In 2021, these five visualization tools must be used

As a data analyst, I feel inexplicably excited when it comes to data visualization. I think data visualization has two very important parts: one is data and the other is visualization. The most common problem we have is that we already have data but don’t know how to visualize it.

There are quite a lot of visualization tools on the market, which can definitely dazzle your eyes, but most of these are tools with relatively high threshold, such as Gantti, Paper.js, Highchart.js, etc. It must be said that they On a technical level, it is indeed very impressive and very mature. But the target user group is also relatively single, that is, programmers.

I personally feel that in the era of big data, the use of data will become more and more popular. Many companies that make data tools are trying to make data analysis a barrier-free thing. Only everyone can Only by making it easy to get started can we truly maximize the value of data.

So from this perspective, I would like to recommend several visualization tools that everyone can use and can quickly empower data.

#The purpose of data visualization?

Before recommending tools, we need to answer another question. What do you need to use these data visualization tools to do and what purpose do you need to achieve?

Maybe you have a complete idea that has been verified by facts and needs to be presented in a more intuitive and easy-to-understand way to tell a logic or a story;

Maybe you There is a large amount of data. How do you want to discover, mine, and display some knowledge or insights behind the data?

Maybe you have all kinds of data, but you don’t If you understand data modeling, programming, or data cleaning, you need an easy-to-use data visualization tool that can complete data visualization by dragging and dropping, and can provide the most appropriate display graphics;

Maybe There are various other scenarios, but all data visualization tools have a scenario of their core services. Beautiful, easy to use, simple, collaborative, smart, etc. are all labels given to each data visualization tool by its parents. We need Match relevant tags to make corresponding recommendations.

First of all, it must be clear that data analysis needs to be oriented by self-needs. Recommending visualization tools regardless of the purpose is a scam.

We can classify them as:

Personal self-service analysis: non-programmed visualization, suitable for business personnel, operations personnel, etc. to conduct self-data analysis without relying on IT personnel, representative tools For example, BI tools such as python, FineBI, Tableau;

Indicator monitoring reports: can reflect the actual business situation in a timely manner, and provide data analysis support for predictive analysis, decision-making and diagnosis, etc. The main tool is an enterprise-level reporting platform , there seems to be nothing else in China except FineReport;

Dynamic data visualization: It can realize the update and display of dynamic real-time data. In addition to time series data, there are also dynamic path data, real-time trajectory data, etc., which is quite professional. Representative tools are ECharts, etc.;

Okay, based on this assumption, I will start to recommend personal favorite data visualization tools based on purpose.

1. Personal self-service analysis

FineBI

Simple and clear data analysis tool, it is also my personal favorite The advantages of the visualization tool are zero-code visualization and rich visual charts. You only need to drag and drop to complete very cool visualization effects. It has functions such as data integration, visual data processing, exploratory analysis, data mining, and visual analysis reports. What's more important is that the personal version is free.

The main advantage is that it can realize self-service analysis, and the learning cost is extremely low. There is almost no need for profound programming foundation. It is easier to use than many foreign tools. , very suitable for regular business personnel and operations personnel. In terms of comprehensiveness, FineBI has outstanding performance. It does not require programming and is simple and easy to use. It can realize platform display and is more suitable for enterprise users and individual users. It is a good choice in terms of data visualization;

python

I originally didn’t want to put python in. After all, it is more troublesome to learn a scripting language like python, but in the end, I considered that python is too powerful, and data analysis visualization is only a small part of python. For some application directions, if you don’t want to type code, it is recommended to ignore this section.

In fact, it is not very troublesome to use Python to visualize data, because there are two libraries in Python dedicated to visualization, matplotlib and seaborn, which allow us to easily complete the task.

Tableau

Tableau is a data analysis reporting tool used by major foreign companies. Personally, I feel that the main focus is: a data analysis tool that everyone can use. Through simple graphical operations (similar to Excel), you can get what you want. Analyze the results.

#The principle is to establish a basic data set based on a certain SQL syntax by connecting to the company database and analyze the data set. This places high demands on the integrity of the data set.

2. Indicator monitoring report

finereport

One of the major applications of visualization is data reporting, and FineReport can be freely Compile the report fields required for integration for report output, and supports regular refresh and monitoring email reminders. It is a daily report platform used by most Internet companies.

Especially for business reports within the company system, we use a business reporting tool, which is finereport. I recommend it because it has two high-efficiency points: ① It can complete the process of fetching data from the database (with the function of integrating data) - designing report templates - data display. ② Similar to making reports in Excel, one template combined with parameter query can replace dozens of reports.

3. Dynamic Data Visualization

An open source visualization library implemented using JavaScript. The underlying layer relies on the lightweight vector graphics library ZRender, which provides intuitive, rich interaction and can A highly personalized and customized data visualization chart, which is open sourced by the Baidu team.

In actual development, data is often required to be fetched from the server for dynamic display. Generally speaking, the data request process is as follows:

The client sends a request through ajax;

The server-side Servlet receives the request;

Generates json data and returns it to the client;

The client displays the data after receiving it.

Jsp Servlet Echarts are usually used to achieve dynamic data visualization.

PHP Chinese website has a large number of free Python introductory tutorials, everyone is welcome to learn!

This article is reproduced from: https://www.jianshu.com/p/0474b0e3eb71

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