**A Comparative Study of Data Mining and Data Visualization**

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**A Brief on Data Mining and Data Visualization**

Data is a very important part of any business operation. These business operations include education, retail, and health care. These operations help us to determine if the data is important or not. The procedure of working on data and then coming up with outcomes to predict future outcomes and trends has come up a long way. **Data Science** has become very famous with all kinds of latest technologies such as **big data analytics**, data mining and data visualization.

**What are the two parts of Data Science?**

Data science is a major part of computer science which has statistics and computing along with other mathematical and technical processes involved. These different methodologies form an integral part of the data science program. Thus, we can say the two parts of **Data Science** are data mining and data visualization.

**The concept of Data Mining**

The term data mining was framed in the year 1990s. Data mining involves running of data and presenting the output after screening them properly. This involves running and screening of data using various mathematical tools and statistical tools. These data patterns are found out of the accumulated data. These include the various processes such as data extraction, data transformation, data management and processing of data.

The three different pillars of data mining are:

**Statistics**– The use of statistics in data mining involves the use of numeric to study various relationships.**Machine Learning**– This form of machine learning involve the use of an algorithm to learn about predictions by studying the present data. This is however achieved by the use of various research tools.**Artificial Intelligence**– It is about the use of automation and machine technology to achieve the human-like operations.

**What is machine learning?**

Machine learning is the science of creating algorithms and programs for a system which has the capability of learning on its own from the given set of data. Some of the examples of typical machine learning application are credit scoring, fraud detection, stock trading and spam filter.

**The Concept of Data Visualization**

Data visualization is a form of data science concept which is comparatively simpler than data mining. Data visualization is such a concept that makes it easier to understand the process. Some of the common data visualization modes adopted by various companies include pie charts, graphs, statistics presentation, bar graphs and many more.

The main objective of data visualization is to spread information regarding graphs, plots and statistical graphs in a very clear and efficient manner.

The main point here is that both data mining and data visualization plays a very important role in the process of data interpretation along with message conveying process. Data mining involves a greater in-depth analysis. Data visualization can be defined as a pictorial representation of data to simplify the process of understanding information by the use of data.

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