. Gimmal Discover can work with content from a variety corporate data sources, including file shares, PST files and local workstations. It also works with Exchange, SharePoint, OneDrive Box, Google Workspace, Google Workspace, and other corporate data sources. If sensitive data, such as personally identifiable information (PII), is not managed, it can be lost in data sources and pose serious privacy or compliance risk. Gimmal Discover helps reduce risk by finding sensitive files and offering a way to mitigate them. Discover's powerful eDiscovery capabilities can also be beneficial to legal teams. Gimmal Discover can then apply classification categories to help control content according to your organization's information governance standards.

Techarcis has established itself as a trusted partner for companies seeking reliable software testing and quality assurance solutions. Our team specializes in quality engineering and software quality testing, providing cost-effective solutions that enable clients to expedite the launch of their products while enhancing brand visibility and boosting revenue. In today’s fast-paced business environment, where customer demands and expectations are in constant flux, the need for quality and speed is paramount for achieving success. As a result, more organizations are turning to DevOps and Agile methodologies to swiftly adapt to market changes and maintain a competitive edge. Despite some misconceptions that testing can be managed solely by developers and business analysts, the reality is quite different; testing remains a crucial area that requires specialized skills and deep domain knowledge, and while the competencies required for testers have evolved, their expertise is as vital as ever. Ultimately, investing in professional testing services can lead to significant long-term benefits for businesses striving to thrive in this dynamic landscape.