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Difference between Data mining and Data Science?
Data mining and data science are the two most important concepts in information technology. Data mining is a process of determining useful information, trends, and patterns from large databases, so that these parameters can be used to solve several business problems. On the other hand, data science is the process of obtaining important insights from the unstructured and structured data by using different analysis tools. Basically, data science is one of the modern emerging fields of computer science and information technology for the study of largescale data analysis.
Read this article to learn more about Data Mining and Data Science and how they are different from each other.
What is Data Mining?
Data mining is a process of extracting useful information, patterns, and trends from raw data. It uses sophisticated numerical algorithms to split the data and compute the probability of future events. There are several types of services in data mining processes, including text mining, web mining, audio, and video mining, pictorial data mining, and social network data mining.
Data mining is done through simple or advanced software. Data mining is known as Knowledge Discovery in Data (KDD). Data mining can include the use of several types of software packages including analytics tools. It can be automated, or it can be largely labor-intensive, where individual workers send specific queries for information to an archive or database.
What is Data Science?
Data Science is an emerging area of computer science that targets information. It is an interdisciplinary area that uses a blend of devices, algorithms, and machine principles to extract usable data from both structured and unstructured records.
Data science is not only statistics or machine learning, it also uses data analysis and modeling to learn the complex world of data. Data scientists are the one responsible for this job and they can collect data from multiple sources, organize and analyze the data, and then connect the findings in a way that efficiently affects business decisions. The objective is to extract useful insights from information.
Difference between Data Mining and Data Science
The following are the important differences between data mining and data science −
S.No. |
Data Mining |
Data Science |
|---|---|---|
1. |
Data mining is a phase of extracting useful data, patterns, and trends from large databases. |
Data science defines the process of obtaining valuable insights from structured and unstructured records by using several tools and methods. |
2. |
The main objective of data mining is to discover properties of existing information that were previously unknown and to find statistical rules or patterns from those data to solve complex computing problems. |
The main objective of data science is to use certain specialized computational methods to find meaningful and useful data within a dataset to create important decisions. |
3. |
In Data mining, the identified trends and patterns are used by organizations to formulate operations, marketing, and financial strategies to fuel business growth. |
Data science is scientific research that paves the way for a project program- or portfolio-centric analysis. |
4. |
Data Mining centers on discovering records from several sources and transforming the data into a useful tool. It can be used across industries. |
Data Science makes data-focused products for organizations and drives decisions through the aid of records. It can be used across industries. |
5. |
Data mining involves the process of data analysis to obtain information. |
Data science focuses on the science of the data. |
6. |
The objective of data mining is to make existing data more valuable. |
The objective of the data science is to increase the dominance of the data product. |
7. |
This is a technique of extracting information and patterns. |
Data science is a wider field of studying about data. |
8. |
Data mining mainly used in business applications. |
Data science is mainly used in scientific applications. |
9. |
Data mining is a part of knowledge discovery in database processes. |
Data science is a field of study in different engineering disciplines like cloud computing. |
10. |
Data mining generally deals with structured data. |
Data science can deal with any type of data whether structured, unstructured, or semi-structured. |
Conclusion
The most significant difference that you should note here is that data mining is a technique used for business purposes, whereas data science is a field of study of data which is mainly used for scientific purposes.
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