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Table of contents
1.
Introduction
2.
Data Mining
2.1.
Datasets on which Data Mining can be performed
2.1.1.
Relational Databases:
2.1.2.
Data Warehouses:
2.1.3.
Object-Relational Databases:
2.1.4.
Transactional Databases:
2.2.
Pros of Data Mining
2.3.
Cons of Data Mining
3.
Artificial Intelligence
3.1.
Types of Artificial Intelligence
3.1.1.
Weak AI
3.1.2.
Strong AI
3.2.
Applications of Artificial Intelligence
3.3.
Pros of Artificial Intelligence
3.4.
Cons of Artificial Intelligence
4.
Difference between Data Mining and Artificial Intelligence
5.
Frequently Asked Questions
5.1.
What is Data Mining?
5.2.
What are the types of data mining?
5.3.
What is Artificial Intelligence?
5.4.
What are the types of artificial intelligence?
5.5.
What are the pros of data mining?
6.
Conclusion
Last Updated: Mar 27, 2024
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Data Mining vs AI

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Introduction

Both Data Mining and Artificial Intelligence are areas inspired by each other, yet they have different ends. Data mining basically uses the techniques developed by machine learning to predict the outcomes. Whereas artificial intelligence is just a code or algorithm that enables a machine to demonstrate human behavior.

Data Mining vs AI

In the article “data mining vs ai”, we will first be going to discuss what are data mining and artificial intelligence with their types, pros, and cons. Then we will discuss the difference between data mining and artificial intelligence.

Data Mining

In the article “data mining vs ai”, first we will discuss what is data mining. Data Mining consists of some techniques and tools which are used by scientists to find out the properties of datasets. Data mining uses machine learning to predict the outcomes. Basically, data mining extracts new and possibly information from large sets of data and transforms it into something useful for future use.

For example, If there are three different products of Amazon which are claimed to be bought by the customers frequently together. So here, data mining is used to find this insightful information, and now these products can be clubbed to make it a set so that more customers buy these products.

Datasets on which Data Mining can be performed

Here are the following types of data on which data mining can be performed:

Relational Databases:

These are the databases which is a collection of data sets organized by tables, columns, and records.

Data Warehouses:

It is a technology that basically collects data from different sources within the organisation to provide meaningful business insights.

Object-Relational Databases:

It is a combination of relational and object-oriented database models which supports classes, objects, inheritance, etc.

Transactional Databases:

Transactional Database is a database management system (DBMS) that has a functionality to undo a database transaction. But now, most relational databases have the capability to undo a database transaction.

Pros of Data Mining

  • Data mining helps in the decision-making in an organisation.
     
  • Data mining also helps organisations to obtain knowledge-based data.
     
  • The process of data mining is cost-effective.
     
  • The insight information that is extracted from the data sets can be very helpful in terms of business tactics.
     
  • The process of data mining is very quick and makes it easy for the users to analyse the amount of data in a short period of time.

Cons of Data Mining

  • Most data mining applications are not easy to operate that need advanced training to work on.
     
  • The selection of data mining tools is a very challenging task, especially for beginners.
     
  • The data mining techniques are not precise, which may lead to severe consequences in some conditions.
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Artificial Intelligence

In the article “data mining vs ai”, first we will discuss what artificial intelligence is. Artificial Intelligence is just a code or algorithm that enables a machine to demonstrate human behaviour. AI systems are primarily used for finding expert systems, natural language processing, speech recognition, and machine vision.

The field of artificial intelligence is one of the fastest growing and going to be one of the vast fields in the future.

Types of Artificial Intelligence

Artificial Intelligence is categorized into mainly two types, as follows

Weak AI

Weak AI, also known as Narrow AI, and Artificial Narrow Intelligence (ANI). It is a type of AI that solves a specific task. For example, if there is an AI system that can beat anyone in the game of chess, then that system can be called a weak AI because it serves only one function but do it efficiently.

