Alternatives to Soflab G.A.L.L.

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.

Titaniam provides enterprises and SaaS vendors with a full suite of data security controls in one solution. This includes highly advanced options such as encrypted search and analytics, and also traditional controls such as tokenization, masking, various types of encryption, and anonymization. Titaniam also offers BYOK/HYOK (bring/hold your own key) for data owners to control the security of their data. When attacked, Titaniam minimizes regulatory overhead by providing evidence that sensitive data retained encryption. Titaniam’s interoperable modules can be combined to support hundreds of architectures across multiple clouds, on-prem, and hybrid environments. Titaniam provides the equivalent of at 3+ solutions making it the most effective, and economical solution in the market. Titaniam is featured by Gartner across multiple categories in four markets (Data Security, Data Privacy, Enterprise Key Management, and as a Cool Vendor for 2022). Titaniam is also a TAG Cyber Distinguished Vendor, and an Intellyx Digital Innovator for 2022. In 2022 Titaniam won the coveted SINET16 Security Innovator Award and was also a winner in four categories for the Global Infosec Awards at RSAC2022.

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.

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.

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.

DataVantage provides a wide range of data management solutions that focus on the protection and governance of sensitive information in both mainframe and distributed settings. Among its key products are DataVantage for IMS, Db2, and VSAM, which incorporate sophisticated features for data masking, editing, and extraction, ensuring the safeguarding of Personally Identifiable Information (PII) during non-production activities. Furthermore, DataVantage DME (Data Masking Express) enables economical, real-time data masking for Db2, IMS, and VSAM environments, facilitating compliance without hindering existing operations. For distributed infrastructures, DataVantage Global offers comprehensive data masking, obfuscation, and de-identification processes, promoting both compliance and operational effectiveness across various platforms. Moreover, DataVantage Adviser streamlines the management of COBOL files following mainframe rehosting or application modernization, thereby improving data accessibility and editing capabilities. This holistic approach to data management not only enhances security measures but also supports organizations in their quest for regulatory compliance and operational integrity.

DPM easyData serves as an advanced engine for data de-identification and spoofing, offering methods such as masking, tokenization, anonymization, pseudonymization, and encryption to safeguard sensitive information. Through its data spoofing techniques, the software effectively substitutes entire data sets or fragments with non-sensitive alternatives, generating fictitious data that serves as a robust protective measure. This solution is tailored for web and application server environments, enabling databases to anonymize and tokenize information while enforcing masking policies for users without proper authorization when accessing sensitive materials. DPM easyData stands out for its precise control, allowing administrators to specify which users are permitted to access certain protection measures and outlining the actions they can perform under these policies. Furthermore, its highly customizable framework accommodates a wide variety of data types, offering unparalleled flexibility in defining input and token formats to meet diverse security needs. This adaptability ensures that organizations can maintain stringent data protection standards while managing sensitive information effectively.

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.

Subsalt represents a groundbreaking platform specifically designed to facilitate the utilization of anonymous data on a large enterprise scale. Its advanced Query Engine intelligently balances the necessary trade-offs between maintaining data privacy and ensuring fidelity to original data. The result of queries is fully-synthetic information that retains row-level granularity and adheres to original data formats, thereby avoiding any disruptive transformations. Additionally, Subsalt guarantees compliance through third-party audits, aligning with HIPAA's Expert Determination standard. It accommodates various deployment models tailored to the distinct privacy and security needs of each client, ensuring versatility. With certifications for SOC2-Type 2 and HIPAA compliance, Subsalt has been architected to significantly reduce the risk of real data exposure or breaches. Furthermore, its seamless integration with existing data and machine learning tools through a Postgres-compatible SQL interface simplifies the adoption process for new users, enhancing overall operational efficiency. This innovative approach positions Subsalt as a leader in the realm of data privacy and synthetic data generation.

