Active metadata management is a set of capabilities that enables continuous access and processing of metadata that support ongoing analysis over a different spectrum of maturity, use cases and vendor solutions. Active metadata outputs range from design recommendations based upon execution results and reports of runtime steps through, and indicators of, business outcomes achieved. The resulting recommendations from those analytics are issued as design inputs to humans or system-level instructions that are expected to have a response.
The data integration tools market comprises stand-alone software products that allow organizations to combine data from multiple sources, including performing tasks related to data access, transformation, enrichment and delivery. Data integration tools enable use cases such as data engineering, operational data integration, delivering modern data architectures, and enabling less-technical data integration. Data integration tools are procured by data and analytics (D&A) leaders and their teams for use by data engineers or less-technical users, such as business analysts or data scientists. These products are consumed as SaaS or deployed on-premises, in public or private cloud, or in hybrid configurations.
Data and Analytics refers to products and services that enable organizations to collect, integrate, analyze, and act on data to drive informed decision-making and business outcomes. This category includes markets that focus on empowering enterprises to manage data pipelines, ensure data quality and governance, extract insights through advanced analytics, and machine learning across structured and unstructured data environments.
Gartner defines integration platform as a service (iPaaS) as a vendor-managed cloud service that enables end users to implement integrations between applications, services and data sources, both internal and external to their organization. iPaaS enables end users of the platform to integrate a variety of internal and external applications, services and data sources for at least one of the three main patterns of integration technology use: data consistency, multistep process and composite services. These integration use cases are most commonly implemented via intuitive low-code or no-code developer environments, though some vendors provide more complex developer tooling.