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data integration

Contributor(s): Ivy Wigmore

Data integration is the process of retrieving data from multiple source systems and combining it in such a way that it can yield consistent, comprehensive, current and correct information for business reporting and analysis. The source systems may be various types of devices and the data may be in a variety of formats.  

Customer data integration was one of the first applications. CDI is the process of consolidating and managing customer information from all available sources, including contact details, customer valuation data, and information gathered through interactions such as direct marketing. CDI software helps to ensure that departments across a business can reliably access the most current and complete view of customer information available.  

Similarly, sensor fusion integrates data from multiple sensors to add context and achieve a more complete view of the sensors' subject or environment. Sensors detect and respond to some type of input from the physical environment. The output sensor data may be used to provide information or input to another system or to guide a process. For an organization, integrated sensor data yields insights faster and enables more sophisticated analysis than is possible when the output of each sensor is processed separately.  

The amount of data being collected and managed within the enterprise and elsewhere continues to grow exponentially, and that rate is only expected to increase as the Internet of Things (IoT) develops further. The essence of the IoT is connectivity among almost anything conceivable, along with the capacity for those things to share data. The challenge, however, is realizing the potential value of all that data. Data integration and analysis are essential to that effort.

This was last updated in July 2017

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