Alternatives to Informatica Test Data Management

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.

Sahi Pro is a suite automation tools for web, Web-services, Windows desktop and Java applications. Sahi Pro features include automatic waits, recorders and accessor spy, inbuilt frame and editor, parallel playback, automatic reporting, automatic logging, and reporting. Also, Sahi Pro can save 70% of the time and effort that is normally spent on test automation. Sahi Pro has been trusted by more than 400 companies around the world and is quickly becoming the preferred tool for test automation in the agile world.

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.

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

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

The increasing risks to security and the rise of stringent privacy laws have necessitated a more cautious approach to handling sensitive information. Oracle Data Masking and Subsetting offers database users a solution to enhance security, streamline compliance efforts, and lower IT expenses by sanitizing production data copies for use in testing, development, and various other functions, while also allowing for the removal of superfluous data. This tool allows for the extraction, obfuscation, and sharing of both full copies and subsets of application data with partners, whether they are within or outside the organization. By doing so, it ensures the database's integrity remains intact, thus supporting the ongoing functionality of applications. Additionally, Application Data Modeling automatically identifies columns within Oracle Database tables that contain sensitive data through established discovery patterns, including national IDs, credit card details, and other forms of personally identifiable information. Furthermore, it can recognize and map parent-child relationships that are defined within the database structure, enhancing the overall data management process.

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.

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.

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.

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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.

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.

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.

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.

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.

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.

IBM InfoSphere® Optim™ Data Privacy offers a comprehensive suite of tools designed to effectively mask sensitive information in non-production settings like development, testing, quality assurance, or training. This singular solution employs various transformation methods to replace sensitive data with realistic, fully functional masked alternatives, ensuring the confidentiality of critical information. Techniques for masking include using substrings, arithmetic expressions, generating random or sequential numbers, manipulating dates, and concatenating data elements. The advanced masking capabilities maintain contextually appropriate formats that closely resemble the original data. Users can apply an array of masking techniques on demand to safeguard personally identifiable information and sensitive corporate data within applications, databases, and reports. By utilizing these data masking features, organizations can mitigate the risk of data misuse by obscuring, privatizing, and protecting personal information circulated in non-production environments, thereby enhancing data security and compliance. Ultimately, this solution empowers businesses to navigate privacy challenges while maintaining the integrity of their operational processes.

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.

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 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.

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.

Maintain the essence, structure, and accuracy while ensuring confidentiality. Improve data security by anonymizing and altering sensitive information, as well as implementing pseudonymization strategies for adherence to privacy regulations and analytics purposes. The obscured data continues to hold its context and referential integrity, making it suitable for use in testing, analytics, or support scenarios. Serving as an exceptionally scalable and high-performing data masking solution, Informatica Persistent Data Masking protects sensitive information—like credit card details, addresses, and phone numbers—from accidental exposure by generating realistic, anonymized data that can be safely shared both internally and externally. Additionally, this solution minimizes the chances of data breaches in nonproduction settings, enhances the quality of test data, accelerates development processes, and guarantees compliance with various data-privacy laws and guidelines. Ultimately, adopting such robust data masking techniques not only protects sensitive information but also fosters trust and security within organizations.

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.

Infosys' Test Data Management solution guarantees comprehensive test coverage by supplying appropriate data in sufficient volumes and at optimal times within a non-production setting. It effectively supports the integration of Agile and DevOps methodologies, offers a self-service data capability, and utilizes machine learning for tasks such as data profiling and sensitivity analysis, alongside intelligent data masking. Additionally, it supports cloud-based large-scale Big Data transformation initiatives by ensuring the timely provision of necessary data. This offering seamlessly combines data management techniques, proprietary test data management tools, and partner solutions to achieve complete traceability of test data throughout the testing process. Moreover, it enhances efficiency by streamlining the data preparation process, ultimately leading to improved project outcomes.

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.

BizDataX offers a data masking solution that delivers test data with the quality comparable to that of production environments. It ensures adherence to GDPR and various other regulations by concealing customer identities while supplying data for developers and testers. Utilizing masked or anonymized data rather than actual production data significantly mitigates associated risks. The focus is placed on managing policies, fulfilling business requirements, governing sensitive data, and adhering to diverse regulations. It also facilitates the monitoring of databases, data sources, and tables to identify the locations of sensitive information. Furthermore, it allows for the management of extensive customer databases and the seamless exchange of data with online partner retailers and delivery services. Given the stringent regulations surrounding medical records, compliance can be effectively maintained through the process of data anonymization, ensuring that patient information is protected. This capability not only safeguards sensitive data but also enhances the overall data management strategy for organizations.

