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Data Mining and Examples in Marketing

Data Mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. In Marketing, it is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs.

Practical Examples of Data Mining in Marketing

There are many examples of data mining which used in marketing, we will explain it briefly in this article.

CLUSTER ANALYSIS used to identify single target groups it enables identifying a given user group according to common features within a database. These features can include age, geographic location, education level and so on. The variable combinations are endless and make cluster analysis more or less selective according to the search requirements.

CLASSIFICATION ANALYSIS used to identify spams and more besides. it is the process of assigning columns into meaningful categories that can be used to organize and focus subsequent analysis work. it used the data mining technique that enables recognizing the patterns inside a database.it is an effective solution to improve your marketing strategy performance, to delete any superfluous information and to create improved sub-archives.

REGRESSION ANALYSIS used to make marketing forecasts to be able to tell the future is the dream of any marketing professional. it is a powerful statistical method that allows you to examine the relationship between two or more variables of interest. While there are many types of regression analysis, at their core they all examine the influence of one or more independent variables on a dependent variable.

ANOMALY DETECTION  used to recognize any abnormalities. it is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. it used to eliminate any database inconsistencies or anomalies at the source.

INTRUSION DETECTION is a device or software application that monitors a network or systems for malicious activity or policy violations. any malicious activity or violation is typically reported either to an administrator or collected centrally using a security information and event management system.it is sufficient to search for the intruders, a data mining technique that decontaminates the database and guarantees greater security for the entire system.

ASSOCIATION RULE LEARNING used to discover links between data. it is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using some measures of interestingness.

DECISION TREES  is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements.  it may be confusing having to handle a decision tree, but if we have the right computer tool that organizes the tree and submits definitive choices complete with costs/benefits, then it is a different story and the tree becomes a valuable tool for Project Risk Management. 

NEURAL NETWORKS used to automate learning and to complement clustering and decision trees is the neural network concept. It is one of the latest data mining applications whereby the means you use for marketing operations. the computer managing your database learns to identify a certain pattern containing elements with precise relationships with each other.

INDUCTION RULE is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a full scientific model of the data, or merely represent local patterns in the data. If a given circumstance occurs, then another and another again, we have this result. That is basically how the induction rule works.

DATA WAREHOUSING  is a system used for reporting and data analysis and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources. To choose software such as Egon for your data warehousing means simplifying your database, extracting the most interesting data about your customers, simplifying the creation of detailed reports and much more besides. 

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