Data Mining Overview
In this article, we get an overview of data mining and understand its evolution. There are some fundamental question about data mining that every beginner wants to know. Therefore, we try to answer those questions as accurately as possible.
As we learn more, you will find that the data mining industry is growing into a new areas rapidly since there has been some new development in database systems industry.
What is the motivation behind Data Mining?
The business in older times did not accumulate much data. However, with the development of digital systems many new businesses are spread across many countries and customer all over the world. These new businesses are doing huge number of transactions year after year. There is a requirement of understanding the customer behavior, products and other statistical information from the historical data.
The database industry and information system technology is also growing at rapid pace and continuously evolving. Therefore, data mining is a result of this natural evolution and assist business to analyze data and get meaningful information to take important decisions.
Evolution of Data Mining
Let us understand how database system industry evolved into data mining industry.
OLTP vs OLAP
The businesses have two types of data repository. One is to manage day-to-day management of transaction from an OLTP (Online Transaction Processing) application.
When you book a ticket online, or query for availability of tickets is called a simple database transaction. The data is either retrieved from a RDBMS or stored to the RDBMS if the transaction follow ACID properties.
Withdrawing money from an ATM machine is another example of OLTP system. The user can see the available balance by querying the database and withdraw money.
The OLAP ( Online Analytical Processing ) system is one that provides a multi-dimensional analysis of the data from different data repositories and databases. One of these repositories is Data Warehouse.
What is Data Mining ?
Earlier we told you that data is growing at an exponential rate and this data contains rich information which we cannot use.
The data mining technology change this information into knowledge. Therefore, Data mining refers to extracting or ‘mining’ knowledge from large amount of data.
Some other names given to data mining is
- Knowledge mining from data
- Data or Pattern Analysis
- Knowledge Extraction
- Data Archeology
- Data Dredging
- KDD or Knowledge discovery from data
Data Mining Introduction
In this document, you will find articles introducing you to data mining and its main components, structures, and overall process of data mining.
- Data Mining Overview
- What Are The Steps In Data Mining?
- Data Mining Architecture And Its Components
- Kind Of Data In Data Mining
- Kind Of Patterns In Data Mining
Data Mining Notes – Concepts, Examples, and Exam-Ready Revision
Data Mining are a core subject in Computer Science and Information Technology (IT) curricula, as well as in competitive examinations such as GATE, UGC NET, and university semester exams.
On this page, you will find structured resources to learn data mining concepts, along with clear explanations, examples and exam-ready revision notes.
What Will You Learn
On this page you will find:
- Core Data Mining concepts explained clearly and systematically
- Exam-oriented explanations supported with relevant examples
- MCQ-based practice posts to test your understanding
- Detailed articles along with exam-ready revision PDFs
This Page is for:
- Computer science and IT students
- GATE and other competitive exam aspirants
- University exam preparation
- Self learners who want to revise data structures knowledge.
Topic Sections
Find Data Structures topics here.
(1) Introduction to Data Mining
- Data Mining Overview.
- What are the steps in data mining.
- Data mining architecture and its components.
- Kind of data in data mining.
- Kind of patterns in data mining.