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.

Stop spending unnecessary time on the provisioning and upkeep of databases by automating the process. Instantly generate isolated test databases to accelerate the delivery of features. Empower your developers with the immediate access to essential data they require to keep projects moving swiftly. Seamlessly create pre-populated databases for testing within your CI/CD pipeline and automatically remove them once the testing phase concludes. With just a click, you can quickly and easily set up databases for testing, bug reproduction, demonstrations, and much more, all supported by integrated container orchestration. Utilize our innovative subsetter to condense petabytes of data down to gigabytes while maintaining referential integrity, and then take advantage of Tonic Ephemeral to create a database containing only the necessary data for development, thereby reducing cloud expenses and enhancing productivity. By combining our patented subsetter with Tonic Ephemeral, you can ensure access to all required data subsets for only the duration they are needed. This approach maximizes efficiency by providing your developers with easy access to specific datasets tailored for local development, enabling them to work more effectively. Ultimately, this leads to a more streamlined workflow and better project outcomes.

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.

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.

Explore the innovative features of your mobile app by engaging with genuine mobile devices in real-time through your web browser. You can develop and run hundreds of both manual and automated tests simultaneously across more than 1,000 authentic iOS and Android devices hosted in the cloud. Craft Appium tests effortlessly right from your integrated development environment and take advantage of live interactions and debugging. Gain insights through visual test reports and sophisticated analytics. Streamline your cross-browser testing by executing Selenium tests on over 1,000 different browser types, versions, and operating systems. Engage actively with your application as you debug and conduct visual assessments to confirm UI adaptability across various resolutions. With Appium Studio, you can intuitively create new tests or utilize existing projects. Testing on iOS devices via a Windows setup is straightforward, providing advanced testing options. Digital.ai Continuous Testing empowers organizations to perform scalable tests, enhance test coverage, and leverage data-driven insights to deliver superior applications. This comprehensive approach ensures that applications are not only functional but also user-friendly across diverse platforms.

Storybook serves as a dedicated environment for creating user interfaces in isolation, allowing developers to address challenging scenarios and edge cases effectively. You can design components and pages without the hassle of managing data, APIs, or business logic complexities. It enables the rendering of components in specific states that are difficult to replicate within a typical application setup. By saving use cases as stories in straightforward JavaScript, you can easily return to them throughout development, testing, and quality assurance phases. Additionally, you can enhance your workflow with addons that facilitate automated testing and integration with preferred tools. These stories act as a practical and reproducible method to document UI edge cases comprehensively. After writing a story, you can leverage it for automated testing, as each one essentially provides a valuable test case. This allows you to swiftly review stories and ensure your UI appears as intended. You can identify pixel-level UI changes by comparing image snapshots of these stories, and you can incorporate them into your unit tests to validate intricate functionalities. Ultimately, stories illustrate the actual operation of UIs rather than just their intended functionality, simplifying the process of collecting feedback and reproducing issues. Furthermore, this approach fosters a collaborative environment where team members can share insights and improvements based on real user interactions.

Modern software teams can automate their tests without writing code. Rainforest QA allows developers and product managers to automate and maintain end tests within any CI/CD pipeline. In five minutes or less, you can create your first test. Product builders should be able to control product quality. Rainforest allows anyone on your team to write, run, maintain, and triage automated UI tests. You can use our API, CLI or one of our direct connections with popular CI tools. Rainforest has everything you need to get started immediately.

Mage™ offers comprehensive Static Data Masking (SDM) and Test Data Management (TDM) functionalities that are fully compatible with Imperva’s Data Security Fabric (DSF), ensuring robust safeguarding of sensitive or regulated information. This integration occurs smoothly within an organization’s current IT infrastructure and aligns with existing application development, testing, and data processes, all without necessitating any alterations to the existing architectural setup. As a result, organizations can enhance their data security while maintaining operational efficiency.

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.

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.

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.

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.

