Managing and Optimizing Data Exchange

Data exchange allows disparate systems to communicate. This process is able to support a broad range of business use-cases and promotes efficient collaboration between teams.

All sizes of businesses and sectors can benefit from best practices to ensure seamless data exchange, making it easier to streamline data acquisition, monetize data assets, augment decision-making, encourage innovation, and enable interoperability. However there are some challenges to be aware, such as inconsistent data, lack of transparency and trust data integration and interoperability challenges and the need for a clear Data Governance framework.

Many organizations are developing new revenue streams through data exchange, earning additional income and improving their operations. AccuWeather, for example earns revenue through the placement of its repositories with historical and predictive weather data on platforms for data exchange. This lets them connect with a variety of data users, ranging from events to the agriculture sector.

Managing and optimizing data exchange requires a thorough analysis of current processes as well as the development of an enterprise-wide strategy for managing data. This will require a deep understanding of the value data exchange can bring, the requirements and expectation of stakeholders, as also the capabilities of existing data sources. It should also include an approach to integration that is flexible enough for future requirements and opportunities and is able to adjust to technological changes. In the ideal scenario, this would include an architecture that separates databases and applications, in support of enterprise-level data integration strategies that favor web services and brokered messaging techniques.

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