How Can Beginners Design Cool Data Visualizations?
A discussion of the importance of data visualization in the data pipeline and on business decisions, and a look one data visualization tool.
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1. Why Do We Visualize Data?
At work, no matter which industry you are in, you will be exposed to data and need to express it. The role of data visualization is to better convey business information by combining charts and data. For the time being, most companies are gradually transitioning from traditional process management to data-based management. Data visualization can help analysts gain a more complete understanding of the data and gain insights that are more commercially valuable.
2. What Is Data Visualization?
Data visualization is how the data gets displayed after data analysis, including chart design, dynamic combination, two-dimensional charts, three-dimensional charts, linkage, drilling, large-screen display, etc.
The functions of data visualization are mainly reflected in two aspects: one is data display, and the other is business analysis. The data display is well understood. It is to display the known data or data analysis results through visual charts. Business analytics is the effective translation of data and metrics to be analyzed into business-valued insights after seeing charts, dashboards, and large screens, enabling them to support decisions based on facts.
3. How to Achieve Reliable Data Visualization
Data visualization will eventually return to the "reader." It helps the "reader" identify problems and make good decisions by conveying data. So the value of data is not that it is seen, but in the thoughts and actions it causes after it is seen.
Here, the data in the enterprise is different from ordinary application data. Most data does not directly generate value to the user. Instead, the data is analyzed through and then the manager thinks and judges, and finally takes action, so that the data can exert its value.
3.1 Who Is the Beneficiary of Visualization?
Whether you are doing a traditional report, PPT, or something else, you first need to figure out who this is for, what they need to know, what indicators they care about, and how they will use the information and data you present in the decision-making process. In one sentence, it is to figure out the goal of the user's data analysis work: what is this report used for? All the content to be presented in the subsequent data analysis work and analysis reports will be closely related to this target theme.
3.2 Tease Out the Indicator System
Data visualization is to sort out the complicated data into indicators, and form an indicator system around each business finance, sales, supply chain, production, etc., and finally display it through visual methods, such as the rate of return and efficiency benefit.
It can be said that the success of data analysis work is generally based on the establishment of indicators. This work requires the personnel of the data center or the personnel of the BI group to go deep into the business to investigate the demand, analyze the data, and build warehouses.
3.3 Combine Data Visualization With Business Solutions
If the purpose of data visualization is to present data that addresses specific, measurable, enforceable, relevant, and time-based issues, then add these issues during the production process and reporting process.
When planning a data visualization solution, make sure that this is to solve the user-specific problem. So your solution should not only be able to well explain the conclusions, information, and knowledge gained from data analysis. But more than that, managers can quickly find and discover decisions along the visual path you plan.
When the company's performance does not meet the target, the design path of the visualization scheme can be like this.
Step 1: From the perspective of the overall operation, you need to be clear about the key factors that will affect the performance.
Look at the performance of the KPIs corresponding to the key factors like sales orders, customer price, number of customers, user activity, product output, quality, cost, delivery, etc. These factors will be the driving factors, which will directly influence the performance. The visualization of this driving data is the foundation for finding a solution.
Step 2: You need to delve into the key factors and find out what factors are causing the performance to fail.
For example, you can use the comparative analysis to observe the performance of all key factors on the KPI in a certain period of time. In response to specific problems, track what the current action plan is, whether to adjust the progress, and explore ways to improve performance.
4. Data Visualization Tools
There are many tools for data visualization. Chart plug-ins like ECharts, Highcharts, and D3.js, are very powerful. There are also tools like Excel, Cognos, Tableau, FineReport, etc. For daily report production, this class of tools are easier to learn and use, and more biased towards business analysis. They cover a complex set of processes for data collection, analysis, management, mining, and visualization.
I'm used to using a zero-coding reporting tool, FineReport, which allows you to achieve cool visualizations with a simple drag-and-drop operation. I used to spend two hours charting or drawing. With FineReport, I can complete a dashboard in ten minutes. It is really friendly to beginners in data analysis.
Here I will show you some dashboards I made with FineReport, so that everyone can have a clearer understanding of data visualization.
3D Dynamic Effects
If you want to quickly get started with data visualization, I suggest you start with FineReport. You can go to the official website for a free download.
Published at DZone with permission of Lewis Chou. See the original article here.
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