Data Mining Solutions

"One of the greatest strengths of data mining is reflected in its wide range of methodologies that can be applied to a host of problem sets."

"How do you determine whether investment in a data mining system is justified? In some cases the math is fairly straightforward."

"The models you create will determine the types of results that can be discovered in your analysis."

"Depending on the type of data you have, you will use either a descriptive or a transactional model."

"Network representations allow the analyst to establish pathways, identify important substructures in the data set, and identify a framework for more advanced analyses."

"Any time that you are in a situation in which your metaknowledge status is "don't know," you are in a potential data mining space."

"The reactive analysis works well under circumstances in which something is already known about the data set and the analyst can generate hypotheses a priori."

"One of the first steps in a data mining engagement is to define a subset of data with which to begin your analysis."

"The long record format gives you access to all available types of information about entities of interest, but the price you pay for this functionality is that the process of building your model(s) may be a bit more complex."

"Visualization methods allow you to discover overall trends in your data set while also affording you an opportunity to discover smaller hidden patterns that can often be just as important within an application."

"When using visualization methodologies the analysis occurs through interactions with the displays themselves."

"Visual mining analyses include the presentation of results as a critical first step."

"Statistical methods may be used in the context of hypothesis testing in which we predict differences between groups before the analysis begins (a priori)."

"Neural networks are a type of computational methodology commonly used for pattern identification and classification."