Modern enterprises encounter severe repercussions if they fail to comply with the growing privacy standards set by regulators and the public alike. To stay competitive, vendors must continuously integrate advanced algorithms aimed at safeguarding sensitive information such as Personally Identifiable Information (PII) and Protected Health Information (PHI). HushHush leads the way in privacy defense through its innovative PII data discovery and anonymization tool, which is also referred to as data de-identification, data masking, and obfuscation software. This tool assists organizations in locating, classifying, and anonymizing sensitive data, ensuring compliance with regulations like GDPR, CCPA, HIPAA/HITECH, and GLBA. It offers a suite of rule-based atomic add-on components that empower users to build robust and secure data anonymization strategies. HushHush's solutions are pre-configured to effectively anonymize both direct identifiers, such as Social Security Numbers and credit card information, as well as indirect identifiers, utilizing a combination of fixed algorithms tailored for this purpose. With such versatile capabilities, HushHush not only enhances data security but also fortifies trust with clients regarding their privacy.

OpenText Data Privacy & Protection Foundation (Voltage) enables organizations to secure sensitive information with a modern, quantum-resilient approach that supports both operational continuity and regulatory compliance. Instead of relying on traditional encryption that breaks workflows, it uses NIST-approved, format-preserving methods that preserve data usability while protecting high-value fields. The platform provides persistent protection, securing data no matter where it lives or how it moves—across cloud infrastructures, analytics pipelines, and distributed applications. With stateless key management, performance stays high even at massive volumes, making it ideal for enterprise-scale deployments. Global organizations trust OpenText because its technologies meet stringent certifications, including FIPS 140-2, Common Criteria, and NIST SP 800-38G. Deep integrations across AWS, Azure, Google Cloud, Snowflake, Hadoop, Databricks, and more ensure seamless adoption without architectural overhaul. This enables businesses to modernize, migrate, or analyze data safely without exposing sensitive information. Ultimately, the platform helps reduce compliance risk, streamline governance, and future-proof data protection strategies.

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.

The hours dedicated to manually anonymizing data detract from essential work tasks. When data is not easily accessible, it becomes trapped, resulting in organizational silos and inefficient knowledge management. Furthermore, there is an ongoing concern about whether the shared data complies with constantly changing regulations such as GDPR, CCPA, and HIPAA. Nymiz addresses these challenges by securely anonymizing personal data using both reversible and irreversible techniques. Original data is substituted with asterisks, tokens, or synthetic surrogates, enhancing privacy while preserving the information's utility. By effectively identifying context-specific data such as names, phone numbers, and social security numbers, our solution delivers superior outcomes compared to conventional tools that lack artificial intelligence features. Additionally, we incorporate an extra security layer at the data level to safeguard against breaches. Ultimately, anonymized or pseudonymized data loses its value if it can be compromised through security vulnerabilities or human mistakes, underscoring the importance of robust protection measures.

Libelle DataMasking (LDM) is a powerful, enterprise-level solution designed for the automated anonymization of sensitive personal information, including names, addresses, dates, emails, IBANs, and credit card details, converting them into realistic substitutes that preserve logical consistency and referential integrity across both SAP and non-SAP environments such as Oracle, SQL Server, IBM DB2, MySQL, PostgreSQL, SAP HANA, flat files, and cloud databases. With the capability to handle up to 200,000 entries per second and facilitate parallel masking for extensive datasets, LDM employs a multithreaded architecture, ensuring efficient reading, anonymization, and writing of data with exceptional performance. The solution boasts over 40 predefined anonymization algorithms—including those for numbers, alphanumeric characters, date shifting, and various forms of masking for names, emails, IBANs, and credit cards—along with tailored templates specifically designed for SAP modules like CRM, ERP, FI/CO, HCM, SD, and SRM. Additionally, its scalability and flexibility make it suitable for organizations of all sizes looking to enhance their data security measures.

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.

Ensure the safe storage, anonymization, masking, mining, redaction, and sharing of sensitive information while achieving complete accuracy and adhering to global data privacy regulations. By effectively separating personally identifiable information (PII) from identified data, you can enjoy substantial time and cost efficiencies without sacrificing functionality. Integrate PII Vault to foster groundbreaking solutions, accelerate your time to market, and provide unparalleled security for PII across all platforms. This approach enables you to harness data for creating more precise and targeted communications. Simplify the process with a straightforward method to anonymize all data prior to its entry into your system. Utilize Poly-Anonymization™ to merge various anonymous data sets at the individual level without ever accessing PII post-anonymization. Furthermore, substitute PII with a compliant, multi-valued, non-identifying key that facilitates anonymous data matching across different organizations, enhancing collaborative efforts while maintaining privacy. This comprehensive strategy not only protects individual identities but also empowers organizations to derive meaningful insights from their data securely.

