InfoAdvisors-MDM-Neo4j-Graph

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Your Master Data Is a Graph: Are You Ready?In Figure 4 - Employee Roles, Activities, Skills, Degrees, Teams Graph, we can see that both nodes andrelationships have varied properties. This is our data model, just as we might draw it on a whiteboard.Figure 4 - Employee Roles, Activities, Skills, Degrees, Teams GraphGraphs in the Real WorldMany organizations are using graph databases to focus on the data relationships in their master data tobe more competitive.Retail Transformation at a Communications OrganizationAn information and communications that offers mobile, TV and digital services upgraded their customerexperiences by adopting Neo4j in the production of their retail offerings. Their previous retail processrequired sales associates to use multiple systems to sell a mobile handset, accessories, promotions andplans to a walk-in customer. Their technologies were optimized for maintaining their product data andnot for providing efficient customer service, nor for helping product management to design efficientproduct bundles. They attempted to build hard relationships between product and services items, butthen paid the cost of having to adjust and re-engineer those hard relationships when new propertiesneeded to be added. They realized they needed a more flexible, more responsive solution a constantlychanging items and promotions world.InfoAdvisors 6
Your Master Data Is a Graph: Are You Ready?Today they use Neo4j to allow buyers to pre-package groups of items so that sales associates can quicklyprovide bundles for customers. Leveraging the flexibility and the focus on product and promotionrelationships in Neo4j, they have been able to reduce the time required to put together product bundlesfrom one month to 10 days. In store, they can help customers choose the items they want and sell themother services or items to bundle well with those items. Using the many different types of datarelationships in their product and customer master data is key to improving customer service,completing orders and decreasing cost of sales, as well as substantially reducing queue times at theirphysical stores.This retailer hosts nearly one million nodes and millions of relationships between those nodes andcontinues to scale up as volume and number of users increases. They are already working on addingNeo4j to cable and digital TV services and products to bring the same competitive advantages to theirother lines of business.Leveraging Multi-vendor Product Combinations at PolyvorePolyvore allows shoppers to put together sets of clothing and products in a highly visual, interactiveformat. A shopper (a stylist in Polyvore terms) can pull products, their metadata and prices from anywebsite using a clipper tool, then enhance these sets with graphics, text and personal photos. The stylistcan then put together sets of sets, called collections, to build even more relationships among items.Polyvore users compose millions of these sets ayear, creating a wealth of buying intentions andinfluence for other shoppers. Today there aremillions of retail items (SKUs) in this database ofuser-generated content. Users build thesecollections of items based on their own fashiontastes and trends.Polyvore can ask questions about what items “gotogether” and infer from those answers otherproducts that may influence interests and sales ofadditional items. Users can also tag products withthe relevant characteristics of each product. Thesetags also become relationships for product data,further enhancing the rich dataset beingcrowdsourced.Brands can also participate in the Polyvorecommunity by clipping their items into the itemdatabase, then looking at trends and popularity, based on community sharing and “likes” of theirproducts in relationship to other products.InfoAdvisors 7
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