By Alan R. Simon
You log on to shop for a digicam. quickly, you know you could have received a costlier digital camera than meant, besides additional batteries, charger, and pictures software-all on the prompting of the retailer.Happy along with your purchases? The store definitely is, and when you are too, you either may be stated to be the beneficiaries of "customer intimacy" completed throughout the transformation of knowledge amassed in this stopover at or kept from prior visits into genuine enterprise intelligence that may be exercised in actual time.Data Warehousing and company Intelligence for e-Commerce is a realistic exploration of the technological recommendations by which conventional information warehousing is delivered to endure in this and different much less modest e-commerce purposes, reminiscent of these at paintings in B2B, G2C, B2G, and B2E versions. The authors learn the center applied sciences and advertisement items in use at the present time, supplying a nuts-and-bolts knowing of ways you could set up purchaser and product info in ways in which meet the original requisites of the net marketplace-particularly while you are a part of a brick-and-mortar corporation with particular on-line aspirations. In so doing, they construct a strong case for funding in and competitive improvement of those techniques, that are more likely to separate winners from losers as e-commerce grows and matures. * comprises the most recent from winning facts warehousing specialists whose paintings has inspired the field's new concentrate on e-commerce.* provides details that's written for either specialists and practitioners in businesses of all sizes.* Emphasizes the distinctive wishes and possibilities of conventional brick-and-mortar companies which are going surfing or partaking in B2B provide chains or e-marketplaces.* Explains how long-standing assumptions approximately information warehousing must be rethought in gentle of rising enterprise versions that depend upon client intimacy.* presents suggestion on protecting facts caliber and integrity in environments marked by way of broad client self-input.* Advocates cautious making plans that would support either previous economic climate and new economic system businesses improve long-lived and profitable e-commerce strategies.* makes a speciality of info warehousing for rising e-commerce components reminiscent of e-government and B2E environments.
Read Online or Download Data Warehousing And Business Intelligence For e-Commerce (The Morgan Kaufmann Series in Data Management Systems) (The Morgan Kaufmann Series in Data Management Systems) PDF
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Additional info for Data Warehousing And Business Intelligence For e-Commerce (The Morgan Kaufmann Series in Data Management Systems) (The Morgan Kaufmann Series in Data Management Systems)
Example text
Therefore, implementing the models and architectures we’ll discuss throughout this book must be done as part of an overall end-to-end business strategy that encompasses both ecommerce and traditional channels and the necessary touch points throughout those respective sets of processes. Challenges There are demonstrable and self-evident business advantages to making data warehousing and business intelligence capabilities an integral part of an organization’s ecommerce efforts. However, it needs to be noted that there are three primary challenges in doing so, as will be discussed in this section: • “Discipline-centric” views among corporate strategists, consultants and systems integrators, and product vendors • “Dot-com” spin-offs as separate companies • The need to deliver products and solutions in “Internet time” Discipline-Centric Views Simply stated, there exists an artificial, unnatural, and unhealthy demarcation between the discipline of data warehousing and that of e-commerce.
Note that the evolution to CRM data marts typically was problematic, for several reasons. , OLAP functionality) applied against the CRM data mart. A more significant problem, though, was that many larger organizations typically found themselves by the mid-1990s with multiple call center and SFA systems. 4. 3 Phase 3: creating functionality-specific data marts for CRM support. forward-looking (some would say “courageous,” others might use the phrase “foolishly optimistic”) organizations was to evolve from their hodgepodge of CRM data marts to a single integrated customer data warehouse.
OLAP functionality) applied against the CRM data mart. A more significant problem, though, was that many larger organizations typically found themselves by the mid-1990s with multiple call center and SFA systems. 4. 3 Phase 3: creating functionality-specific data marts for CRM support. forward-looking (some would say “courageous,” others might use the phrase “foolishly optimistic”) organizations was to evolve from their hodgepodge of CRM data marts to a single integrated customer data warehouse.