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Data Mining Tutorial

Home » Data Science » Data Science Tutorials » Data Mining Tutorial

Data Mining Basics

Introduction To Data Mining

What Is Data Mining?

Advantages of Data Mining

Types of Data Mining

Data Mining Algorithms

Data Mining Applications

Data Mining Architecture

Data Mining Methods

Data Mining Process

Association Rules in Data Mining

Data Mining Software

Data Mining Tool

Data Mining Techniques

Data Mining Concepts and Techniques

Data Mining Techniques for Successful Business

Orange Data Mining

Decision Tree in Data Mining

Types of Clustering

What is Clustering in Data Mining?

Hierarchical Clustering

How Text Mining Works

What is Text Mining?

Data Mining Interview Question

Models in Data Mining

Decision Tree in Data Mining

Data Mining Cluster Analysis

Text Data Mining

Data Mining Tutorial

Simply put Data mining is extracting meaningful insights from huge sets of data. It involves processes to extract information by identifying patterns, anomalies, trends, etc. which can be used by decision-makers to take important decisions. With the advent of technologies like Big Data and Data Science Businesses around the world have benefitted from data mining to achieve their business goals by identifying opportunities and making their organizations lean by cutting waste.

It involves Mathematical Algorithms to break down a complex set of data to gain meaningful insight like discovering patterns, forecasting trends, etc. This process is basically transforming raw data into useful insights or information. This process is called data Mining.

Need to learn Data Mining

As discussed, it is of utmost importance in today’s time for Businesses and Organizations across the globe to make use of their data which they generate every second and throughout various business processes. Learning Data Mining techniques is, therefore, is one of the most sought-after skills that organizations are looking for and because the area of study is relatively new there is a dearth of experts in this field. The importance of data mining is unmatched and almost all kinds of businesses from Retail to banking and from Defense to Agriculture.

Applications of Data Mining

  • In Healthcare it can with the help of Machine Learning and Artificial Intelligence be used to prescribe best practices, diagnose diseases, track patterns of symptoms and also provide first in some cases.
  • In Finance, it can be used by Banking and other institutions to customize solutions, lending decisions, customer profiling, fraud detection, etc.
  • In Manufacturing, it can help decision-makers to cut down on production time, idle inventory,
  • It can also be of great use in matters of Regulations and Compliances to various organizations like Taxation, Legal and Other Governmental commitments by reducing human intervention.
  • Data Mining in Education has also shown huge potential by getting insights from data generated by educational institutes to improve the learning behavior of students and the overall quality of education provided.

Example

One of the examples of Data Mining that we encounter daily in our lives is how Facebook has “targeted Ads” for its users. Facebook accumulates a lot of data in the form of likes, comments, photos, videos, chats, etc. It is one of the most data-rich companies along with Google and Amazon. By using Data mining tools and techniques it targets its users based on patterns and trends as discussed earlier with custom ads based on their individual tastes and preferences making Marketing more effective and efficient for Advertisers and Companies.

Prerequisites

Before considering taking on this course one needs to be well versed with certain topics like Structured Query Language, Schema and basic knowledge of Data Warehousing concepts.

Target Audience

Although it can be learned by anyone interested in understanding the concepts of Data mining for Academic or Career perspective, it is ideally suited for Computer Science graduates and people who are looking to advance their careers who are already actively involved in Data Mining and allied projects directly or indirectly.

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