| Data mining can be technically defined as the | | | | services and utilities. BI uses various technologies like |
| automated extraction of hidden information from | | | | data mining, scorecarding, data warehouses, text |
| large databases for predictive analysis. In other | | | | mining, decision support systems, executive |
| words, it is the retrieval of useful information from | | | | information systems, management information |
| large masses of data, which is also presented in an | | | | systems and geographic information systems for |
| analyzed form for specific decision-making. | | | | analyzing useful information for business decision |
| Data mining requires the use of mathematical | | | | making. |
| algorithms and statistical techniques integrated with | | | | Business intelligence is a broader arena of |
| software tools. The final product is an easy-to-use | | | | decision-making that uses data mining as one of the |
| software package that can be used even by | | | | tools. In fact, the use of data mining in BI makes the |
| non-mathematicians to effectively analyze the data | | | | data more relevant in application. There are several |
| they have. Data Mining is used in several applications | | | | kinds of data mining: text mining, web mining, social |
| like market research, consumer behavior, direct | | | | networks data mining, relational databases, pictorial |
| marketing, bioinformatics, genetics, text analysis, | | | | data mining, audio data mining and video data mining, |
| fraud detection, web site personalization, | | | | that are all used in business intelligence applications. |
| e-commerce, healthcare, customer relationship | | | | Some data mining tools used in BI are: decision trees, |
| management, financial services and | | | | information gain, probability, probability density |
| telecommunications. | | | | functions, Gaussians, maximum likelihood estimation, |
| Business intelligence data mining is used in market | | | | Gaussian Baves classification, cross-validation, neural |
| research, industry research, and for competitor | | | | networks, instance-based learning /case-based/ |
| analysis. It has applications in major industries like | | | | memory-based/non-parametric, regression algorithms, |
| direct marketing, e-commerce, customer relationship | | | | Bayesian networks, Gaussian mixture models, |
| management, healthcare, the oil and gas industry, | | | | K-means and hierarchical clustering, Markov models |
| scientific tests, genetics, telecommunications, financial | | | | and so on. |