In this article, we'll look at the continuum between isolated data and shared data, and identify three distinct approaches for creating data architectures that fall at different places along the continuum.
Next, we'll explore some of the technical and business factors to consider when deciding which approach to use.
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June 2006 Frederick Chong, Gianpaolo Carraro, and Roger Wolter Microsoft Corporation Applies to: Application Architecture Software as a Service (Saa S) Summary: The second article in our series about designing multi-tenant applications identifies three distinct approaches for creating data architectures.
(25 printed pages) Many thanks to Paul Henry for his help with technical writing.
, or the lack thereof, is the number one factor blocking the adoption of software as a service (Saa S).
A case could be made that data is the most important asset of any business—data about products, customers, employees, suppliers, and more. Saa S applications provide customers with centralized, network-based access to data with less overhead than is possible when using a locally-installed application.
However, quite a number of tasks require actions not directly supported by the API.
Here the fact comes handy that EA is based on a database model which has proven to be very stable with respect to its structure.
The last major change was introduced with audit functionality which added a couple of new tables but left the structure of the existing tables untouched.
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