CloudTDMS Alternatives

Windocks is a leader in cloud native database DevOps, recognized by Gartner as a Cool Vendor, and as an innovator by Bloor research in Test Data Management. Novartis, DriveTime, American Family Insurance, and other enterprises rely on Windocks for on-demand database environments for development, testing, and DevOps. Windocks software is easily downloaded for evaluation on standard Linux and Windows servers, for use on-premises or cloud, and for data delivery of SQL Server, Oracle, PostgreSQL, and MySQL to Docker containers or conventional database instances. Windocks database orchestration allows for code-free end to end automated delivery. This includes masking, synthetic data, Git operations and access controls, as well as secrets management. Windocks can be installed on standard Linux or Windows servers in minutes. It can also run on any public cloud infrastructure or on-premise infrastructure. One VM can host up 50 concurrent database environments.

Test Data Management solutions like data masking, synthetic data generation, data subsetting, data discovery, database virtualization, data automation are our core business. We see and understand the struggles of software development teams with test data. Personally Identifiable Information? Too large environments? Long waiting times for a test data refresh? We envision to solve these issues: - Obfuscating, generating or masking databases and flat files; - Extracting or filtering specific data content with data subsetting; - Discovering, profiling and analysing solutions for understanding your test data, - Automating, integrating and orchestrating test data provisioning into your CI/CD pipelines and - Cloning, snapshotting and timetraveling throug your test data with database virtualization. We improve and innovate our test data software with the latest technologies every single day to support medium to large size organizations in their Test Data Management.

IRI FieldShield® is powerful and affordable data discovery and masking software for PII in structured and semi-structured sources, big and small. Use FieldShield utilities in Eclipse to profile, search and mask data at rest (static data masking), and the FieldShield SDK to mask (or unmask) data in motion (dynamic data masking). Classify PII centrally, find it globally, and mask it consistently. Preserve realism and referential integrity via encryption, pseudonymization, redaction, and other rules for production and test environments. Delete, deliver, or anonymize data subject to DPA, FERPA, GDPR, GLBA, HIPAA, PCI, POPI, SOX, etc. Verify compliance via human- and machine-readable search reports, job audit logs, and re-identification risk scores. Optionally mask data as you map it. Apply FieldShield functions in IRI Voracity ETL, federation, migration, replication, subsetting, or analytic jobs. Or, run FieldShield from Actifio, Commvault or Windocks to mask DB clones.

Datanamic Data Generator is a powerful data generator that allows developers to easily populate databases with thousands of rows of meaningful and syntactically correct test data for database testing purposes. An empty database is not useful for making sure your application will work as designed. You need test data. Writing your own test data generators or scripts is time consuming. Datanamic Data Generator will help you. The tool can be used by DBAs, developers, or testers, who need sample data to test a database-driven application. Datanamic Data Generator makes database test data generation easy and painless. It reads your database and displays tables and columns with their data generation settings. Only a few simple entries are necessary to generate comprehensive (realistic) test data. The tool can be used to generate test data from scratch or from existing data.

Tonic automatically creates mock data that preserves key characteristics of secure datasets so that developers, data scientists, and salespeople can work conveniently without breaching privacy. Tonic mimics your production data to create de-identified, realistic, and safe data for your test environments. With Tonic, your data is modeled from your production data to help you tell an identical story in your testing environments. Safe, useful data created to mimic your real-world data, at scale. Generate data that looks, acts, and feels just like your production data and safely share it across teams, businesses, and international borders. PII/PHI identification, obfuscation, and transformation. Proactively protect your sensitive data with automatic scanning, alerts, de-identification, and mathematical guarantees of data privacy. Advanced sub setting across diverse database types. Collaboration, compliance, and data workflows — perfectly automated.

