Changing the structure of a very large table doesn't need to require a maintenance window.
Hierarchical structures have an inherent ability for significant data value increases beyond the data collected. This will be shown to exist in hierarchical structures and even more powerfully in their natural hierarchical processing capabilities. These will demonstrate flexible and efficient ways to increase data value automatically and will be discussed in this article. SQL will be used to perform a wide range of hierarchical processing operations that easily demonstrate these increasing data value capabilities.
The capability of extending the limits of combining multiple node hierarchical structures has not been fully explored. Michael M. David presents a solution to advanced structure combining that is simple to use, generic and freely extends the way hierarchical structures can be semantically combined to produce advanced new hierarchical data structure mashups that dynamically increase the value of the data.
Data modeling is based on the precept of knowing your data and knowing how the data is interrelated with other data. Everyone knows their data – right? If so, then why do we have so many problems building systems that do what the users want?