Gartner defines agentic analytics as software used for the process of data analysis that applies AI agents across the data-to-insight workflow, orchestrating tasks semi-autonomously or autonomously toward stated goals that support, augment or automate insights. Agentic analytics’ must-have capabilities are data source connectivity, data preparation, agent workflow orchestration, automated insights and natural language query. Optional capabilities include data storytelling, a coding assistant, function calling, agent memory, embedded analytics and platform administration. Agentic analytics is the evolution of augmented analytics through the application of AI agents to data analysis. Must-have capabilities are: data source connectivity data preparation agent workflow orchestration automated insights natural language query Optional capabilities include: data storytelling a coding assistant function calling agent memory embedded analytics platform administration
A data and analytics governance platform is a set of integrated business and technology capabilities that help business leaders and users develop and manage a diverse set of governance policies and enforce those policies across business and data management systems. These platforms are unique from data management in that data management focuses on policy execution, whereas D&A platforms are used primarily by business roles — not only or even specifically IT roles — for policy management. Data and analytics (D&A) leaders who are investing in operationalizing and automating the work of D&A governance should evaluate this market. The work of D&A governance primarily includes policy setting and policy enforcement, and collaborates with data management (policy execution). Use cases are employed across numerous governance policy categories and multiple business scenarios and asset types (data, KPIs, analytics models). The intersection of use-case/business scenarios, policy categories and assets to be governed is then used to identify the technology capability. These capabilities may share similar names across policy categories, but may not mean the same thing, or may be used differently by various governance personas. For example, data classification in a data security implementation would be quite different from a data classification effort for creating trust models, which would be based on lineage and curation.
Gartner defines metadata management solutions as applications to enable the collection, analysis and orchestration of metadata related to organizational data assets. These solutions enable workflow and operational support to make data easy to find, use and manage. They do this by collating metadata in any form from within its own application and third-party systems, and providing the ability to search, analyze and make decisions on the collated results. They also provide transparent cross-referencing over all related metadata, and derive insights from data (such as usage patterns and performance) through analysis of metadata to support a wide range of data-driven initiatives.