This verification-based process stems from the intuition of the user to pose the questions and refine the analysis based on the results of potentially complex queries against a database. The effectiveness of this analysis depends on several factors, the most important of which are the following:
- Ability of the user to pose appropriate questions
- Capability of tools to return results quickly
- Overall reliability and accuracy of the data being analyzed.
Query and Reporting Tools
Some business analysis tools have been optimized to address some of these issues. Query and reporting tools, such as those used in data mart or warehouse applications, let users develop queries through point-and-click interfaces. Statistical analysis packages are used by many insurance or actuarial firms to explore relationships among a few variables and determine statistical significance against demographic sets. Multidimensional OLAP (Online Analytical Processing) tools enable fast response to user inquiries through their ability to compute hierarchies of variables along “dimensions” such as size, color or location.
Data mining, in contrast to these analytical tools, uses discovery-based approaches in which pattern matching and other algorithms are employed to determine the key relationships in the data. Data mining algorithms can look at numerous multi-dimensional data relationships concurrently, highlighting those that are dominant or exceptional.
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- Gas Chromatography Database
Chromatography. Atomic Emission Detector A brief description of the microwave-induced plasma emission detector for gas chromatography. Basic Liquid Chromatography
