Learning notes ｜ data Xiaobai uses dataease to make a large data screen

Editor's note ：

This article is an original article by Zhihu blogger xiaominmin .

Link to the original text ：

https://zhuanlan.zhihu.com/p/521926246

Today's society is developing and progressing , data 、 Information is full of our life and work , Even if I have no relevant knowledge base , I also learned a lot of relevant information . I've been thinking about self-study data analysis , But for all kinds of databases 、 virtual machine 、 Front and rear code 、API Data source and other basic concepts of these data aspects only know a name . My college major and IT Informatization has nothing to do with it , Although I deal with all kinds of data after work , But in most cases, I just ask professional information technicians to give me the data I need , So my positioning is “ Data white ”.

By chance , I met. DataEase This open source product . After knowing its basic information , I think it's easy to use , And there are abundant learning materials , It is very suitable to be used as a learning tool for my introduction to data analysis . This article is for me to pass DataEase Data visualization , And made a record of my own dashboard ！ I hope I can give more like me “ Data white ” Provide some reference .

My data learning growth record , Mainly from learning methods 、 Hands-on practice 、 Results display 、 Summarize four aspects to introduce .

Learning methods

First step , Visit the official website of the company to which the product belongs , Mainly to understand the company behind the product .（FIT2CLOUD The official website address of feizhiyun ：https://www.fit2cloud.com/.）

Click into the official website and see a slogan of the company ——“ Software is valuable when used , There are opportunities for improvement ”. This slogan makes people feel very pragmatic . I have used all kinds of software , Some software doesn't care about the actual needs of users , Improvements and updates are not timely , This kind of software will be gradually eliminated later . So I think , Software is afraid of not being used , You can't make cars behind closed doors , Only in this way can it stand the test .

The second step , visit DataEase The product's official website , Have a basic understanding of the product .（DataEase Official website address ：https://dataease.io/https://dataease.io/.）

DataEase It is an open source data visualization analysis tool , Help users quickly analyze data and gain insight into business trends , So as to realize the improvement and optimization of business .DataEase Support rich data source connection , Be able to quickly make charts by dragging , And it can be easily shared with others .

The third step , Study DataEase Product online documentation .（ Document address ：https://dataease.io/docs/.）

DataEase The official document of is very detailed , You can fully understand the basic information and functions of the product , And how to deploy and use DataEase. As “ Data white ” Of me , The most serious part is “ Function manual ” and “ Teaching video ”. By reading the official documents , Many of my questions have been answered , And I found out DataEase The various tutorials are also very detailed , It greatly reduces my difficulty in getting started .

Through the previous steps of learning , I am right. DataEase Have a basic grasp , So start practicing .

Hands-on practice

Before doing it , I'm going to organize my thoughts . I use DataEase The ultimate goal of is to produce a large data visualization screen , While using DataEase Making dashboard is divided into four parts ： Data sources 、 Data connection 、 Data preparation 、 Instrument panel fabrication （ That is, data use ）.

1. Data sources

at present DataEase There are many types of data sources supported , The details are shown in the following figure .

There are various types of data warehouses / Data Lake 、OLTP Type database 、OLAP Type database , As “ Data white ” My understanding is , These are like the types of supermarkets , It's like a warehouse supermarket 、 Comprehensive supermarket 、 Convenience stores, etc , Only the size and positioning are different . There is also a data source name under the data source type , It's like different brands of supermarkets , Wal-Mart 、 Maiden voyage 、 Carrefour, etc . There is also a special one here API data source , It's like it's dedicated to those restaurants every day （ Regular periodicity ） Supermarket for delivery （ food market ）.

The above is my understanding of data source types , If there is any deviation, you are welcome to correct .

2. Data connection

Find out where the raw materials are , We are going to take or borrow the raw materials to our own home . In the product, the corresponding is to create a new data source . This process is like we are going to talk about cooperation with supermarkets , Need to complete docking and identity authentication with supermarkets , The supermarket allows us to get things inside . So we should do a good job of docking first , The data in it can be used later .

Different types of supermarkets need different certifications , For example, the information required by the database data source is like the name of the supermarket 、 Address 、 type 、 User authentication 、 A series of information, such as passwords .

3. Data preparation

After the data source is connected , We need to see what data we need , And extract these data into our data set .

There are two ways to connect , One is the direct connection mode , One is timing synchronization mode . Which mode to adopt is mainly determined according to our needs , For example, some restaurants take fresh ingredients as their main advantage , Then the delivery method they need is direct delivery （ Direct connection ）, As long as there are fresh raw materials, they need to be delivered immediately . Some restaurants may deliver raw materials at regular intervals every day .

DataEase The process of using is ： data source → Data sets → instrument panel .

4. Instrument panel fabrication （ Data usage ）

In this step ,DataEase The concepts of dashboard and view are introduced . Here we can understand the dashboard as our dining table , The view can be understood as a dish .

Let's start with the view . In the process of using it, I found that , To create a view, you must first select a dataset , This is something we need to pay attention to . The process of view making is as follows ：

The specific operation steps of view and dashboard will not be expanded for the time being , I'll share it with you later . and DataEase The design concept itself is also very simple , Various views / Components / Element settings can be quickly edited in the function bar on the right , After the elements are adjusted, the chart is automatically applied . View / Components / Elements are also operated by dragging , It's not too difficult .

You can learn the specific operation at feizhiyun School , The operation steps are very detailed . If you don't, you can join their community communication group , Have enthusiastic customer service little sister 、 Little brother and spontaneous volunteers help everyone solve problems .

Address of feizhiyun School ：

https://edu.fit2cloud.com/page/2635108?navIndex=1

stay “ Instrument panel fabrication ” What needs to be done in this step is , We need to show the data “ Loading ”（ That is, making views ）, And put it on the table （ That is, making dashboard ）. You can design and place according to your preferences .

Results display

As a “ Data white ”, I can make a large data visualization screen that I can change data at any time , And share it with those who want to share , There is no trouble for front and rear end technicians . For me, , This is a very fulfilling learning experience . The following figure is what I used DataEase The company's annual sales screen produced by this open source tool . It should be noted that , The data shown here are only schematic data , It is not the real business data of the company .

Sum up

DataEase Open source data visualization analysis platform for a white man like me , The function is easy to operate , Various concepts are also very convenient to understand . I can make a simple dashboard through official online documents and teaching videos , It can be seen that “ Everyone can use ” Our slogan is worthy of the name .

In the course of practical use , I found out, too DataEase Some places that can be improved ：

■ It is recommended to add gradient support to the chart color ;

■ It is recommended that the chart text support bold display .

in general , Use DataEase The process of data analysis is relatively easy and friendly . Whether it's the function of the product itself or the support of the product team , Put the user experience first . I hope this open source tool can be better and better , In the future, we can iteratively develop more usable 、 Powerful features .