Data Mining
The amount of knowledge available in today's world is massive. The information technology specialist who's responsible to his or her organization for maximizing the capacity for practical usage of this knowledge, it is becoming increasingly difficult to have a total grasp of the problem. The purpose of this essay is to discuss the importance of implementing data warehousing and mining systems inside an organization. In order to do this, it is necessary to contrast the positive benefits of data mining and contrast those ideas with the negative connotations associated with the similar processes.
Data mining, according to Thearling (2009) is "the automated extraction of hidden predictive information from large databases. " Additionally, data mining is a proactive and aggressive tactic that can serve the overall business strategy when properly aligned. Statistical analysis is inherent within any type of data mining technique and is expressed in these terms. The reasons why data mining or data warehousing is important is because of the potential to simplify all types of processes within a complicated data field.
It is also important to understand the complex issues involved in gaining a total understanding of what is at stake. Greenfield (2005) examined the case for data warehousing and the case against data warehousing. There's several reasons why a company would want to implement these...
The use of databases as the system of record is a common step across all data mining definitions and is critically important in creating a standardized set of query commands and data models for use. To the extent a system of record in a data mining application is stable and scalable is the extent to which a data mining application will be able to deliver the critical relationship data,
The heuristics that are considered are probabilistic machine learning approaches. Such an approach is the 'Alignment Conditional Random Fields' that is designed for a scoring sequence for undirected graphical models. (Bilenko; Mooney, 2005) There are demands for this type of software and there is a vast area of information analysis where text mining is beginning to get important. One field is in the analysis of literature and research reviews. Literary
Data MiningToday, companies of all sizes and types are eager to learn as much about their customers and competitors as possible in order to gain and sustain a competitive advantage in an increasingly globalized marketplace. One strategy that has demonstrated utility for this purpose is data mining. The purpose of this paper is to provide a review of the relevant literature to determine the pros and cons of using data
Data Warehousing: A Strategic Weapon of an Organization. Within Chapter One, an introduction to the study will be provided. Initially, the overall aims of the research proposal will be discussed. This will be followed by a presentation of the overall objectives of the study will be delineated. After this, the significance of the research will be discussed, including a justification and rationale for the investigation. The aims of the study are to
Mining The process of extracting new information from existing information through the use of computer system is called Text Mining. Text mining retrieves data of available information and establishes the connection between the facts mentioned in that data. This is how, new information is developed. Since it is newly formed information, its validation is conducted through experimentation. The process of web search is often confused with that of text mining,
Growth Aided by Data Warehousing Adaptability of data warehousing to changes Using existing data effectively can lead to growth Uses of data warehouses for Public Service Getting investment through data warehouse Using Data Warehouse for Business Information Ongoing changes in Data Warehousing The Origin of Data Warehousing and its current importance Relationship between new operating system and data warehousing Developing Organizations through Data Warehousing Telephone and Data Warehousing Choose your own partner Data Warehousing for Societal Causes Updating inaccessible data Data warehousing for investors Usefulness
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