As physical customer interactions shift into digital, we can no longer rely on real-life conversations. Customers express their intents, share their needs through data. Understanding customers and testing our assumptions about them also happens through data. And privacy regulations such as GDPR and CCPA make a deep understanding even harder. The MOSTLY AI synthetic data platform bridges this ever-growing gap in customer understanding. A reliable, high-quality synthetic data generator can serve businesses in various use cases. Providing privacy-safe data alternatives is just the beginning of the story. In terms of versatility, MOSTLY AI's synthetic data platform goes further than any other synthetic data generator. MOSTLY AI's versatility and use case flexibility make it a must-have AI tool and a game-changing solution for software development and testing. From AI training to explainability, bias mitigation and governance to realistic test data with subsetting, referential integrity.

Privacy engineering tools delivered to you as APIs. Synthesize and transform data in minutes. Build trust with your users and community. Gretel’s APIs grant immediate access to creating anonymized or synthetic datasets so you can work safely with data while preserving privacy. Keeping the pace with development velocity requires faster access to data. Gretel is accelerating access to data with data privacy tools that bypass blockers and fuel Machine Learning and AI applications. Keep your data contained by running Gretel containers in your own environment or scale out workloads to the cloud in seconds with Gretel Cloud runners. Using our cloud GPUs makes it radically more effortless for developers to train and generate synthetic data. Scale workloads automatically with no infrastructure to set up and manage. Invite team members to collaborate on cloud projects and share data across teams.

Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.

A self-service synthetic data platform for visual AI applications, focusing on human and object data. The Datagen Platform allows for granular control over your data generation. You can analyze your neural networks to understand what data is needed to improve them, then easily generate that exact data and use it to train your network. To solve your challenges, Datagen provides a powerful platform that allows you to generate high-quality & high variance, domain-specific, simulated synthetic data. Access advanced capabilities such as the ability to simulate dynamic humans and objects in their context. With Datagen, CV teams have unparalleled flexibility to control visual outcomes across a broad variance of 3D environments. Ability to define the distributions for every part of the data with no inherent biases.

Our AI-driven, autonomous low-code automation platform is designed to help you achieve the highest quality outcome in the shortest amount of time possible. Generate automation scripts automatically in plain English with our Natural Language Processing (NLP) powered solution, and allow your coders to focus on innovation. Maintain quality throughout your application lifecycle with our autonomous discovery and up-to-date tracking of changes. Reduce risk in your dynamic development environment with our autonomous healing capability and deliver flawless updates by keeping automation current. Ensure compliance with all regulatory requirements and eliminate security risk using AI-generated synthetic data for all your automation needs. Run multiple tests in parallel, determine test frequency, keep pace with browser updates and executions across operating systems and platforms.

Overcome challenges in acquiring data for machine learning and AI systems training. Rendered.ai is a PaaS designed for data scientists, engineers, and developers. Generate synthetic datasets for ML/AI training and validation. Experiment with sensor models, scene content, and post-processing effects. Characterize and catalog real and synthetic datasets. Download or move data to your own cloud repositories for processing and training. Power innovation and increase productivity with synthetic data as a capability. Build custom pipelines to model diverse sensors and computer vision inputs​. Start quickly with free, customizable Python sample code to model SAR, RGB satellite imagery, and more sensor types​. Experiment and iterate with flexible licensing that enables nearly unlimited content generation. Create labeled content rapidly in a hosted, high-performance computing environment​. Enable collaboration between data scientists and data engineers with a no-code configuration experience.

We help you discover, create, and subset test data; visualize test data coverage; and protect data so you can focus on development. Automate provisioning of masked, subsetted, and synthetically generated data to meet development and testing needs. Identify sensitive data locations quickly with consistent masking in and across databases. Store, augment, share, and reuse test datasets to improve testers’ efficiency. Provision smaller data sets to minimize infrastructure requirements and speed performance. Use our comprehensive set of masking techniques to consistently protect data across applications. Support packaged applications to ensure solution integrity and speed deployments. Engage risk, compliance, and audit teams to align with data governance initiatives. Improve test efficiency with reliable, trusted production data sets; reduce server and storage footprints with data set sizes targeted for each team.

