Data exchange lets disparate systems communicate. This facilitates a range of business uses, and helps to increase the amount of collaboration between teams and customers.
Companies of all sizes and industries can leverage best practices for seamless data exchange allowing them to streamline the acquisition of data, monetize data assets, boost decision-making, promote innovation and facilitate interoperability. However, there are a few issues to be aware of including inconsistencies in data, lack of transparency and trust, interoperability issues and data integration and the need for a clear Data Governance framework.
Many organizations are creating new revenue streams through data exchange, which is bringing in additional revenue and enhancing their operations. For example, weather data providers like AccuWeather generate revenue by putting their repositories of historical and predictive data on data exchange platforms which are accessible to a broad range of users, ranging from agriculture sectors to event planners.
To manage and optimize data exchange, it’s necessary to assess the current processes and formulate a data management strategy for the entire company. This should include a thorough understanding of the value that data exchange can bring as well as the expectations and needs of all stakeholders, as the capabilities of existing data sources. It should also include a strategy for data integration that is flexible enough to adjust to changes in technology and to meet future demands and opportunities. Idealy, it should also include an architecture that decouples applications and databases, which will help support design patterns for data integration in the enterprise which favor web-based services and brokered messaging.
