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Table of contents
1.
Introduction
2.
Data Mining
3.
Data Analysis
4.
Comparison Chart
5.
Frequently Asked Questions
6.
Conclusion
Last Updated: Mar 27, 2024
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Data Mining Vs Data Analytics

Author Nagendra
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Ashwin Goyal
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Introduction

In today's world of new technology, data plays a critical role in improving the nature of products and their reach to customers. Information is critical in assisting with this factor. Companies have begun to rely on assessments advanced by their internal processes, business operations, and customers to explore new chances for progress and success in the ever-changing international economy. Such insights present a huge, complex set of data that must be produced, maintained, examined, and manipulated. For any data-driven project, data mining and data analytics are critical components that must be done correctly for the project to succeed. As previously said, distinguishing between data mining and analytics can be challenging due to their close proximity. Before we can compare, we must first have a thorough understanding of the two fields.

Data Mining

The practice of collecting usable data from a bigger quantity of raw data is known as data mining. It refers to a strategy for finding and discovering hidden patterns and data throughout a large dataset that is both efficient and continuous. It's also used to create machine learning models, which are then used in artificial intelligence. It segmented the data and calculated the probability of future events using advanced mathematical methods. Data mining is also known as data knowledge discovery. It is also called Knowledge Discovery in Databases.

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Data Analysis

Data analysis is extracting, cleaning, transforming, modelling, and visualising data to extract essential and useful information that may be used to draw conclusions and make decisions. In statistical applications, exploratory data analysis, descriptive statistics, and confirmatory data analysis are the three types of data analysis. It has only lately entered the mainstream, but it has already shown to be a vital instrument in the arsenal of any major global actor. In most cases, a Data Analyst cannot be a single person. The job description comprises preparing raw data, cleansing, transforming, and modelling it, and finally presenting it in the form of chart/non-chart based visualisations. In business, data analysis is utilised to assist firms in making better business decisions.

Comparison Chart

The following table compares and contrasts Data Mining and Data Analysis:

Also see, Difference Between Analog and Digital Computer

Frequently Asked Questions

  1. What is Data Mining?
    Data Mining refers to a strategy for finding and discovering hidden patterns and data throughout a large dataset that is both efficient and continuous.
     
  2. What is Data Analysis? 
    Data analysis is extracting, cleaning, transforming, modelling, and visualising data to extract essential and useful information that may be used to draw conclusions and make decisions.
     
  3. Are visualisation tools included in data Mining?
    No, visualisation tools are not included in data mining. The Visualisation tools are used in data analytics.
     
  4. What are the three categories of Data Analysis?
    Data Analysis can be classified into three categories: exploratory data analysis, descriptive statistics, and confirmatory data analysis.

Conclusion

In this article, we have extensively discussed the comparison of Data mining and Data Analysis. The article explains the details of Data mining, Data Analysis, their applications in the real world, and a comparison between data mining and data analysis.
We hope that this blog has helped you enhance your knowledge regarding the difference between Data Mining and Data Analysis. You can also consider our Data Analytics Course to give your career an edge over others.
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