Alternatives to IRI FieldShield

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.

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. ​

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.

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

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.

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.

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

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

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.

IRI CellShield®, protects sensitive information in Microsoft Excel®, allowing you to comply data privacy laws. You can protect your columns with reversible or non-reversible masking options. CellShield protects your data, no matter how many sheets they are. Multiple search methods are available to locate and report on PII across the LAN. Protect it all at once with CellShield. Intuitive graphical dialogs allow you to classify and mask it. CellShield's core technology uses the award-winning IRI FieldShield flat file and database data masking product. Data that is hidden in one platform can be seen in another. CellShield EE, the only fully-featured professional data discovery, masking and auditing package for Excel 2010, 2016, and 2019 (plus Office 365 workbooks) in your LAN, is available. CellShield EE goes beyond the security and scope a single password can provide by combining and automating all of these additional capabilities.

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

For more four decades, IRI CoSort has defined the state-of-the-art in big data sorting and transformation technology. From advanced algorithms to automatic memory management, and from multi-core exploitation to I/O optimization, there is no more proven performer for production data processing than CoSort. CoSort was the first commercial sort package developed for open systems: CP/M in 1980, MS-DOS in 1982, Unix in 1985, and Windows in 1995. Repeatedly reported to be the fastest commercial-grade sort product for Unix. CoSort was also judged by PC Week to be the "top performing" sort on Windows. CoSort was released for CP/M in 1978, DOS in 1980, Unix in the mid-eighties, and Windows in the early nineties, and received a readership award from DM Review magazine in 2000. CoSort was first designed as a file sorting utility, and added interfaces to replace or convert sort program parameters used in IBM DataStage, Informatica, MF COBOL, JCL, NATURAL, SAS, and SyncSort. In 1992, CoSort added related manipulation functions through a control language interface based on VMS sort utility syntax, which evolved through the years to handle structured data integration and staging for flat files and RDBs, and multiple spinoff products.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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

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

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

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.

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.

Protect sensitive information at every stage—whether on-site, in the cloud, or within extensive data analytic systems. Voltage encryption provides a robust solution for data privacy, mitigates the risks associated with data breaches, and enhances business value through the secure utilization of data. Implementing effective data protection fosters customer trust and ensures adherence to international regulations such as GDPR, CCPA, and HIPAA. Privacy laws advocate for methods like encryption, pseudonymization, and anonymization to safeguard personal information. Voltage SecureData empowers organizations to anonymize sensitive structured data while still allowing its use in a secure manner, facilitating business growth. It's essential to guarantee that applications function on secure data that moves seamlessly through the organization, without any vulnerabilities, decryption requirements, or negative impacts on performance. SecureData is compatible with a wide array of platforms and can encrypt data in various programming languages. Additionally, the Structured Data Manager incorporates SecureData, enabling companies to protect their data efficiently and continuously throughout its entire lifecycle, from initial discovery all the way to encryption. This comprehensive approach not only enhances security but also streamlines data management processes.

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.

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.

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

The 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.

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.

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

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.

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.

Discover the advantages of utilizing a Trusted Third Party (TTP) for the meticulous pseudonymization of personal data, enabling you to conduct data analysis while adhering to GDPR regulations. Our fundamental offering revolves around the pseudonymization of personal data, utilizing techniques that ensure irreversible pseudonyms and the enhancement of behavioral data. The pseudonymized dataset serves as the foundation for subsequent processing by our clients. Additionally, our filtering service allows for the proportional sharing of personal data, ensuring privacy is maintained throughout the process. We carefully filter information through a rigorously managed pseudonymized whitelist, guaranteeing that only data pertaining to individuals on this list is shared. Viacryp also provides expert privacy consultation focused on the safeguarding and security of personal data. In collaboration with our partners, we offer guidance on the necessary measures organizations should implement to meet GDPR compliance, addressing both technical solutions and organizational protocols. By prioritizing these compliance strategies, businesses can enhance their data protection practices effectively.

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.

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

Secure data transmission is essential for both training and testing environments. It has been incorporated into the U.S. NCDSMO Baseline for SABI environments since 2009 and comes with built-in support for various protocols including DIS, HLA, TENA, RTP, and MPEG2-TS, while conforming to NSA Raise the Bar and NIST standards. The High Performance Computing Modernization Program Office (HPCMPO) has assessed its compatibility with the Defense Research & Engineering Network (DREN) and Secure Defense Research & Engineering Network (SDREN). SimShield facilitates fully automated, predictable, controlled, and audited two-way communication, as well as the sanitization of events across distinct, air-gapped security domains. In contrast to Government-Off-The-Shelf (GOTS) solutions, it ensures access to the latest features without incurring additional costs. This system allows multiple national agencies or coalition forces to train simultaneously within a singular, real-world environment. Furthermore, it ensures sanitized information sharing, which accelerates the detection and resolution of issues during the Research, Development, Test & Evaluation (RDT&E) phases. Ultimately, this robust architecture enhances the overall efficiency and effectiveness of collaborative defense efforts.

Streamlining privacy through automated secure redaction for document sharing is the cornerstone of Rectify's approach. By utilizing privacy-centric artificial intelligence, Rectify efficiently eliminates sensitive information during the data sharing process. This innovation significantly reduces the need for human intervention in identifying and expunging consumer identities, trade secrets, intellectual property, and other confidential data from datasets destined for third-party distribution. Our team has safeguarded tens of millions of pages, and the number continues to rise. With our advanced "privacy-enabled AI" for deidentification, organizations can move away from tedious manual redaction processes. The risks associated with disclosing sensitive information without a reliable redaction tool can be severe, making it imperative to choose an effective redaction service. Rectify offers a comprehensive solution tailored to your redaction requirements, ensuring your business's security and privacy are maintained at all times. By opting for Rectify's secure redaction, you can automate privacy protection and foster confidence in your data handling practices.

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.

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

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

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

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.