当前位置:网站首页>Staying up late summarizes the key points of report automation, data visualization and mining, which is different from what you think

Staying up late summarizes the key points of report automation, data visualization and mining, which is different from what you think

2020-11-06 20:12:27 The sail is soft

 

First of all, business intelligence and report automation .

business intelligence , also called BI, Using modern data warehouse technology 、 Online analytical processing technology 、 Data mining and data presentation technology for data analysis to achieve business value .

Report Automation It refers to the traditional manual collation of reports (excel) To achieve automation of the process , For example, calculate the total sales of the month , The automatic report can automatically calculate the total sales information of the current month according to all the sales order records of the month , It doesn't have to be done manually like the traditional way - statistics .

business intelligence ≠ Report Automation , It can be said that report automation is a foundation of business intelligence , Only by automating the processing of a large amount of data first 、 Summary 、 Statistics can further practice business intelligence .

 Staying up late summed up report Automation 、 Key points of data visualization and mining , It's not what you think

 

As mentioned above, report automation is the foundation of business intelligence , So what else is needed ? We can definitely know that there must be data mining , But this step is relatively complicated , In the process of gradually realizing business intelligence , What we are looking forward to is to generate value continuously in the process of realization , I think it can be divided into the following steps :

 Staying up late summed up report Automation 、 Key points of data visualization and mining , It's not what you think

 

Report Automation

Since reporting automation is the foundation of business intelligence , So implement it first , What is the value of this step ?

  • Release the labor force : When the data is so huge 、 Miscellaneous times , Any enterprise will have all kinds of data , Relatively simple statistics may only need to analyze one type of data , But a little bit more complicated will result in the fusion of multiple types of data or complex analysis on the time line , At this point, a lot of manpower is needed , The realization of automation can directly reduce the repeated development of this part , Note that “ repeat ”.
  • Reduce the error rate : Automation means persisting processes through coding 、 Logic , When we debug it right once , So we can trust this tool , I believe that the stable output rate of machines is more reliable than that of human beings in the repeated work scenario .
  • High timeliness : Except for the monthly reports , We can also consider the implementation of statistics on each day of the month , Collect daily information in real time to dynamically control the monthly plan .
 Staying up late summed up report Automation 、 Key points of data visualization and mining , It's not what you think

FineReport Do report Automation

Data charting

The pie chart 、 Broken line diagram 、 Histogram …… I'm talking about charting here , It's not a one-step Visualization , Even visualizing the level of the big screen .

Why do you have a chart first ? It's just a small step , But it can definitely improve the utilization of data to a great extent , The graph can help us visualize initially .

 Staying up late summed up report Automation 、 Key points of data visualization and mining , It's not what you think

 

Preliminary data understanding method : Why curing ?

A number is placed on the screen independently , What is the connection between them ? Who and who needs aggregate analysis ? Charts can be used to solidify business needs or data experts' sensitivity to data , The relationship between the data they found is persisted into code and displayed in a fixed chart , So that any user can see the data and the relationships between them .

Data visualization

What's the relationship between charting and Visualization ? In fact, the representation of the above diagram is preliminary visualization , But one or two charts can be quickly understood , Dozens of them ? Too much information requires classification , We can do that .

1、 Graph aggregation

We need to deal with the relationship between charts reasonably , Although a chart can show multiple data or even multiple dimensions of information , But there is a limit to what a chart can represent , We may need to combine multiple charts to show , The relationship between this combination may be :

  • According to the business mix : Go on to the supermarket , We can according to the sales situation 、 Upstream suppliers 、 Employee management and other different businesses are classified 、 grouping , Combine reports , Display this type of report in a visual area for comprehensive analysis
  • According to the value mix : There is a need to break down departmental barriers in management , It's the same with data visualization , Supermarket purchase and sales will have a certain relationship , The speed with which some items are sold may be affected by the number of salesmen on the day 、 The impact of the number of customers entering the store on the same day , According to a certain relationship, the data that may affect each other / Calculate the formula for statistics , Get valuable information , For example, performance indicators such as conversion rate
  • According to the information combination : Some information may need to be brought together for display , For example, supermarket items that are about to expire

2、 Display optimization

When we put all kinds of information together and show it , We also need to beautify the data

  • When it comes to multi-dimensional, we can directly see the evaluation score of each dimension in the same stage in the form of polygon ;
  • Information such as ratios can be displayed in colored bars or circles , In addition to being able to see the ratio, you can also directly alert people by color

In the end, we get “ Visualization screen ”, For example, the effect in the figure below , It's all by FineReport It's done .

 Staying up late summed up report Automation 、 Key points of data visualization and mining , It's not what you think

 

 Staying up late summed up report Automation 、 Key points of data visualization and mining , It's not what you think

3、 data mining

Through the report we can see some trends , For human visual observation , We may be able to see more clearly the trend shown by the line chart , But how to quantify trends ?

Other forms of reporting , Even the rules among the data that are not organized into reports ?

Data mining can be done at this time , Find potential connections between data in a variety of analytical ways , Making data more valuable .

 Staying up late summed up report Automation 、 Key points of data visualization and mining , It's not what you think

 

Last

There must be an end

This article mainly talks about how to gradually achieve business intelligence BI, Through reporting Automation 、 Data charting 、 Data visualization 、 Four steps of data mining , Step by step, let the data generate value .

Of course, this is just the beginning of this series of articles , I'd rather say the first step , Report automation how to do , The following articles will explain my understanding of report automation step by step 、 A design method of report system 、 Data warehouse dimensional modeling process and my practical experience .

 
 

 

版权声明
本文为[The sail is soft]所创,转载请带上原文链接,感谢