There are important considerations to be made while determining the basic building blocks of a DATA MODEL. The design needs to be outcome-driven so that it supports the intermediate results effectively. Simply put, relying on set of stable inputs such as large datasets that get updated automatically on daily basis is the key to successful data mining. Here is a classic example explaining how some analytical tools can address business queries very efficiently:
DATA ACCESS
One of the most daunting task is to access the data that might be piped from multiple sources. Being able to connect to those records through appropriate engines and library references is the key to begin intricate data modeling. Many data scientists like to get this organized by following standard naming conventions and heavy usage of ordering sequence. It helps browse through data marts efficiently when there is a need to join multiple datasets to create complex views for deriving extensive quantitative measures.
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