Data exchange ties together disparate systems, enabling them to communicate with each other. This process supports a wide variety of business scenarios and encourages effective collaboration between teams.
All sizes of businesses and in all sectors can benefit from best practices that facilitate seamless exchange of data. This enables them to reduce the time spent on data acquisition and to monetize their data assets, enhance decision-making, promote innovation, and facilitate interoperability. However there are some obstacles to be aware of like data inconsistencies, a lack of transparency and trust, interoperability and data integration challenges, and the need for a standardized data Governance framework.
Data exchange is a method for a variety of organizations to generate new revenue streams, thereby increasing their revenue and enhancing operations. For instance weather data providers such as AccuWeather generate revenue by putting their repositories of historical as well as predictive data on data exchange platforms, which are accessible to a broad variety of data consumers, from industries like agriculture to event planners.
Managing and optimizing data exchange requires a thorough evaluation of the current processes and the creation of an enterprise-wide strategy for managing data. This should include a thorough understanding of the benefits that data exchange can bring as well as the expectations and needs of all stakeholders, as in the capabilities of current data sources. It should also include a plan for data integration that is flexible enough to adjust to technological changes and to take advantage of future demands and opportunities. Ideally, this should also be built around an architecture that is decoupled from applications and databases, supporting the design of enterprise data integration systems that favor web services and brokered messaging methods.