Data exchange brings together disparate systems, enabling them to communicate with one and each other. This facilitates a range of business scenarios, and helps to increase the amount of effective collaboration between teams and customers.
Businesses of all sizes and in all sectors can benefit from the best practices for seamless exchange of data. This lets them reduce the time spent on data acquisition and to monetize their data assets, enhance decision-making, promote innovation, and improve interoperability. However, there are a few hurdles to be aware of for example, data inconsistencies, lack of transparency and trust data integration and interoperability challenges, and the need for a standardized Data Governance framework.
Many companies are creating new revenue streams with data exchange, earning additional income and improving their operations. For example, weather data providers like AccuWeather earn revenue by placing their repositories of historical and predictive data on data exchange platforms where they can reach a wide spectrum of data consumers ranging from agricultural sectors to event planners.
To control and optimize data exchange, it is important to analyze the current processes and formulate an appropriate data management strategy for the entire company. This should include a comprehensive understanding of the value that data exchange can bring, the requirements and expectations of stakeholders, as also the capabilities of current data sources. It should also include an integration strategy that is flexible enough for future requirements and opportunities, and is able to adapt to technological changes. Idealy, it should also include an architecture that decouples applications and databases, which will help support design concepts for enterprise data integration which favor web-based services and brokered messaging.
