How does the data visualization tool select the appropriate enterprise requirements to see if they meet these conditions

Time:2022-6-20

With the rapid development of economy, enterprises’ demand for data analysis is also increasing. At the same time, they also put forward higher requirements for data value mining, that is, the requirements for data visualization. To achieve the data visualization effect, we can use some high-quality data visualization tools to achieve.

Data visualization toolsIt is an application software that helps users display data intuitively and graphically, showing the complete outline of data. The visualization tool displays the results intuitively for users, and can help users quickly understand and analyze data.

At present, there are many kinds of visualized chemical products in the market, and their characteristics and prices are different. It is particularly difficult to choose the appropriate visualization tools. Take smartbi, a smart software with good market reputation, for example. It analyzes what features data visualization tools should include and how enterprises should choose their own visual tools.

How does the data visualization tool select the appropriate enterprise requirements to see if they meet these conditions

1. clear, concise and customizable interface

A good data visualization tool should have the following characteristics. Maintain proper balance on the interface; The interface accurately displays all important data; The interface is customizable. For example, KPIs, important trends or data sets related to important businesses that users are concerned about should be completely and clearly displayed within a few seconds after the interface is started, and all displayed contents should be clear at a glance.

How does the data visualization tool select the appropriate enterprise requirements to see if they meet these conditions

2. agility

This consideration is based on the fact that the whole program is easy to operate, easy to use and fast in functional response. Smartbi can quickly complete data set preparation, visual exploration and dashboard production by dragging and dropping the mouse. Smartbi has a wealth of interactive controls and chart components, which can easily make Bi Kanban without the limitation of dimension and measurement.

How does the data visualization tool select the appropriate enterprise requirements to see if they meet these conditions

3. display effect

The Bi visualization tool converts data into a plan view, which should not only make the picture look good, but also intuitively and clearly express the changes of data, so that the viewer can understand the trend of data without thinking more.

How does the data visualization tool select the appropriate enterprise requirements to see if they meet these conditions

Smartbi perfectly inherits the graphics function of Excel. It supports not only basic graphics, but also various advanced graphics derived from basic graphics creativity. Support images, illustrations, images and other drawings to increase the vividness and interest of the picture. It can also realize map analysis, interesting mapping and other functions. It supports multiple data sources, flexible layout, business themes and self-service groups, dual layout design, cross screen app publishing, and flow layout.

4. data mining

Data mining is the process of studying large amounts of data to determine their patterns and trends. When you are dealing with large data sets, and you want visual tools to help you extract potential information and generate visual reports, you need visual tools with this feature.

Smartbi supports five mature algorithms, including classification, regression, clustering, prediction and association, and supports efficient and practical algorithms for machine learning. These models include: logistic regression, decision tree, random forest, naive Bayes, SVM, linear regression, K-means, DBSCAN, Gaussian mixture model. In addition to providing basic algorithms and modeling functions, smartbi also provides necessary data preprocessing functions, including field segmentation, row filtering and mapping, column selection, random sampling, filtering null values, merging columns, merging rows, joining, row selection, removing duplicate values, sorting, adding serial numbers, adding calculation fields, and so on.

The above-mentioned data visualization tools should generally include the functional features, but when selecting data visualization tools, the most critical thing for enterprises is to depend on their own needs.