Describe your data model on an abstract level in XML. Involve your business people as no developer skills are necessary. Use a wide range of function libraries to fake realistic data. Write your own extensions in Javascript or Java. Integrate your data processes into Gitlab CI or Jenkins. Generate, anonymize, and migrate with Benerator’s model-driven data toolkit. Define processes to anonymize or pseudonymize data in plain XML on an abstract level without the need for developer skills. Stay GDPR compliant with your data and protect the privacy of your customers. Mask and obfuscate sensitive data for BI, test, development, or training purposes. Combine data from various sources (subsetting) and keep the data integrity. Migrate and transform your data in multisystem landscapes. Reuse your testing data models to migrate production environments. Keep your data consistent and reliable in a microsystem architecture.

At K2View, we believe that every enterprise should be able to leverage its data to become as disruptive and agile as the best companies in its industry. We make this possible through our patented Data Product Platform, which creates and manages a complete and compliant dataset for every business entity – on demand, and in real time. The dataset is always in sync with its underlying sources, adapts to changes in the source structures, and is instantly accessible to any authorized data consumer. Data Product Platform fuels many operational use cases, including customer 360, data masking and tokenization, test data management, data migration, legacy application modernization, data pipelining and more – to deliver business outcomes in less than half the time, and at half the cost, of any other alternative. The platform inherently supports modern data architectures – data mesh, data fabric, and data hub – and deploys in cloud, on-premise, or hybrid environments.

Advanced technology and services to safely transform and enhance sensitive data into actionable insights, help drive innovation, and open new revenue streams. Using the Mimic synthetic data engine, companies can safely synthesize their data assets, protecting consumer privacy information from being exposed, while still maintaining the statistical relevancy of the data. The synthetic data can then be used for internal initiatives like analytics, machine learning and AI, marketing and segmentation activities, and new revenue streams through external data monetization. Mimic enables you to safely move statistically-relevant synthetic data to the cloud ecosystem of your choice to get the most out of your data. Analytics, insights, product development, testing, and third-party data sharing can all be done in the cloud with the enhanced synthetic data, which has been certified to be compliant with regulatory and privacy laws.

Data is an invaluable business asset. With the right AI model, it’s possible to use data to build and understand customer profiles, look for trends, and identify new business opportunities. But it requires huge volumes of data to develop accurate and robust AI models, and that’s a challenge, from both a data quality and quantity perspective. In addition, stringent regulations, most notably GDPR, restrict the use of certain sensitive data, like customer data. It’s time for a new approach. Especially in a software testing environment where good quality testing data is hard to access. We typically see actual customer data being used, which risks GDPR non-compliance and ensuing heavy financial fines. Artificial Intelligence (AI) is expected to increase business productivity by at least 40% but businesses struggle to deploy or fully unlock AI solutions due to data-related challenges. ADA generates synthetic data using advanced deep learning.

Synth is an open-source data-as-code tool that provides a simple CLI workflow for generating consistent data in a scalable way. Use Synth to generate correct, anonymized data that looks and quacks like production. Generate test data fixtures for your development, testing, and continuous integration. Generate data that tells the story you want to tell. Specify constraints, relations, and all your semantics. Seed development and environments and CI. Anonymize sensitive production data. Create realistic data to your specifications. Synth uses a declarative configuration language that allows you to specify your entire data model as code. Synth can import data straight from existing sources and automatically create accurate and versatile data models. Synth supports semi-structured data and is database agnostic, playing nicely with SQL and NoSQL databases. Synth supports generation for thousands of semantic types such as credit card numbers, email addresses, and more.

A synthetic data platform for ML engineers to enable the development of more capable AI models. Simple APIs provide on-demand generation of perfectly-labeled, diverse, and photoreal images. Highly-scalable cloud-based generation platform delivers millions of perfectly labeled images. On-demand data enables new data-centric approaches to develop more performant models. An expanded set of pixel-perfect labels including segmentation maps, dense 2D/3D landmarks, depth maps, surface normals, and much more. Rapidly design, test, and refine your products before building hardware. Prototype different imaging modalities, camera placements, and lens types to optimize your system. Reduce bias in your models associated with misbalanced data sets while preserving privacy. Ensure equal representation across identities, facial attributes, pose, camera, lighting, and much more. We have worked with world-class customers across many use cases.

