Traditional Data Mining Applications Essay

Data mining software allows users to analyze large databases to solve business decision problems. Data mining is, in some ways, an extension of statistics, with a few

As stated above, data mining is often used to solve business decision problems, “it provides ways to quantitatively measure what business users should already know qualitatively” (Linoff, 2004). A growing number of industries are using data mining to become more competitive in their market by primarily focusing on the customers; increasing their customer relationships and increasing customer acquisition.

Usually the data mining analysis is done by grouping commonly co-occuring things (Associations), discovering time-ordered events (Sequences), anticipating future occurences (Predictions), identifying natural groupings of items (Clusters) and finally, by uncovering generalizations to help classify items (Classification). These different type of mining usually take a lot of time and a good understanding of the business and

With the increased and widespread use of technologies, interest in data mining has increased rapidly. Companies are now utilized data mining techniques to exam their database looking for trends, relationships, and outcomes to enhance their overall operations and discover new patterns that may allow them to better serve their customers. Data mining provides numerous benefits to businesses, government, society as well as individual persons. However, like many technologies, there are negative things that caused by data mining such as invasion of privacy right. This paper tries to explore the advantages as well as the disadvantages of data mining. In addition, the ethical and global issues regarding the use of data mining

In a world where computers are becoming as essential to daily life as the cars we drive or the telephones we use to communicate, it is difficult to find a person who doesn’t have some particular use for computers. Computers have become the information stores of the world. If you take a moment to think about all the kinds of information a person can and does hold on their computer it is staggering. I myself have all the passwords to my email and bank accounts, the history of every web page I’ve visited in the last 3 weeks, my credit card numbers, the complete history of all my banking transactions for the last three years stored on my computer. Additionally, think about all the

Both data mining and data analysis are a subset of Business Intelligence which also includes data management systems, data warehouses and Online analytic processing(OLAP). To manage the mountains of information, the data is put away in a warehouse of information accumulated from different sources, including corporate databases, compressed data from interior frameworks, and information from outer

Many other terms are being used to interpret data mining, such as knowledge mining from databases, knowledge extraction, data analysis, and data archaeology. Data mining is one of the provoking and significant areas of research. Data mining is implicit and non-trivial task of identifying the viable, novel, inherently efficient and perspicuous patterns of data. Figure 1 represents the data mining as part of KDD process. The hidden relationships and trends are not precisely distinct from reviewing the data. Data mining is a multi-level process involves extracting the data by retrieving and assembling them, data mining algorithms, evaluate the results and capture them. Data Mining is also revealed as necessary process where bright methods are used to extract the data patterns by passing through miscellaneous data mining

In today’s business world, information about the customer is a necessity for a businesses trying to maximize its profits. A new, and important, tool in gaining this knowledge is Data Mining. Data Mining is a set of automated procedures used to find previously unknown patterns and relationships in data. These patterns and relationships, once extracted, can be used to make valid predictions about the behavior of the customer.

This research paper is about the Comparative analysis of three data mining software’s selected based on four important criteria Performance, Functionality, Usability and Ancillary Tasks support. “Data Mining is a field of study that is gaining importance and is used to explore data in search of patterns or relationships between variables and is applied to new data used for predictions”. (Statistics – Textbook. (n.d.). Retrieved November 17, 2015). Selection of the appropriate data mining tools is critical to any research or business and this could impact the business in terms of money, resources and time. Data experts

Since higher education has blurred the lines with traditional businesses, it is important to have the tools to assist them with valuable data and information, in making decisions. Using of data and having the right data mining tools can insure the institute’s success, in many forms, such as, identifying market trends, precision marketing, new products, performance management, grants and funding management, student life cycle management and procurement to mention a few. To get a better grasp on these benefits it’s important to understand data warehouse, data mining and the associated benefits.

Data mining also called knowledge discovery in data, began in the early1980s, and has been fast growing in today’s various industries as an essential information technology. “Data mining is a step in the KDD process that consists of applying data analysis and discovery algorithms that, under acceptable computational efficiency limitations, produce a particular enumeration of patterns (or

In the year of 2001 when the use of data mining in marketing was a relatively new concept Shaw ,Subramaniam, Tan and Welge gave an insight about management of large database using data mining techniques. They brought the concept of identifying useful information from the large customer database by identifying hidden patterns. They integrated data mining and marketing knowledge management to help in managing marketing decisions.

In this paper we are trying to understand how specific company software can provide better information to users, improve the business process (sales), etc. by incorporating data mining and data warehouse concepts to their existing

Data mining consists of analysing huge sets of data and extracting relevant information and data patterns. Companies often have very large data sets that needs to be analysed for many different purposes. Initially this was a hard task to accomplish because of limitations in computing power. However, computer technology has accelerated so fast in recent past that analysing large volumes of data has become possible. Companies use these analysis results for

Data mining is an area of data processing in which extraction of useful patterns from pre-existing databases and transformation of extracted information into understandable form is done. Data mining employs various methods like clustering, classification, regression etc.[1] One such method is Association Rule Mining which discovers the dependencies between database variables. Frequent Pattern Mining is an area of data mining which works on this principle and generates