To protect sensitive information, including personally identifiable information (PII), organizations must implement techniques such as pseudonymization and anonymization for secondary purposes like comparative effectiveness studies, policy evaluations, and research in life sciences. This process is essential as businesses amass vast quantities of data to detect patterns, understand customer behavior, and foster innovation. Compliance with regulations like HIPAA and GDPR mandates the de-identification of data; however, the difficulty lies in the fact that many de-identification tools prioritize the removal of personal identifiers, often complicating subsequent data usage. By transforming PII into forms that cannot be traced back to individuals, employing data anonymization and pseudonymization strategies becomes crucial for maintaining privacy while enabling robust analysis. Effectively utilizing these methods allows for the examination of extensive datasets without infringing on privacy laws, ensuring that insights can be gathered responsibly. Selecting appropriate de-identification techniques and privacy models from a wide range of data security and statistical practices is key to achieving effective data usage.

Utilize Oracle Advanced Security to encrypt application tablespaces, thereby safeguarding sensitive data from unauthorized access. Implementing redaction policies helps curb the spread of sensitive information and enhances compliance with data protection laws. Transparent Data Encryption (TDE) acts as a barrier against potential attackers who might attempt to read sensitive data directly from storage by ensuring encryption of data at rest within the database. You can encrypt individual data columns, entire tablespaces, database exports, and backups for better control over access to sensitive information. Data Redaction works in conjunction with TDE to further mitigate the risk of unauthorized data exposure within applications by obscuring sensitive information before it exits the database. By allowing for partial or full redaction, it prevents extensive extraction of sensitive data into reports and spreadsheets. Additionally, encryption is carried out at the database kernel level, which removes the necessity for modifications to existing applications, thus streamlining the implementation process. Ultimately, these security measures work together to provide a robust framework for protecting sensitive data throughout its lifecycle.

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

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.

The Dynamic Data Replicator is a multifunctional tool that provides a range of capabilities. It enables the quick setup of new non-production environments, improves the efficiency of client refresh processes by reducing the necessary storage space, allows for targeted data copying as needed, and upholds data security through the application of GDPR-compliant protocols for non-production environments. This application ensures that SAP users have regular access to up-to-date and relevant data for tasks including production support, testing, and training, thus equipping them with the essential information at the right time. Additionally, its flexible design makes it an invaluable resource for organizations looking to optimize their data management strategies.

Don't allow concerns about data security or privacy to obstruct your innovation efforts driven by analytics. Dataguise offers robust protection for personal and sensitive information through adaptable masking and encryption solutions, ensuring you can maximize business value. With data sets prepared for analysis delivered in near real-time, you can gain fresher insights and make informed decisions based on a complete understanding of your data landscape. Recognizing the diverse and evolving needs of our customers, Dataguise has built a strong network of carefully selected partners to provide more comprehensive solutions, services, and expertise. This executive guide illustrates how to safeguard data privacy while enhancing data value. When looking at various data discovery solutions, it's clear that Dataguise has a longer history, accommodates a wider array of data types and repositories, achieves lower false-positive rates, and consistently scans data at scale more effectively. By choosing Dataguise, organizations can confidently harness their data to drive decisions that best serve their business objectives, ultimately fostering a culture of informed and strategic decision-making.

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

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.

Your IT department can implement advanced data masking techniques to restrict access to sensitive information, utilizing adaptable masking rules that correspond to the authentication levels of users. By incorporating mechanisms for blocking, auditing, and notifying users, IT staff, and external teams who interact with confidential data, the organization can maintain adherence to its security protocols as well as comply with relevant industry and legal privacy standards. Additionally, you can tailor data-masking strategies to meet varying regulatory or business needs, fostering a secure environment for personal and sensitive information. This approach not only safeguards data but also facilitates offshoring, outsourcing, and cloud-based projects. Furthermore, large datasets can be secured by applying dynamic masking to sensitive information within Hadoop environments, enhancing overall data protection. Such measures bolster the integrity of the organization's data security framework.

