Data Mining and visualization in the big data age

Billions of people around the world use computers, tablets, mobile phones, and other digital devices to generate massive amounts of data each day. Data has been infiltrated in various industries and fields, and data has become a very important factor in the big data era, big Data Processing and big data mining will mean a new wave of increasing productivity and a wave of consumer surplus.

 

In the big data era, data mining is impossible from the beginning to the end. Someone compared the data to a coal mine with energy. Coal is classified into coking coal, anthracite coal, fat coal, and lean coal. The mining costs of Open-pit coal mines and shenshan coal mines are different. Similarly, big data is not "big", but "useful ". The value content and mining cost are more important than the quantity.

What is data mining?

 

Data mining refers to the extraordinary process of revealing hidden, unknown, and potentially valuable information from a large amount of data in a database. Data Mining is a business process that detects a large amount of data to discover meaningful patterns and rules. Data Mining is a decision-making support process. It is mainly based on artificial intelligence, machine learning, pattern recognition, statistics, databases, and visualization technologies, and is highly automated in analyzing enterprise data, make disruptive reasoning, discover potential models from them, help policy makers adjust market strategies, reduce risks, and make correct decisions.

 

Why data mining?

 

We care about Data Mining and how to find what we need through the data mining process. If we compare big data to an industry, the key to achieving profitability for this industry is to improve the "Mining Capability" of data and realize "value-added" of data through "mining ".

 

Data Mining is a business process that detects a large amount of data to discover meaningful patterns and rules. When talking about discovery models and rules, it is actually a business process that serves the business. What we need to do is to make the business easier or directly help the customer improve the business. Find meaningful patterns and rules in a large amount of data. In the face of a large amount of data, data acquisition is no longer an obstacle, but an advantage. Nowadays, many technologies perform better in big datasets than in small datasets-you can use data to generate intelligence or computers to do what they are best: raise and solve the problem. Patterns and rules are defined as patterns or rules that are beneficial to the business. The discovery Mode means that the target of the retention activity is positioned as the most likely lost customer. This means optimizing the customer's access to resources, taking into account the short-term benefits of the number of customers, as well as the medium-and long-term benefits of the customer's value.

Visualized presentation of data mining results

 

The Strategic Significance of big data technology is not to grasp the huge data information, but to perform professional processing on the meaningful data, visualize the results of massive amounts of information data after distributed data mining. Data Visualization mainly uses graphical means to clearly and effectively convey and communicate information. Based on the data and its internal patterns and relationships, we can use computer-generated images to gain in-depth understanding and knowledge. Second, the vast bandwidth of the human perception system is used to manipulate and interpret complicated processes, datasets involving different subject fields, and simulation of large abstract data sets with diverse sources.

 

However, this does not mean that data visualization must be boring to achieve its functional purposes, or it may seem extremely complicated to look colorful. In order to effectively convey ideas and concepts, aesthetic forms and functions must go hand in hand. By intuitively conveying key aspects and features, we can gain insight into sparse and complex datasets. Therefore, the development of data visualization application software is imminent. The development of data visualization software should not only ensure the implementation of its functional purposes, but also take into account the aesthetic form, this puts forward higher requirements for data visualization software. Currently, there are only a handful of data visualization software that can take both of these two aspects into account in China. Among them, the most popular is a visual analysis software named Big Data magic mirror. With the big data Magic mirror, enterprises can integrate various internal and external data for real-time analysis to promote their intelligent data management, enhance their core competitiveness, and transform data value into commercial value, to maximize profits.

For more highlights, the latest big data information, industry cases, and solutions, please scan the big data magic mirror number

Data Mining and visualization in the big data age