Find, build, manage, and deliver test data to everyone on your team. Test Data Manager helps you address data privacy and compliance Issues as they relate compliance regulations and your corporate mandates. The TDM Discovery and Profiling feature provides the ability to identify personally identifiable information (PII) across multiple data sources. A heat map displays PII data and classifies it according to severity levels. Test data engineers and compliance officers can review and tag the Data for further mitigation. Comprehensive reports can be generated in PDF format to demonstrate compliance to anyone interested. Test Data Manager helps you address data privacy and compliance Issues as they relate compliance regulations and your corporate mandates. The TDM Discovery and Profiling feature provides the ability to identify personally identifiable information (PII) across multiple data sources. A heat map displays PII data and classifies it according to severity levels.

Qlik Gold Client improves the efficiency, cost and security of managing test data in SAP environments. Qlik Gold Client is designed to eliminate development workarounds by easily moving configuration, master, and transactional data subsets into testing environments. Rapidly define, copy and synchronize transactional data from production to non-production targets. Identify, select, and delete non-production data. Manage extensive and powerful data transformations through a clean and easy-to-use interface. Automate data selection and enable hands-free test data refresh cycles, reducing time and effort for test data management. Qlik Gold Client provides several options to protect PII data in non-production environments via data masking. Data masking applies a set of rules to “scramble” your production data when it’s replicated to a non-production environment.

Syntheticus® empowers data exchange and overcomes limitations in data access, scarcity, and bias - at scale. With our synthetic data platform, you generate high-quality and compliant data samples tailored to your business needs and analytics goals. With synthetic data, you easily tap into a wide range of high-quality sources that are not always available in the real world. By accessing high-quality, consistent data, you conduct more reliable research, leading to better products, services, and business decisions. With fast, reliable data sources at your fingertips, you accelerate product development cycles and improve time-to-market. Synthetic data is designed to be private and secure by default, protecting sensitive data and maintaining compliance with privacy laws and regulations.

dbForge Data Generator for Oracle is a small but mighty GUI tool for populating Oracle schemas with tons of realistic test data. Having an extensive collection of 200+ predefined and customizable data generators for various data types, the tool delivers flawless and quick data generation (including random number generation) in easy to use interface. Data Generator offers flexible options and templates to create and use your own generators to better suit your requirements. Key features: * Generate large volumes of data for multiple Oracle database versions * Support for inter-column dependency * Avoid the need for data entry in multiple databases manually * Automate and optimize data generation tasks in the command line * Add reliability to the application with meaningful test data * Output the data generation script to a file * Increase testing efficiency by sharing and reusing datasets * Eliminate risks to access secure data by provisioning test data

Power up your AI and data projects with the most valuable data At Synthesized, we unlock data's full potential by automating all stages of data provisioning and data preparation with a cutting-edge AI. We protect from privacy and compliance hurdles by virtue of the data being synthesized through the platform. Software for preparing and provisioning of accurate synthetic data to build better models at scale. Businesses solve the problem of data sharing with Synthesized. 40% of companies investing in AI cannot report business gains. Stay ahead of your competitors and help data scientists, product and marketing teams focus on uncovering critical insight with our simple-to-use platform for data preparation, sanitization and quality assessment. Testing data-driven applications is difficult without representative datasets and this leads to issues when services go live.

While enterprise data is exploding and scattered across various systems, oversight of driving privacy, data security, and governance has become very challenging. As a result, businesses hold significant risks in the form of data breaches, privacy lawsuits, and penalties. Finding data privacy risks in an enterprise is a complex, and time-consuming effort that takes months involving a team of data engineers. Data breaches and privacy laws are requiring companies to have a better grip on which users have access to the data, and how the data is used. But enterprise data is complex, so even if a team of engineers works for months, they will have a tough time isolating data privacy risks or quickly finding ways to reduce them.