You can forget about manual content classification or data entry. Doculayer.ai provides a configurable workflow that includes document processing services such as OCR, document type classification and topic classification, as well data extraction and masking. Doculayer.ai allows business users to take control of their learning and training by providing an intuitive user interface that makes labeling documents and data easy. Our hybrid data extraction approach allows machine learning models to be combined with patterns, rules, and library scripts to produce better results in less time. Data masking is an option to anonymize or pseudonymize sensitive data in documents. Doculayer.ai provides document intelligence to your Content Services Platform and Business Process Management systems. Your existing IT environment can be augmented for document processing by machine learning, natural language processing and computer vision technologies.

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.

Privacy1 infrastructure brings transparency, safeguards GDPR | CCPA compliance, builds trust for your business. The solution shields your data centric organizations, lower data leak risks, ensures that no personal data is processed except with the right permission. The service has built in rich features you need to meet data compliance requirements and enforce your organizational data security to the highest level

Syntheticus® revolutionizes the way organizations exchange data, addressing challenges related to data accessibility, scarcity, and inherent biases on a large scale. Our synthetic data platform enables you to create high-quality, compliant data samples that align seamlessly with your specific business objectives and analytical requirements. By utilizing synthetic data, you gain access to a diverse array of premium sources that may not be readily available in the real world. This access to quality and consistent data enhances the reliability of your research, ultimately resulting in improved products, services, and decision-making processes. With swift and dependable data resources readily available, you can expedite your product development timelines and optimize market entry. Furthermore, synthetic data is inherently designed to prioritize privacy and security, safeguarding sensitive information while ensuring adherence to relevant privacy laws and regulations. This forward-thinking approach not only mitigates risks but also empowers businesses to innovate with confidence.

Cutting-edge technology and services are designed to securely transform and elevate sensitive information into actionable insights, thereby fostering innovation and creating new avenues for revenue generation. Through the use of the Mimic synthetic data engine, businesses can effectively synthesize their data assets, ensuring that consumer privacy is safeguarded while preserving the statistical relevance of the information. This synthetic data can be leveraged for a variety of internal initiatives, such as analytics, machine learning, artificial intelligence, marketing efforts, and segmentation strategies, as well as for generating new revenue streams via external data monetization. Mimic facilitates the secure transfer of statistically relevant synthetic data to any cloud platform of your preference, maximizing the utility of your data. In the cloud, enhanced synthetic data—validated for compliance with regulatory and privacy standards—can support analytics, insights, product development, testing, and collaboration with third-party data providers. This dual focus on innovation and compliance ensures that organizations can harness the power of their data without compromising on privacy.

Adaptive is a robust data security platform aimed at safeguarding sensitive data from exposure across both human and automated entities. It features a secure control plane that allows for the protection and access of data, utilizing an agentless architecture that does not demand any network reconfiguration, making it suitable for deployment in both cloud environments and on-premises settings. This platform empowers organizations to grant privileged access to their data sources without the need to share actual credentials, thereby significantly bolstering their security stance. Additionally, it supports just-in-time access to an array of data sources such as databases, cloud infrastructure, data warehouses, and web services. Furthermore, Adaptive streamlines non-human data access by linking third-party tools or ETL pipelines through a unified interface, while ensuring data source credentials remain secure. To further reduce the risk of data exposure, the platform incorporates data masking and tokenization techniques for users with non-privileged access, all while maintaining existing access workflows. Moreover, it ensures thorough audibility by providing identity-based audit trails that cover all resources, enhancing accountability and oversight in data management practices. This combination of features positions Adaptive as a leader in the realm of data security solutions.

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Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

Safeguard your confidential SAP information by addressing security issues and adhering to data protection laws like the EU's General Data Protection Regulation (GDPR), South Africa's POPI Act, and California's Consumer Privacy Act of 2018 (CCPA) through the use of Data Secure™. In the current business landscape, ensuring data security has become paramount. Data Secure™, which is integrated within EPI-USE Labs' Data Sync Manager™ (DSM) suite, effectively tackles your data security concerns. This comprehensive solution features pre-set masking rules, allowing you to obfuscate any non-key field across various client-dependent SAP tables through diverse methods, including table look-up mappings, constant values, or even clearing a field entirely. Additionally, you can tailor these rules to suit your specific security requirements. By implementing Data Secure, your organization can comply with widely recognized data privacy standards and regulations, ensuring the protection of sensitive information in line with GDPR, Sarbanes Oxley, and the BDSG (Bundesdatenschutzgesetz). Ultimately, adopting such robust security measures not only enhances compliance but also fosters trust among your clients and stakeholders.

