Gartner defines data integration as the discipline comprising the architectural patterns, methodologies and tools that allow organizations to achieve consistent access and delivery of data across a wide spectrum of data sources and data types to meet the data consumption requirements of business applications and end users. Data integration tools enable organizations to access, integrate, transform, process and move data that spans various endpoints and across any infrastructure to support their data integration use cases. The market for data integration tools includes vendors that offer a stand-alone software product (or products) to enable the construction and implementation of data access and data delivery infrastructure for a variety of data integration use cases.
File analysis (FA) products analyze, index, search, track and report on file metadata and file content, enabling organizations to take action on files according to what was identified. FA provides detailed metadata and contextual information to enable better information governance and organizational efficiency for unstructured data management. FA is an emerging solution, made of disparate technologies, that assists organizations in understanding the ever-growing volume of unstructured data, including file shares, email databases, enterprise file sync and share, records management, enterprise content management, Microsoft SharePoint and data archives.
The hybrid cloud storage market comprises diverse deployment patterns with underlying technologies that address a wide range of data types. Products in this market must facilitate seamless data services across different environments, including disparate data centers, co-locations, edge locations and public cloud infrastructure. Hybrid cloud data solutions are offered through various means such as distributed hybrid infrastructure, hybrid cloud storage platforms, data transfer appliances, hyperconverged solutions, storage arrays, software-defined storage (SDS) products, and comprehensive data management software.