Home » Software Engineering

Data Mining – Introduction, Benefits, Disadvantages and Applications

In this tutorial, we are going to learn about the introduction, benefits, disadvantages and applications of data mining.
Submitted by Harshita Jain, on October 19, 2019

Introduction

In today's world, the amount of data is increasing exponentially whether it is biomedical data, security data or online shopping data, many industries preserve the data in order to analyse it, so that they can serve their customers more effectively through the information which they take out from large preserve data. This taking out or digging out information from huge data sets obtained from different sources and industries is known as Data Mining.

Knowledge Discovery

Knowledge discovery is the overall process of extracting knowledge from the huge data sets. It involves the following steps:

  • Data Cleaning – In Data Cleaning the noise and inconsistent data is removed.
  • Data Integration − multiple data sources are combined.
  • Data Selection − only the relevant data is selected from the database.
  • Data Transformation − data is consolidated into appropriate forms for mining by performing summary or aggregation operations.
  • Data Mining − this is an intelligent step in which various methods are applied to extract data patterns.
  • Pattern Evaluation − data patterns, which can be in different forms like trees, associations, clusters, etc. are evaluated.
  • Knowledge Presentation − this step finally provides knowledge.

Benefits of Data Mining

The below figure describes the various benefits of data mining.

benefits of data mining


Disadvantages of Data Mining

  • The concise information obtained by the companies, they can sell it to other companies for money like American Express has sold information about their customers credit card purchases to other company.
  • Data mining requires advance training and prior knowledge about the tools and softwares to work on.
  • Various data mining tools work in different manners due to different algorithms employed in their design. Therefore, the selection of the correct data mining tools is a very tough task.
  • Some times prediction can go wrong and can play havoc for the companies on taking any decision based on that prediction.

Applications of Data Mining

Applications Usage
Communications Data mining techniques are used in the communication sector to predict customer behavior to offer highly targeted and relevant campaigns.
Insurance Data mining helps insurance companies to price their products profitable and promote new offers to their new or existing customers.
Education Data mining benefits educators to access student data, predict achievement levels and find students or groups of students who need extra attention. For example, students who are weak in a science subject.
Manufacturing By using the help of Data Mining Manufacturers can predict wear and tear of production assets. They can anticipate maintenance which helps them reduce them to minimize downtime.
Banking Data mining helps the finance sector to get a view of market risks and manage regulatory compliance. It helps banks to identify probable defaulters to decide whether to issue credit cards, loans, etc.
Retail Data Mining techniques help retail malls and grocery stores identify and arrange most sellable items in the most attentive positions. It helps store owners to come up with the offer which encourages customers to increase their spending.
Service Providers Service providers like mobile phone and utility industries use Data Mining to predict the reasons when a customer leaves their company. They analyze billing details, customer service interactions, complaints made to the company to assign each customer a probability score and offer incentives.
E-Commerce E-commerce websites use Data Mining to offer cross-sells and up-sells through their websites. One of the most famous names is Amazon, which uses Data mining techniques to get more customers into their eCommerce store.





Comments and Discussions

Ad: Are you a blogger? Join our Blogging forum.




Languages: » C » C++ » C++ STL » Java » Data Structure » C#.Net » Android » Kotlin » SQL
Web Technologies: » PHP » Python » JavaScript » CSS » Ajax » Node.js » Web programming/HTML
Solved programs: » C » C++ » DS » Java » C#
Aptitude que. & ans.: » C » C++ » Java » DBMS
Interview que. & ans.: » C » Embedded C » Java » SEO » HR
CS Subjects: » CS Basics » O.S. » Networks » DBMS » Embedded Systems » Cloud Computing
» Machine learning » CS Organizations » Linux » DOS
More: » Articles » Puzzles » News/Updates


© https://www.includehelp.com some rights reserved.