Demand Signal Repository

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What Does Demand Signal Repository Mean?

A demand signal repository (DSR) is a database or a data warehouse that is used for aggregating and structuring demand data. Companies use this tool to make efficient use of demand data and to anticipate change in business process automation and other planning enhancements.

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Techopedia Explains Demand Signal Repository

Some experts characterize the DSR as a database that curates and structures a lot of raw or unstructured data, or matches it against more defined data sets to create better business intelligence in terms of customer demand. The DSR can also be used for "cleansing" data; the idea is that a DSR has to comb through relatively unstructured data sets and deal with a number of different issues. Unstructured data can include problems with typographical errors, missing or mismatched customer identifiers, incomplete bits of information, and other unruly aspects of handling large data sets. A DSR can also help eliminate duplicate data pieces or build a fuller birds-eye view of demand activity.

A DSR can be tied into supply chain processes and point-of-sale systems to provide full-cycle transparency. In a lot of senses, easy data access and user-friendly data handling systems are critical to business advancement, and more third-party vendors are becoming experts in creating DSRs and other gears for companies that need to optimize their business processes, using the data that constitute valuable business intelligence.

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Margaret Rouse
Technology Specialist
Margaret Rouse
Technology Specialist

Margaret is an award-winning writer and educator known for her ability to explain complex technical topics to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles in the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret’s idea of ​​a fun day is to help IT and business professionals to learn to speak each other’s highly specialized languages.