Set your enterprise data free. Hazy re-engineer your enterprise data to make it faster, easier and safer to use. We enable every enterprise to actually use its data. Data has never been more valuable. But with growing privacy demands and tightening regulations, most of the world’s data is locked away and unusable. Hazy has pioneered a new approach that allows you to actually use your data. So you can make better decisions, develop new technologies and deliver more value for your customers. Create and deploy realistic test data to quickly validate new systems and technologies and accelerate your organization’s digital transformation. Generate enough safe, high-quality data to build, train and improve the algorithms that power your AI applications and enable automation. Empower teams to generate and share accurate analytics and intelligence on products, customers, and operations to improve decision-making.

Fast test data generation engine with about 70 built-in functions and expression processor enables users to define complex test data with dependencies, internal structure, and relationships. The product analyzes existing database schema and resolves master-detail key structure (relationships) automatically. Value Library is a predefined data sets: names, countries, cities, streets, currencies, companies, industries, departments, regions, etc. Variables and Named Generators features provide a way to share data generation properties to similar columns. Intelligent schema analyzer makes your data realistic without extra project modifications and "data by example" feature makes data more realistic without extra efforts.

Visualize vast quantities of data objects, understand their relationships, and tune related data extracts to create optimal test data. Compare files, including those that exist on different LPARs, expanding the ability to quickly and frequently assess the impact of your changes. Simplify the complex task of managing data and preparing data for testing by enabling developers and test engineers to perform data-related tasks without writing programs or scripts, coding SQL, or using multiple utilities. Enable developers, test engineers, and analysts to be more self-sufficient by provisioning data when needed, reducing reliance on subject matter experts. Improve application quality with better testing scenarios, simplifying the task of creating complete data extracts for testing purposes, and accurately identifying the impact of changing pieces of data.

Stop relying on confidential production data. Masked data may not be realistic or robust enough either. IRI RowGen uses your metadata and business rules to make better test data. Persistent or virtual test sets improve DB/ETL prototypes and speed DevOps. Use the high quality, high volume database, file, report or DataVault targets you create and populate with RowGen's graphical job wizards in in the IRI Workbench IDE (built on Eclipse) to stress-test and future-proof new software and systems. 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. You can also leverage RowGen functionality in CI/CD pipelines like GitLab, cloned DBs via Windocks et al, and purpose-built TDM hubs from Cigniti or ValueLabs.

The Synthetic Data Vault (SDV) is a Python library designed to be your one-stop shop for creating tabular synthetic data. The SDV uses a variety of machine learning algorithms to learn patterns from your real data and emulate them in synthetic data. The SDV offers multiple models, ranging from classical statistical methods (GaussianCopula) to deep learning methods (CTGAN). Generate data for single tables, multiple connected tables, or sequential tables. Compare the synthetic data to the real data against a variety of measures. Diagnose problems and generate a quality report to get more insights. Control data processing to improve the quality of synthetic data, choose from different types of anonymization, and define business rules in the form of logical constraints. Use synthetic data in place of real data for added protection, or use it in addition to your real data as an enhancement. The SDV is an overall ecosystem for synthetic data models, benchmarks, and metrics.

Adopting data-centric AI has never been easier with automated data quality profiling and synthetic data generation. We help data scientists to unlock data's full potential. YData Fabric empowers users to easily understand and manage data assets, synthetic data for fast data access, and pipelines for iterative and scalable flows. Better data, and more reliable models delivered at scale. Automate data profiling for simple and fast exploratory data analysis. Upload and connect to your datasets through an easily configurable interface. Generate synthetic data that mimics the statistical properties and behavior of the real data. Protect your sensitive data, augment your datasets, and improve the efficiency of your models by replacing real data or enriching it with synthetic data. Refine and improve processes with pipelines, consume the data, clean it, transform your data, and work its quality to boost machine learning models' performance.

