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deta123
Newbie Biz-Whizer
Joined: Dec 01, 2011
Posts: 1
Status: Offline
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 Posted:
Jan 04, 2012 - 02:50 AM |
 
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We always start with a service plan for your specific data entry projects and Internet Marketing Services
form logical processing requirements. Our approach to data entry is unique and the technologies we use enable us to deliver the highest levels of data quality, accuracy, and fast turnaround time.
Data mining is an integral part of data analysis which contains a series of activities that goes from the 'meaning' of the ideas, to the 'analysis' of the data and up to the 'interpretation' and 'evaluation' of the outcome. The different stages of the technique are as follows:
Objectives for Analysis: It is sometimes very difficult to statistically define the phenomenon we wish to analyze. In fact, the business objectives are often clear, but the same can be difficult to formalize. A clear understanding of the crisis and the goals is very important setup the analysis correctly. This is undoubtedly, one of the most complex parts of the process, since it establishes the techniques to be engaged and as such, the objectives must be crystal clear and there should not be any doubt or ambiguity.
Collection, grouping and pre-processing of the data: Once the objectives of the analysis are set and defined, we need to gather or choose the data needed for the study. At first, it is essential to recognize the data sources. Usually data are collected from the internal sources as the same are economical and more dependable and moreover these data also has the benefit of being the outcome of the experiences and procedures of the business itself.
Investigative analysis of the data and their conversion: This stage includes a preliminary examination of the information available. It involves a preliminary assessment of the significance of the gathered data. An exploratory and / or investigative analysis can highlight the irregular data. An exploratory analysis is important because it lets the analyst choose the most suitable statistical method for the subsequent stage of the analysis.
Choosing statistical methods: There are multiple statistical methods that can be put into use for the purpose of analysis, so it is very essential to categorize the existing methods. The choice statistical method is case specific and depends on the problem and also upon the type of information available.
Data analysis on the basis of chosen methods: Once the statistical method is chosen, the same must be translated into proper algorithms for working out the results. Ranges of specialized and non-specialized software are widely available for data mining and as such it is not always required to develop ad hoc computation algorithms for the most 'standard' purpose. However, it is essential that the people managing the data mining method well aware and have a good knowledge and understanding of the various methods of data analysis and also the different software solutions available for the same, so that they may adapt the same in times of need of the company and can flawlessly interpret the results.
Assessment and contrast of the techniques used and selection of the final model for analysis: It is of utmost necessity to choose the best 'model' from the variety of statistical methods accessible. The selection of the model should be based in contrast with the results obtained. When assessing the performance of a specific statistical method and / or type, all other dependent and / or relevant criterions should also be considered. The other criterions may be the constraints on the company both in terms of time and resources or it may be in terms of quality and the accessibility of data.
Elucidation of the selected statistical model and its employment in the decision making process: The scope of data mining is not limited to data analysis rather it is also includes the integration of the results so as to facilitate the decision making process of the company. Business awareness, the pulling out of rules and their use in the decision process allows us to proceed from the diagnostic phase to the phase of decision making. Once the model is finalized and tested with an information set, the categorization rule can be generalized. But the inclusion of the data mining process in the business should not be done in haste; rather the same should always be done slowly, setting out sensible and logical aims. The final aim of data mining is to be an integral supporting part of the company's decision making process.
http://data-entry.outsourcing-services-india.com/ |
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jasonbrien
Senior Biz-Whizer
Joined: Oct 28, 2011
Posts: 83
Status: Offline
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Jan 05, 2012 - 01:25 AM |
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billmat
Biz-Whizer
Joined: Jan 05, 2012
Posts: 16
Status: Offline
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Jan 05, 2012 - 11:17 PM |
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andy25i
Senior Biz-Whizer
Joined: Sep 28, 2011
Posts: 87
Status: Offline
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Jan 06, 2012 - 05:29 AM |
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Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. |
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princemkhan
Biz-Whizer
Joined: Nov 18, 2011
Posts: 27
Status: Offline
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Jan 16, 2012 - 12:32 AM |
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A long description about data mining you provides hare. thanks for sharing this. |
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Chimney Balloon |
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jasonbrien
Senior Biz-Whizer
Joined: Oct 28, 2011
Posts: 83
Status: Offline
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Feb 01, 2012 - 07:40 AM |
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Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Data mining is all about the detailed information about data.Simply it is the process of collecting information about all the resources related to the data. |
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Decorative Cushions | Tapestry Wall Hangings |
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johanson21
Biz-Whizer
Joined: Feb 03, 2012
Posts: 20
Status: Offline
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Feb 03, 2012 - 03:45 AM |
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Generally, data mining also known as knowledge discovery, is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Data mining is all about the detailed information about data.Simply it is the process of collecting information about all the resources related to the data. |
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Ber Certs Dublin |
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spider123
Senior Biz-Whizer
Joined: Feb 08, 2012
Posts: 56
Status: Offline
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Feb 14, 2012 - 06:11 AM |
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Data mining a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems.The goal of data mining is to extract knowledge from a data set in a human-understandable structure and involves database and data management, data preprocessing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of found structure, visualization and online updating. |
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jackdcosta56
Newbie Biz-Whizer
Joined: Feb 13, 2012
Posts: 2
Status: Offline
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Feb 14, 2012 - 11:56 PM |
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alen12345
Advanced Biz-Whizer
Joined: Oct 21, 2011
Posts: 141
Status: Offline
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| Posted:
Feb 20, 2012 - 12:42 PM |
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