INTRODUCTION
We are very familiar with the word data science as it is in trend everywhere. The data science technology is becoming the new approach for companies. The executives are preferring the data science technology for business intelligence. This technology is beating all the traditional technologies which were formerly used by executives for running their business smoothly. Data science technology finds the hidden pattern and useful information from a large set of data. Here, the hidden pattern means–> when the data is collected from the user, it usually has a pattern. These patterns are made on the basis of the way the user uses his own data. The data science technology extracts information from those patterns. Data mining and data analysis are two important techniques of the data science technology. However, these two technologies seem to be same but are completely different from each other. When the data is collected from the user, it is analyzed very carefully. That’s why there are different techniques or methods which are used by data science technology for analyzing the data. All these methods and techniques performs their task in different way. Here, we will discuss what is data mining, what is data analysis and the difference between them.
WHAT IS DATA MINING?
Data mining is a very important technique of the data science technology. The data mining technique is used to concentrate useful information from an ample amount of the data. Whenever the data is collected from the client, the whole data is not useful for the producer or the company. The useful information which is required for producing a satisfying output is concentrated on from the collected data. This is what we call data mining.
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WHAT IS DATA ANALYSIS?
Data analysis is also an important technique of the data science technology. We can say that data mining is a part of data analysis technique. Data analysis contains all the processes which are required for arranging the collected data in an organized and structured way. Whenever the data is collected from the user, it doesn’t always get collected in a structured way. The data needs to be arranged and organized for producing an output. This technique is used to collect data from the user, arranging the data and analyzing of the data through visualization.
DIFFERENCE BETWEEN DATA MINING AND DATA ANALYSIS
- Data mining is used to recognize hidden patterns from the sets of data. On the other hand, data analysis is used to arrange and organize the data.
- Data mining uses machine learning and statistics for its implementation. On the other hand, data analysis uses artificial intelligence, machine learning, statistics, mathematics for its implementation.
- The data mining technique can be implemented by one person through algorithms. The people who do this are known as data mining specialists. On the other hand, a data analysis technique requires a team for its implementation.
So, those were some differences between data mining and data analysis.
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