Today’s Agile DevOps teams need the ability to go faster. BMC Compuware File-AID provides a cross-platform file and data management solution that enables developers and QA staff to quickly and conveniently access necessary data and files instead of hunting around for them. In turn, developers devote less time to data-related tasks and spend more time developing new functionality and managing production problems. Rightsizing your test data provides confidence to make code changes without unintended consequences. Access all standard file types regardless of record length or format for application integration. Compare data files or objects to simplify the test results validation process. Reformat files by easily modifying an existing file format instead of starting from scratch. Extract and load related subsets of data from multiple databases and files & more.

Quickly and easily generate diverse and realistic synthetic data and high-fidelity 3D worlds to enhance model performance. Bifrost's platform is the fastest way to generate the high-quality synthetic images that you need to improve ML performance and overcome real-world data limitations. Prototype and test up to 30x faster by circumventing costly and time-consuming real-world data collection and annotation. Generate data to account for rare scenarios underrepresented in real data, resulting in more balanced datasets. Manual annotation and labeling is an error-prone, resource-intensive process. Easily and quickly generate data that is pre-labeled and pixel-perfect. Real-world data can inherit the biases of conditions under which the data was collected, and generate data to solve for these instances.

We offer data anonymization software that generates entirely anonymous synthetic datasets for our customers. The synthetic data generated by Statice contains statistical properties similar to real data but irreversibly breaks any relationships with actual individuals, making it a valuable and safe to use asset. It can be used for behavior, predictive, or transactional analysis, allowing companies to leverage data safely while complying with data regulations. Statice’s solution is built for enterprise environments with flexibility and security in mind. It integrates features to guarantee the utility and privacy of the data while maintaining usability and scalability. It supports common data types: Generate synthetic data from structured data such as transactions, customer data, churn data, digital user data, geodata, market data, etc We help your technical and compliance teams validate the robustness of our anonymization method and the privacy of your synthetic data

Xeotek helps companies develop and explore their data applications and streams faster with Xeotek's powerful desktop and web application. Xeotek KaDeck was designed to be used by developers, operations, and business users alike. Because business users, developers, and operations jointly gain insight into data and processes via KaDeck, the whole team benefits: fewer misunderstandings, less rework, more transparency. Xeotek KaDeck puts you in control of your data streams. Save hours of work by gaining insights at the data and application level in projects or day-to-day operations. Export, filter, transform and manage data streams in KaDeck with ease. Run JavaScript (NodeV4) code, transform & generate test data, view & change consumer offsets, manage your streams or topics, Kafka Connect instances, schema registry, and ACLs – all from one convenient user interface.

SKY ENGINE AI is a simulation and deep learning platform that generates fully annotated, synthetic data and trains AI computer vision algorithms at scale. The platform is architected to procedurally generate highly balanced imagery data of photorealistic environments and objects and provides advanced domain adaptation algorithms. SKY ENGINE AI platform is a tool for developers: Data Scientists, ML/Software Engineers creating computer vision projects in any industry. SKY ENGINE AI is a Deep Learning environment for AI training in Virtual Reality with Sensors Physics Simulation & Fusion for any Computer Vision applications. SKY ENGINE AI Synthetic Data Generation makes Data Scientist life easier providing perfectly balanced datasets for any Computer Vision applications like object detection & recognition, 3D positioning, pose estimation and other sophisticated cases including analysis of multi-sensor data i.e., Radars, Lidars, Satellite, X-rays, and more.

A flexible and accurate synthetic data generation platform. Craft the data you need for your perception system in minutes. Design scenarios for your use case with endless variations. Generate your datasets in the cloud. Anyverse offers a scalable synthetic data software platform to design, train, validate, or fine-tune your perception system. It provides unparalleled computing power in the cloud to generate all the data you need in a fraction of the time and cost compared with other real-world data workflows. Anyverse provides a modular platform that enables efficient scene definition and dataset production. Anyverse™ Studio is a standalone graphical interface application that manages all Anyverse functions, including scenario definition, variability settings, asset behaviors, dataset settings, and inspection. Data is stored in the cloud, and the Anyverse cloud engine is responsible for final scene generation, simulation, and rendering.