Strong AI

Strong AI is created to demonstrate human abilities, and which is more difficult to create than weak AI. Strong AI basically works on the application that works on the experience of learning and reasoning.

Applications of Artificial Intelligence

There are various practical applications of artificial intelligence, some of which are as follows:

  • AI helps in fraud detection and financial forecasting in the domain of finance.
     
  • AI is also used in the domain of security as facial recognition and cybersecurity threat analysis can be achieved by AI.
     
  • In marketing industries, AI is also used in targeted advertising and sentiment analysis.
     
  • In the industry of transformation, AI is used in autonomous vehicles and traffic prediction.

Pros of Artificial Intelligence

  • AI systems can automate many jobs that can reduce human efforts.
     
  • AI systems can increase the accuracy and efficiency of the task drastically.
     
  • There is a vast community using AI that can assist anyone who is learning artificial intelligence.
     
  • These systems have high speed and can deal with large datasets.

Cons of Artificial Intelligence

  • The AI systems are vulnerable to hacking and security threats because these systems can contain personal information or data.
     
  • The AI systems have the potential to automate many jobs, which can result in replacing jobs which may increase the unemployment rate.
     
  • AI systems can be difficult to understand, interpret, and implement.

Difference between Data Mining and Artificial Intelligence

In the article “data mining vs ai”, now we will discuss the important part, the difference between data mining and artificial intelligence:

Basis

Data Mining

Artificial Intelligence

Definition Data Mining consists of some techniques and tools which are used by scientists to find out the properties of datasets. Artificial Intelligence is just a code or algorithm that enables a machine to demonstrate human behavior.
Types There are different types of data on which data mining can be performed are Relational Databases, Data Warehouses, Object-Relational Databases, and Transactional Database. Artificial Intelligence is categorized into mainly two types, as follows: Weak AI and Strong AI.
Relation to Machine Learning It is a basket of techniques and tools implemented by machine learning. Machine Learning comes under Artificial Intelligence, which is nothing but algorithms (or pieces of code).
Purpose To find out the properties of datasets and the insightful information which can be used by organisations. To automate the process or a specific task which reduces human effort.
Accuracy The accuracy of data mining depends on how data is collected and how machine learning produces the results. AI systems can increase the accuracy and efficiency of the task drastically.

 
Applications Data mining can be used in identifying sales patterns or trends. Future Healthcare, Fraud Detection, CRM, Market Basket Analysis, and Financial Banking.

 

Frequently Asked Questions

What is Data Mining?

Data Mining consists of some techniques and tools which are used by scientists to find out the properties of datasets and produce insightful information which can be used by organisations.

What are the types of data mining?

Here are the following types of data on which data mining can be performed are Relational Databases, Data Warehouses, Object-Relational Databases, and Transactional databases, etc.

What is Artificial Intelligence?

Artificial Intelligence is just a code or algorithm that enables a machine to demonstrate human behaviour. Artificial Intelligence systems automates the task and reduces human efforts.

What are the types of artificial intelligence?

Artificial Intelligence is categorised into mainly two types, as follows Weak AI (also known as Narrow AI and Artificial Narrow Intelligence) and Strong AI. 

What are the pros of data mining?

Data mining helps in the decision-making in an organization and to obtain knowledge-based data. The process of data mining is cost-effective and is very quick, which makes it easy for users to analyze the amount of data in a short period of time.

Conclusion

Both Data Mining and Artificial Intelligence are areas inspired by each other, yet they have different ends. Data mining is used for producing insightful information that can be used by the organisation for identifying sales patterns or trends. On the other hand, Artificial Intelligence is just a subset of machine learning that is based on artificial neural networks (ANN). 

In the article “data mining vs ai”, we discussed what is data mining along with its types, pros, and cons, what is artificial intelligence with its types, pros, and cons, and the difference between data mining and artificial intelligence.

Here are more articles that are recommended to read:

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