Protecting your personal information is crucial, and it’s essential to create data that appears genuine for software development purposes. To achieve this, DOT Anonymizer provides a solution that effectively masks your testing data while maintaining its consistency across various data sources and database management systems. The risk of data breaches arises significantly when using personal or identifiable information in non-production environments such as development, testing, training, and business intelligence. With the growing number of regulations worldwide, organizations are increasingly required to anonymize or pseudonymize sensitive information. This process allows you to keep the original format of the data while your teams can operate with believable yet fictional datasets. It is vital to manage all your data sources effectively to ensure their continued utility. You can easily invoke DOT Anonymizer functions directly from your applications, ensuring consistent anonymization across all database management systems and platforms. Additionally, it’s important to maintain relationships between tables to guarantee that the data remains realistic. The tool is capable of anonymizing a variety of database types and file formats, including CSV, XML, JSON, and more. As the demand for data protection grows, utilizing a solution like DOT Anonymizer becomes increasingly essential for maintaining the integrity and confidentiality of your data.

Streamline the self-service provisioning and refreshing of enterprise workloads while seamlessly integrating with your current toolchain. Enable efficient data delivery and reutilization for data scientists via a comprehensive suite of APIs and automation tools. Achieve data recovery across any cloud environment from any moment in time, concurrently and at scale, surpassing traditional legacy solutions. Reduce the impact of ransomware and cyber threats by ensuring rapid recovery through immutable backup systems. A consolidated platform enhances the protection, security, retention, governance, and recovery of your data, whether on-premises or in the cloud. Actifio’s innovative software platform transforms isolated data silos into interconnected data pipelines. The Virtual Data Pipeline (VDP) provides comprehensive data management capabilities — adaptable for on-premises, hybrid, or multi-cloud setups, featuring extensive application integration, SLA-driven orchestration, flexible data movement, and robust data immutability and security measures. This holistic approach not only optimizes data handling but also empowers organizations to leverage their data assets more effectively.

LambdaTest, a cloud-based cross browser test platform, enables enterprises to run web automation tests at scale (through parallel coding). **Selenium Automation Grid & Cypress CLI on LambdaTest** Tests can be run across more than 2,000 browsers, devices, operating systems to improve browser coverage. LambdaTest is a cloud-based Selenium Grid which helps you run Selenium tests faster. It's secure, scalable and reliable. The Cypress CLI, available on LambdaTest allows you to expand Cypress test coverage up to 40+ browser versions across Windows or macOS platforms. Automation testing is not the only option. You can also do manual tests, visual interface tests, and real time tests. **LT Browser – Responsive Web Testing** LambdaTest's LT browser is a groundbreaking developer-oriented tool that helps you assess the responsiveness and usability of your website. Mobile testing is easier with responsive tests that can be run against 50+ resolutions. You can also create unlimited custom devices.

TestMatch serves as a tool for comparing transaction content, enabling automated testing of mainframe OLTP applications, which are terminal-based systems for processing online transactions. It is particularly useful for aiding the transition of legacy applications to contemporary open systems, or it can be utilized to create an automated regression testing suite for existing applications. All user interactions are centrally recorded on an IBM or Siemens mainframe without the need for installing any client-side or server-side components of Astadia's software. This network-level recording method ensures compatibility across various development technologies. TestMatch effectively visualizes test scenarios and sessions, showcasing terminal content along with key attributes typical of terminal-based applications, such as protected/editable settings, MDT bits, reverse-video effects, and color schemes. Furthermore, TestMatch can replay these recorded scenarios, which can either be directed at the migrated application for testing purposes or the original application to verify functionality through regression testing. This versatility makes TestMatch an invaluable asset for organizations looking to streamline their testing processes while ensuring reliability during application transitions.

Quash is an innovative quality assurance platform powered by AI, specifically crafted to enhance mobile testing by automatically creating and running functional and visual tests without the need for conventional scripting methods. It systematically maps each screen within your mobile application, converts product requirement documents into actionable test cases, and executes them through an AI engine that comprehends app navigation and user intent, effectively eliminating unreliable selectors and delicate test scripts. The platform intelligently learns the context of your application by analyzing app data, allowing it to adapt in real-time, which leads to considerably improved coverage and more seamless release processes by identifying edge cases at an earlier stage. Following test executions, Quash offers comprehensive bug reports featuring screenshots, session logs, insights into root causes, and recommended solutions, all accessible through a centralized dashboard that integrates test generation, execution, bug tracking, and analytics. Additionally, it is compatible with existing CI/CD pipelines, test management workflows, and bug-reporting tools, ensuring a smooth integration into current development processes while enhancing overall efficiency. Ultimately, Quash aims to transform the mobile testing landscape by providing developers with the tools they need to deliver high-quality applications faster and more reliably.

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.