Data Mining

n the post in our forum CRISP-DM to Spanish Translation Daniel Alejandro attached a document with a Castilian translation of the CRISP-DM methodology for developing data mining models.

In electronic publishing MCData.ti can be found a fairly complete classification of different tools related to business intelligence and data management. 
This is the description that makes the tools of Data Mining

In the article Data Mining: torturing the data until they confess Luis Carlos Molina provides a very illuminating on data mining, including examples of interesting applications of it.

Article including the abstract and index, drawn from the same publication:

Summary: The title of this article is an informal explanation of the activity that makes a technology called data mining (data mining). The purpose of this technology is to discover hidden knowledge from large volumes of data. Over the past decade, due to large computational advances, has been incorporated to the organizations to become an essential support when making decisions. Organizations such as corporations, professional sports clubs, universities and governments, among others, make use of this technology as an aid in making their decisions. Some of these examples will be cited in this paper.

CONTENTS
1. Introduction
2. Data mining: concepts and history
3. Applications
    3.1. In government
    3.2. In the
    3.3. In college
    3.4. In space research
    3.5. In sports clubs
4. Extensions of data mining
    4.1. Web mining

• The Data Warehouse is implemented on a system provided database manager, and loads of data that are made on it from different backgrounds can use ETL tools, which allow to link the database with different origins, define transformations to be done for the integration of data, and schedule or automate regular loads. 
• For operations using different tools, which can be classified according to the profile of the person who uses them.
  • The classic reporting tools are for users of different departments that need to operate in their daily work specific information.