Data Mining

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Contributors

Bjorn Burscher, NN

The word "Mining" refers to the extraction of valuable things like minerals from the earth. However, data mining is the process by which we can extract interesting patterns and knowledge from huge amounts of data. The data mining is a relatively new field of study and research and has generated huge interests among business communities. It is a an important part of business intelligence which deals with how an organization uses, analyzes, manages and stores data it collects from various sources to make better decisions.

In the popular article, "IT Does Not Matter" Nicholas Carr argued that the use of IT is nowadays so widespread that any particular organization does not have any strategic advantage over the others due to the use of IT[1]. So IT has lost its strategic importance. But data mining is one of most important concept of IT that proves him wrong. It reflects that an organization can create strategic advantages over its competitors by making use of data mining to get to important insights from the the data it collects. The way an organization collects data and analyzes it is not same for any organizations. So an organization can easily gain competitive values over others using data mining.


Data Mining: A Definition

Data Mining is knowledge discovery in databases. It stands for the extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from data in large databases.

Data Mining.png

Alternative names for data mining are: Knowledge discovery(mining) in databases (KDD), knowledge extraction, data/pattern analysis, data archeology, business intelligence, etc.

Data mining is a fairly new concept which was emerged in the late 1980s. But it soon attracted huge interests for research works and flourishes with many new and remarkable techniques being discovered throughout the 1990s. Data Mining has evolved from a number of different disciplines like statistics, machine learning, artificial intelligence, database technologies and so on.


Data Mining vs. Data Warehousing

The concept of data mining is closely related to the concept of data warehousing. Data Mining provides the Enterprise with intelligence and Data Warehousing provides the Enterprise with a memory.

Data warehousing is the process that is used to integrate and combine data from multiple sources and format into a single unified schema. So it provides the enterprise with a storage mechanism for its huge amount of data. On the other hand, Data mining is the process of extracting interesting patterns and knowledge from huge amount of data. So we can apply data mining techniques on the data warehouse of an enterprise to discover useful patterns.

References

  1. Carr, N. (2003). It does not matter. Harvard Business Review.

Contributors

Bjorn Burscher, NN