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Ad hoc analysis in IT is commonly defined as a technology or effort pointed toward a single use or a single question or purpose for a given scenario. The opposite of this is comprehensive analysis, which is broad based, multi-use and often based on aggregated data.
Examples of ad hoc analysis might include a software application that lets users enter specific analytical questions about business data. For instance, if the business has an extensive sales database and the user wants to find a unique sales outcome related to a particular scenario, he or she would build a single report that would run once and provide that unique result. Any further reports would be separately generated by subsequent efforts.
Although ad hoc analysis tools are inherently defined as single-use tools, experts point out that some types of ad hoc analysis can be run multiple times or can be useful on an ongoing basis.
Another way to understand ad hoc analysis is that it is a very different kind of analysis from the analysis philosophies that have driven such monumental IT changes in recent years. The idea of big data, or of enormous volumes of business intelligence information driven through cloud systems, faces the idea of getting comprehensive or top-level analysis that is sophisticated and continual, based on broad-based aggregation of data. Ad hoc analysis is different — it seeks a single result, not a comprehensive one. There are many ways to do ad hoc analysis, including using software applications, database queries or other technologies and techniques.