By William A. Giovinazzo, Visit Amazon's W. A. Giovinazzo Page, search results, Learn about Author Central, W. A. Giovinazzo,
Hyperlink company intelligence to the net! applied sciences, integration, and purposes. * Internet-enabled company intelligence: from making plans to learn * In-depth insurance of integration and key allowing applied sciences, together with Java and XML * complex research and profiling: comprehend buyers larger, and reply quicker * Clickstrean research: figuring out how buyers use your website * Linking information warehouses to CRM and different enterprise/value chain structures
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The value chain extends from the customer all the way back through retailers, distributors, manufacturers, and suppliers. The entire length of the value chain reaches from the customer to the actual supplier of raw materials. As we stated earlier, while the B2C aspects of the Internet have certainly captured the imagination of most industry watchers, the real action is occurring in the B2B space. 5 trillion in the United States by the year 2004, while more than $600 billion of that market will pass through B2B exchanges.
This is, of course, a major impediment to delivering a system as quickly as possible. Putting aside the "people" issues, one can see tremendous technical challenges to the single enterprisewide data warehouse. Even if we achieve consensus among the user community and we succeed in understanding all the metadata within our organization, we are still faced with the challenge of extracting that data and putting it into a single data repository. Once that is completed, imagine the size of such a system!
3 shows the difference in data orientation. This difference has far-reaching effects on the entire system. 3. Data orientation. Part 1: The Solution 41 42 Part 1: The Solution The transaction-oriented system structures data in a way that optimizes the processing of transactions. These systems typically deal with many users accessing a few records at a time. For reasons too numerous to discuss here, minimizing record and table size improves overall system performance. System architects normalize transaction databases to structure the database in an optimal way.