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ToggleData Mining and Data Analysis
Data is a valuable resource that is present in every corner of the world. Every day, a large amount of data is produced due to the increase in information sharing over the internet. Data is generated through website visits, advertisement clicks, and various other forms of online activities through the Internet. The data that is generated is stored for processing and deriving certain meaningful conclusions.
Nowadays, digital organizations indulge in several projects that make use of data. In these projects, the raw data generated and stored is modified and analyzed to derive some results. This is where concepts like data mining and data analysis come into existence. These two strategies are extremely important to define the success of every data science project. Therefore, these two steps should be performed with accuracy without taking any risk. Wish to pursue a career in data analytics? Enroll in this Data Analytics Classes in Pune to start your journey.
The role of data mining:
As mentioned, huge datasets are generated regularly, and this data is known as raw data. Data mining is the technique of recognizing the functional data from raw data that can be used to build efficient models for further processing. Data mining is a subset of data analysis, and this technique is often referred to as Knowledge Discovery of Data.
In simple words, just as the term mining suggests, data mining means diving deeper into the huge collection of data and identifying data that is useful for the project. This technique requires skilled professionals with strong knowledge of statistics, data modeling, and probability. Kickstart your career by enrolling in this Best Data Analyst Course in Chennai.
The role of data analysis:
This technique is considered to be the superset of data mining. Data analysis is the process of analyzing and visualizing datasets to discover hidden patterns. These patterns would be useful in data modeling and deriving certain meaningful insights to make better business decisions.
The person who performs this technique is a data analyst. To succeed in this role, strong analytical skills and familiarity with data visualization tools is a must. Pursue a career in Data Analytics with the number one training institute 360DigiTMG. Enroll in the Data Analyst Training in Hyderabad to start your journey.
Key differences:
Data mining and data analysis are two of the most used terms in the field of data science. Some of the key differences between these terms are given below:
- Data analysis is a complete process of analyzing, monitoring, and transforming raw data. Data Science is a step or a technique that is a part of the data analysis process.
- Data mining is a process of extracting essential data and eliminating the rest to derive insights. This essential data is then used in data analysis to build data models for making better decisions.
- In data analysis, strong knowledge about the various data visualization tools is required, whereas data science does not require visualization tools.
- Data mining is a strategy to transform the data that is unstructured into a structured and usable form. Data analysis is the method that is used to process the transformed data and deliver valuable information.
- Data mining is generally performed by only one person who possesses good technical and statistical skills. In contrast, a team of analysts is needed to visualize data and draw hidden patterns.
Data mining and data analysis are the most widely used techniques in every data science project. Although there are some differences between these terms, both these techniques are used to deal with data and transform it to help generate profits for the organization.
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