Data exchange ties together different systems, enabling them to communicate with each and each other. This process is able to support a broad variety of business scenarios and facilitates collaboration between teams.
Businesses of all sizes and across all industries can benefit from best practices for seamless exchange of data. This helps them reduce the time spent on data acquisition and to monetize their data assets and improve decision-making, foster innovation, and improve interoperability. However, there are a few challenges to be aware like inconsistencies in data, lack of transparency and trust, interoperability and data integration challenges and the need for a standardized data Governance framework.
Many companies are creating new revenue streams through data exchange, which is bringing in additional revenue and enhancing their operations. AccuWeather for instance, generates revenue by putting its repositories with historical and forecasted weather information on platforms for data exchange. This lets them connect with a variety of data users, from agriculture sectors to event organizers.
To manage and optimize data exchange, it is necessary to assess the current processes and devise a data management strategy for the entire organization. This will require a deep understanding of the value data exchange can bring, the requirements and expectations of the stakeholders, and the capabilities of current data sources. It should also include a plan for data integration that is flexible enough to adjust to changes in technology and to meet future demands and opportunities. In the ideal scenario, this would include an architecture that separates databases and applications, enabling the design of enterprise data integration systems that favor web services and brokered messaging techniques.