At present, big data is more and more important to everyone, big data has gradually become the focus of research in various industries, we need to understand the tools used in big data when we carry out the use of big data, if we understand the tools of big data, we can better use big data. In this article we will give you an introduction to the tools in big data, I hope to be able to help you.

1. Tools for data mining

When working on data analysis, we need data mining, and for data mining, due to the importance of data mining in the big data industry, so the use of software tools to emphasize more on machine learning, the commonly used software tools is SPSS Modeler.SPSS Modeler is mainly for commercial mining to provide machine learning algorithms, at the same time, its data preprocessing and results to assist in the analysis of the aspect is also quite convenient, which is particularly suitable for rapid mining in a commercial environment, but its processing power is not very strong, once faced with too large a scale of data, it is difficult to use.

2. Tools needed for data analysis

In data analysis, commonly used software tools are Excel, SPSS and SAS. Excel is a spreadsheet software, I believe that many people are in the process of work and study, have been using this software. Calculation methods, so it is widely used, but it is only suitable for simple statistics, once the amount of data is too large, Excel will not be able to meet the requirements. SPSS and SAS are commercial statistics will only be used in the software, to provide us with the classic statistical analysis of the processing, which will allow us to better deal with business issues.

3. Visualization tools

In the field of data visualization, the most commonly used software is TableAU. The main advantage of TableAU is that it supports a variety of big data sources, but also has more types of visual charts and graphs, and the operation is simple, easy to get started, and it is very suitable for researchers to use. However, it does not provide support for machine learning algorithms, so it is not difficult to replace data mining software tools. Relational Analysis. Relational analysis is a new analytical hotspot in the big data environment, and its most commonly used is a visual lightweight tool - Gephi. Gephi can solve many of the needs of network analysis, powerful, and easy to learn, so it is very popular.

On the big data need to use the tools we have introduced to you here, in fact, there are many big data tools, we introduced in this article are very classic tools, of course, there are other tools to solve the corresponding problem, which requires you to continue to learn, continue to learn, in order to be able to integrate, so that their own learning has a qualitative leap.