Gartner defines analytics and business intelligence platforms (ABI) as those that enable organizations to model, analyze and visualize data to support informed decision making and value creation. These platforms facilitate the preparation of data and the creation of interactive dashboards, reports and visualizations to uncover patterns, predict trends and optimize operations. By doing so, they empower users to collaborate and effectively communicate the dimensions and measures that drive their organization. The platforms may also optionally include the ability to create, modify or enrich a semantic model, including business rules. Analytics and business intelligence platforms integrate data from multiple sources, such as databases, spreadsheets, cloud services and external data feeds, to provide a unified view of data, breaking down silos and transforming raw data into meaningful insights. They also allow users to clean, transform and prepare data for analysis, in addition to creating data models that define relationships between different data entities.
Data masking is based on the premise that sensitive data can be transformed into less sensitive but still useful data. This is necessary to satisfy application testing use cases that require representative and coherent data, as well as analytics that involve the use of aggregate data for scoring, model building and statistical reporting. The market for data protection, DM included, continues to evolve with technologies designed to redact, anonymize, pseudonymize, or in some way deidentify data in order to protect it against confidentiality or privacy risk.
Digital communications governance and archiving solutions (DCGA) are designed to enforce corporate governance and regulatory compliance across a growing number of digital communication tools available to employees. For the various communication tools in use across the enterprise, DCGA solutions enable consistent policy management, enforcement and reporting capabilities. Enterprise organizations face a growing number of regulatory mandates, such as the Financial Industry Regulation Authority (FINRA), Financial Conduct Authority (FCA), Health Insurance Portability and Accountability Act (HIPAA), and General Data Protection Regulation (GDPR). In addition, they must adhere to corporate governance guidelines, such as proper employee conduct and handling of sensitive data, in the use of digital communication tools. The DCGA market aligns to vendors that develop archive- and platform-integrated solutions, which capture and analyze communication channels, and those that solely develop communication connectors to a variety of communication tools used by enterprises. Organizations utilize DCGA solutions to proactively manage and collect communication content. As part of their direct integration and ability to centralize access to communication data, DCGA solutions facilitate multiple use cases such as supervision, surveillance, e-discovery and data insights. While email has been the most traditional communication channel in the scope of DCGA solutions, there are multiple types of communication channels to be factored into a governance strategy. The scope of these communication tools is constantly changing as new messaging applications are frequently introduced to the market and adopted by employees. Recent evidence suggests enterprise organizations’ customers are dictating the communication tool of choice.
The structured data archiving and application retirement market is identified by an array of technology solutions that manage the life cycle of application-generated data and accommodate corporate and regulatory compliance requirements. Application-generated data is inclusive of databases and related unstructured data. SDA solutions focus on improving the storage efficiency of data generated by on-premises and cloud-based applications and orchestrating the retirement of legacy application data and their infrastructure. The SDA market includes solutions that can be deployed on-premises, and on private and public infrastructure, and includes managed services offerings such as SaaS or PaaS.
Test Data Management (TDM) is the process of provisioning data for development and testing in preproduction environments. It ensures efficient, high-quality datasets while safeguarding data privacy and sensitive corporate information to meet compliance and security requirements. Modern TDM solutions leverage synthetic data generation, alongside data subsetting and masking techniques, to provide realistic yet secure test data. These solutions are widely used by software developers, QA engineers, data analysts, and IT security teams to optimize testing, maintain regulatory compliance, and enhance application reliability.