dbForge Data Generator for MySQL is a powerful GUI tool for creating massive volumes of realistic test data. The tool includes a large collection of predefined data generators with customizable configuration options that allow to populate MySQL database tables with meaningful data of various types. Key Features: - Support of MySQL server, MariaDB, Percona Server - Full support of all essential column data types - Wide range of basic generators - 180+ meaningful generators - User-defined generators - Data customization for each individual generator - SQL data integrity support - Multiple ways to populate data - User-friendly wizard interface - Real-time preview of generated data - Command-line interface - Python Generator - Support for Spatial data types

RNDGen Random Data Generator is a free user-friendly tool for generate test data. The data creator uses an existing data model and customizes it to create a mock data table structure for your needs. Random Data Generator also known like json generator, dummy data generator, csv generator, sql dummy or mock data generator. Data Generator by RNDGen allows you to easily create dummy data for tests that are representative of real-world scenarios, with the ability to select from a wide range of fake data details fields including name, email, location, address, zip and vin codes and many others. You can customize generated dummy data to meet your specific needs. With just a few clicks, you can quickly generate thousands of fake data rows in different formats, including CSV, SQL, JSON, XML, Excel, making RNDGen the ultimate tool for all your data generation needs instead of standard mock datasets.

Our AI-powered data generation platform enables data analysts and machine learning engineers to maximize the value of their analytical data sets. By leveraging the behavior extracted from existing data, Datomize enables users to generate the exact analytical data sets needed. Equipped with data that comprehensively represent real-world scenarios, users can now gain a far more accurate reflection of reality and make much better decisions. Extract superior insights from your data and develop state-of-the-art AI solutions. Datomize’s AI-powered, generative models create superior synthetic replicas by extracting the behavior from your existing data. Advanced augmentation capabilities enable limitless resizing of your data, while dynamic validation tools visualize the similarity between original and replicated data sets. Datomize’s data-centric approach to machine learning addresses the primary data constraints of training high-performing ML models.

Accurate test data improves application development and testing quality, which is why the most demanding application development teams require that their test data be populated from production databases frequently. It is not unusual for a Test Data Management (TDM) program to maintain six to eight full clones/copies of the production database for use as test and development instances. Without proper automation, provisioning test data is not only inefficient, time-consuming and storage intensive but it could also potentially expose sensitive data to unauthorized personnel leading to compliance risks. Since the cloning process creates such resource drain and data governance challenges, test and development databases are often not refreshed frequently enough resulting in inaccurate test results or even test failures. And of course, the cost of application development increases as the errors are discovered later in the application development lifecycle.

Database design · database implementation · stored routine debuggers · test data generators · database auditing · data change logging · performance monitoring · data transfers · import and export of data · DBA tasks · reporting · performance testing · database release management. A fully featured test data generator tool: generates real-life-like data into your database or data files. The only comprehensive and up-to-date Firebird server monitoring tool available at the market. Database Workbench offers a single development environment for developing with multiple database engines. With database engine specific functionality, powerful tools and a consistent, clear and intuitive user interface, Database Workbench will increase your productivity from the moment you start using it.

ERBuilder Data Modeler is a GUI data modeling tool that allows developers to visualize, design, and model databases by using entity relationship diagrams and automatically generates the most popular SQL databases. Generate and share the data Model documentation with your team. Optimize your data model by using advanced features such as test data generation, schema compare, and schema synchronization.

It's hard to put together a meaningful UI prototype without making real requests to an API. By making real requests, you'll uncover problems with application flow, timing, and API design early, improving the quality of both the user experience and API. With Mockaroo, you can design your own mock APIs, You control the URLs, responses, and error conditions. Paralellize UI and API development and start delivering better applications faster today! There are plenty of great data mocking libraries available for almost every language and platform. But not everyone is a programmer or has time to learn a new framework. Mockaroo allows you to quickly and easily to download large amounts of randomly generated test data based on your own specs which you can then load directly into your test environment using SQL or CSV formats.

