By Rob Mattison
A telecommunications-specific advisor to facts warehousing and mining, this paintings deals step by step instructions for designing and supplying facts warehousing and mining purposes, utilizing a couple of case experiences and real-world examples.
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Extra info for Data Warehousing and Data Mining for Telecommunications (Artech House Computer Science Library)
Merging systems, while effective in solving some problems, actually creates several more along the way. 2 The warehouse alternative It is at this point that we can begin to realize the real power and flexibility that warehouses have to offer. Warehouses make it possible for us to beat the information systems at their own game. With the warehousing option available to us, we no longer have to try to merge everything into one huge, megalithic system. , sales) or interdisciplinary ones. 3 A third alternative There is a third way to view the construction of warehouses, and it is actually the best and most common way to look at them.
The company must execute the transaction and then keep track of it in order to monitor network performance, issue bills, and perform network planning and optimization exercises. In an environment with so much raw data to deal with, the data warehousing and data mining paradigms make a lot of sense. 2 Analysis dependency Telecommunications firms are incredibly dependent on their ability to wade through tons of raw data and make intelligent decisions based upon what they find. As opposed to the traditional manufacturing firm, which has a lot of physical inventory to track and well-defined procedures to measure how well things are going, the telecommunications firm has no tangible goods to track.
Query and reporting tools—These products represent the latest generation of ad hoc access and reporting tools. These tools have been evolving greatly since the early days of Focus, QMF, and Oracle*Forms. Today’s query and reporting tools make it possible for people to ask for business information in business terms with a minimum of structured query language (SQL) and other programming language requirements. 3. Statistical analysis tools—These products represent the latest generation of the traditional mainline statistical report tools like SPSS and SAS.