Safeguard your data comprehensively with a robust, enterprise-level security solution that spans multicloud, hybrid, and on-premises environments, accommodating all types of data. Enhance security measures across diverse platforms while seamlessly discovering and categorizing structured, semi-structured, and unstructured data. Assess and prioritize data risks by considering both incident context and the potential for additional capabilities. Streamline data management through a unified service or dashboard that centralizes oversight. Guard against unauthorized data exposure and prevent breaches effectively. Make data-centric security, compliance, and governance processes simpler and more efficient. Create a consolidated perspective to glean insights on vulnerable data and users, while actively managing a Zero Trust framework and enforcing relevant policies. Leverage automation and workflows to save both time and resources, and ensure support for a wide range of file shares and data repositories, including those in public, private, data center, and third-party cloud environments. Address not only your current requirements but also future integrations as you evolve and expand cloud use cases, thereby enhancing your overall data security strategy. By implementing these measures, you can significantly bolster your organization’s resilience against data-related threats.

The Mage™ Dynamic Data Masking module, part of the Mage data security platform, has been thoughtfully crafted with a focus on the needs of end customers. Developed in collaboration with clients, Mage™ Dynamic Data Masking effectively addresses their unique requirements and challenges. Consequently, this solution has advanced to accommodate virtually every potential use case that enterprises might encounter. Unlike many competing products that often stem from acquisitions or cater to niche scenarios, Mage™ Dynamic Data Masking is designed to provide comprehensive protection for sensitive data accessed by application and database users in production environments. Additionally, it integrates effortlessly into an organization’s existing IT infrastructure, eliminating the need for any substantial architectural modifications, thus ensuring a smoother transition for businesses implementing this solution. This strategic approach reflects a commitment to enhancing data security while prioritizing user experience and operational efficiency.

Renowned startpoint security software products in the IRI Data Protector suite and IRI Voracity data management platform will: classify, find, and mask personally identifiable information (PII) and other "data at risk" in almost every enterprise data source and sillo today, on-premise or in the cloud. Each IRI data masking tool in the suite -- FieldShield, DarkShield or CellShield EE -- can help you comply (and prove compliance) with the CCPA, CIPSEA, FERPA, HIPAA/HITECH, PCI DSS, and SOC2 in the US, and international data privacy laws like the GDPR, KVKK, LGPD, LOPD, PDPA, PIPEDA and POPI. Co-located and compatible IRI tooling in Voracity, including IRI RowGen, can also synthesize test data from scratch, and produce referentially correct (and optionally masked) database subsets. IRI and its authorized partners around the world can help you implement fit-for-purpose compliance and breach mitigation solutions using these technologies if you need help. ​

Statice is a data anonymization tool that draws on the most recent data privacy research. It processes sensitive data to create anonymous synthetic datasets that retain all the statistical properties of the original data. Statice's solution was designed for enterprise environments that are flexible and secure. It incorporates features that guarantee privacy and utility of data while maintaining usability.

IRI DarkShield uses several search techniques to find, and multiple data masking functions to de-identify, sensitive data in semi- and unstructured data sources enterprise-wide. You can use the search results to provide, remove, or fix PII simultaneously or separately to comply with GDPR data portability and erasure provisions. DarkShield jobs are configured, logged, and run from IRI Workbench or a restful RPC (web services) API to encrypt, redact, blur, etc., the PII it discovers in: * NoSQL & RDBs * PDFs * Parquet * JSON, XML & CSV * Excel & Word * BMP, DICOM, GIF, JPG & TIFF using pattern or dictionary matches, fuzzy search, named entity recognition, path filters, or image area bounding boxes. DarkShield search data can display in its own interactive dashboard, or in SIEM software analytic and visualization platforms like Datadog or Splunk ES. A Splunk Adaptive Response Framework or Phantom Playbook can also act on it. IRI DarkShield is a breakthrough in unstructured data hiding technology, speed, usability and affordability. DarkShield consolidates, multi-threads, the search, extraction and remediation of PII in multiple formats and folders on your network and in the cloud, on Windows, Linux, and macOS.