Safely share your production data with ML, data science, and analytics teams while safeguarding customer trust. Stop fiddling with regexes and open-source models. Private AI efficiently anonymizes 50+ entities of PII, PCI, and PHI across GDPR, CPRA, and HIPAA in 49 languages with unrivaled accuracy. Replace PII, PCI, and PHI in text with synthetic data to create model training datasets that look exactly like your production data without compromising customer privacy. Remove PII from 10+ file formats, such as PDF, DOCX, PNG, and audio to protect your customer data and comply with privacy regulations. Private AI uses the latest in transformer architectures to achieve remarkable accuracy out of the box, no third-party processing is required. Our technology has outperformed every other redaction service on the market. Feel free to ask us for a copy of our evaluation toolkit to test on your own data.

MakerSuite is a tool that simplifies this workflow. With MakerSuite, you’ll be able to iterate on prompts, augment your dataset with synthetic data, and easily tune custom models. When you’re ready to move to code, MakerSuite will let you export your prompt as code in your favorite languages and frameworks, like Python and Node.js.

Create, transform, and analyze any text data in your spreadsheet. Automatically normalize addresses, separate columns, extract entities, and more. Rewrite SEO content, write blog posts, generate product description variations, and more. Create synthetic data like first/last names, addresses, phone numbers, and more. Generate bullet-point summaries, rewrite existing content with fewer words, and more. Categorize product feedback, prioritize sales leads, discover new trends, and more. Charm offers several templates that help people complete common workflows faster. Use the Summarize With Bullet Points template to generate summaries of existing long content in the form of a short list of bullets. Use the Translate Language template to translate existing content into another language.

OpenText Data Express is designed to manage the test data environment: improving test results, lowering testing costs, securing customer data from loss or misuse, and enabling accelerated delivery and privacy compliance. Data Express automates the generation of test data environments, so elapsed time is reduced by up to 80%. By masking sensitive information, test data retains its value for testing while keeping it safe from unauthorized use. Data Express provides a single repository of test data knowledge. It offers a wealth of management tools to ensure that test managers can control the repeated generation of test data.

Amazon SageMaker allows you to identify raw data such as images, text files, and videos; add informative labels and generate labeled synthetic data to create high-quality training data sets for your machine learning (ML) models. SageMaker offers two options, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which give you the flexibility to use an expert workforce to create and manage data labeling workflows on your behalf or manage your own data labeling workflows. data labeling. If you want the flexibility to create and manage your own personal and data labeling workflows, you can use SageMaker Ground Truth. SageMaker Ground Truth is a data labeling service that makes data labeling easy and gives you the option of using human annotators via Amazon Mechanical Turk, third-party providers, or your own private staff.

We label your data with the higher quality standards to fulfill the needs of the most complex AI projects, using our proprietary labeling platform. Now you can get back to creating the products your customers love. We provide an end-to-end solution for image annotation with fast labeling tools, synthetic data generation, data management, automation features and annotation services on-demand with integrated tooling to accelerate and finish computer vision projects. When every pixel matters, you need accurate, AI-powered intuitive image annotation tools to support your specific use case, including instances, attributes and much more. Our in-house highly trained data labelers are able to deal with any data challenge. As your data labeling needs grow over time, you can count on us to scale the workforce necessary to meet your goals, and in contrast to crowdsourcing platforms your data quality will not suffer.

HCL OneTest provides software testing tools to support a DevOps approach: API testing, functional testing, UI testing, performance testing and service virtualization. It helps you automate and run tests earlier and more frequently to discover errors sooner — when they are less costly to fix. HCL also provides a bundled offering under a new consumption model that changes the way you can use and deploy DevOps software. The new offering helps simplify your planning for adoption and growth of critical DevOps products. HCL OneTest UI enables testers to take automation all the way from mainframe terminals with 3270 interfaces, through .NET- and Java-based thick client applications. Additionally, it works with the latest top browsers, ERP systems such as SAP and Oracle, right up to HTML5-based responsive web applications that are built on modern frameworks like Angular, React and Vue.js.