Retail - Industry Edge - Vol. 10

Industry Edge: Retail Edition, Issue 010

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Page 10 of 47

Retail Edition 11. Information and analytics hub transactional data stores. While those traditional systems are and will remain important, retail organizations are working to manage data flows that are growing in speed, volume, and complexity. but thus far the efforts to do so have been fragmented and less than comprehensive. Retailers must handle information from familiar sources such as point of sale and enterprise resource planning systems. Those traditional sources are now augmented by information flowing from customer sentiment research, social media sites, customer service interactions, and proliferating digital marketing channels. Handling unstructured data presents unique difficulties. Previous-generation centralized enterprise data warehouses are not well suited to the mining of unstructured data. Instead, unstructured data should be housed in federated information locations, then harmonized and assimilated on the fly���after which it can be mined to produce insights and actionable intelligence in a retail context. Those latter sources typically contain large and growing volumes of unstructured data, often in the form of chat, voice, and video files, and other non-standard forms. Research suggests that as much as 85% of information available to a typical organization is unstructured data. Retailers certainly want to access and understand this growing store of unstructured information, The now-emerging information and analytics hub model was developed specifically to meet those next-generation data management and analysis requirements. A modern information and analytics hub consists of separate tiers, which manage data, business intelligence, and delivery, and elements to coordinate business rules and metadata.

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