The Synthetic Data Vault (SDV) is a comprehensive Python library crafted for generating synthetic tabular data with ease. It employs various machine learning techniques to capture and replicate the underlying patterns present in actual datasets, resulting in synthetic data that mirrors real-world scenarios. The SDV provides an array of models, including traditional statistical approaches like GaussianCopula and advanced deep learning techniques such as CTGAN. You can produce data for individual tables, interconnected tables, or even sequential datasets. Furthermore, it allows users to assess the synthetic data against real data using various metrics, facilitating a thorough comparison. The library includes diagnostic tools that generate quality reports to enhance understanding and identify potential issues. Users also have the flexibility to fine-tune data processing for better synthetic data quality, select from various anonymization techniques, and establish business rules through logical constraints. Synthetic data can be utilized as a substitute for real data to increase security, or as a complementary resource to augment existing datasets. Overall, the SDV serves as a holistic ecosystem for synthetic data models, evaluations, and metrics, making it an invaluable resource for data-driven projects. Additionally, its versatility ensures it meets a wide range of user needs in data generation and analysis.

IRI Data Masking as a Service is a professional services engagement to secure PII. Step 1: IRI agrees under NDA terms to classify, analyze, and report on the sensitive, at-risk data in your sources. We will discuss an initial cost estimate then hone it with you during data discovery. Step 2: Transfer the unprotected data to a secure on-premise or cloud-based staging area or provide remote, supervised access to IRI to the data sources(s) at issue. We'll use the tools in the award-winning IRI Data Protector suite to mask that data according to your business rules, on an ad hoc or recurring basis. Step 3: Our experts can also move newly-masked data to incremental replicas in production or to lower non-production environments. From either, the data is now safe for analytic initiatives, development, testing, or training. Tell us if you need additional services, like re-ID risk scoring (expert determination) of the de-identified data. This approach provides the benefits of proven data masking solution technology and services without the need to learn and customize new software from scratch. If you do want to use the software in-house, you will have everything pre-configured for easier long-term self-use and modification.

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.

Data Safe serves as a comprehensive management hub for your Oracle Databases, enabling you to grasp the sensitivity levels of your data, analyze potential risks, and implement measures to mask sensitive information. It also facilitates the establishment and oversight of security protocols, user security evaluations, and user activity monitoring, while ensuring compliance with data protection regulations. Regardless of whether you're operating Oracle Autonomous Database, Oracle Database Cloud Service (including Exadata, virtual machines, or bare metal), or managing Oracle Databases within your own on-premises environment, Data Safe provides critical data security features that enhance your security posture and mitigate risks. Furthermore, it assists in assessing user risks by pinpointing crucial users, roles, and privileges, while allowing you to configure audit policies and gather user activity data to detect any anomalies. In addition, Data Safe aids in the identification of sensitive data, clarifying its locations, and minimizes risks associated with non-production data sets by effectively masking sensitive information. By leveraging these capabilities, organizations can foster a more secure data environment and maintain better control over their information assets.

Safeguard your file and database information from potential abuse while ensuring compliance with both industry standards and governmental regulations by utilizing this comprehensive suite of integrated encryption solutions. IBM Guardium Data Encryption offers a cohesive set of products that share a unified infrastructure. These scalable solutions incorporate encryption, tokenization, data masking, and key management features, essential for protecting and regulating access to databases, files, and containers across hybrid multicloud environments, thereby securing assets located in cloud, virtual, big data, and on-premises settings. By effectively encrypting file and database data through functionalities like tokenization, data masking, and key rotation, organizations can successfully navigate compliance with various regulations, including GDPR, CCPA, PCI DSS, and HIPAA. Moreover, the extensive capabilities of Guardium Data Encryption—including data access audit logging and comprehensive key management—further assist organizations in meeting critical compliance requirements, ensuring that sensitive data remains protected at all times. Ultimately, implementing such robust encryption measures not only enhances security but also builds trust among stakeholders.