(Note: All the charts and dashboards in this article are made with the BI reporting tool FineReport<\/a>.)<\/p>\n Contents<\/p> Summary data analysis is usually used to count key core indicators, such as the company\u2019s annual operating income, annual consumption costs, and annual net profit, which are often the data that decision makers are most concerned about.<\/p>\n As shown in the figure below, we use the dashboard<\/a> component of FineReport <\/a>to calculate the three core indicators: the company\u2019s total annual revenue, annual cost, and net profit. We set the maximum range of the dashboard to a total revenue of 278 million, and enable the function of displaying percentages. In this way, the two indicators of consumption cost ratio and profit margin are automatically displayed.<\/p>\n Here is another example of summary data analysis.<\/p>\n Development trend analysis is usually used to visually compare the financial operating data or financial ratio trends of a certain continuous interval of the enterprise, and to understand the trend of the financial situation of the enterprise over time. On the one hand, it is possible to analyze whether there is an abnormality in the data increase or decrease, to find possible problems in the enterprise. On the other hand, it can also help the enterprise predict the future financial situation and judge the development prospect.<\/p>\n We generally use line charts to show the development trend of the company. The horizontal axis represents time (year, month, and day), and the vertical axis represents indicators such as operating income, costs, and profitability.<\/p>\n The following dashboard report is an example that combines summary data analysis and development trend analysis.<\/p>\n Data has no value without comparison, and the same is true in corporate financial analysis<\/strong><\/a><\/span>. Through the comparison of various indicators, we reveal the financial status, operating conditions and cash flow of the company. Generally speaking, the reference standards for comparative analysis are as follows.<\/p>\n Bar charts and histograms are often recommended for data comparison analysis. In addition, you can use other charts according to the specific situation, such as the line chart to show the inventory comparison of several companies, and a radar chart (suitable for quick comparison and positioning of weaknesses) can be used to compare the classification statistics of financial indicators.<\/p>\n The following dashboard uses bar chart, histogram, and radar chart. We can also refer to such a dashboard report<\/a> when doing financial statement analysis.<\/p>\n And here is a financial dashboard which combines Donut chart, histogram and radar chart.<\/p>\n Composition analysis can usually be used to analyze the data of each project\u2019s constituent elements, such as sales composition analysis of each product, current asset composition analysis, and management cost composition analysis of each department. It represents the composition of the data structure. In terms of charts, pie charts, donut charts, percentage stacked bars and percentage stacked histograms are common for composition analysis.<\/p>\n In addition, when you need to analyze both the composition structure and the hierarchical structure of the data, multilevel pie charts are undoubtedly the best choice. As shown below, multilevel pie chart makes it easy to calculate the proportion of sales in each province and city.<\/p>\n Here is a cash flow report in which pie chart and histogram are used.<\/p>\n In the financial statements, it is often necessary to show the progress of achieving an indicator or a task, such as the performance of department and the progress of reporting expenses. In this case, we can use stacked column charts, stacked bar charts, and Gantt charts to display data.<\/p>\n Finally, I will introduce the data analysis method related to maps. For large enterprises, in addition to the headquarters, there are branches throughout the country and even the world. In situation like this, using maps to analyze data based on geographic location is more appropriate.<\/p>\n The flow map displays the interaction data between the outflow area and the inflow area. It is usually expressed by the line connecting the geometric centers of gravity of the spatial elements. The width or color of the line indicates the flow value.<\/p>\n The flow map is mostly used in regional trade, traffic flow, population migration, shopping and consumption behavior, communication information flow, and aviation routes.<\/p>\n The heatmap is used to indicate the weight of each point in the geographic area. In addition to the map as the background layer, you can also use other images. And color in a heatmap usually refers to density.<\/p>\n The above are the six data analysis methods and corresponding charts that we commonly use when making financial statements, which can be used as a reference when you make data analysis statistics. In addition, the charts in this article are made with the BI reporting tool FineReport<\/strong><\/a>. Its personal version is free to download and use, and it provides many templates for beginners to learn. You can try it yourself.<\/p>\n A Guide to Take Your Data Reporting to Another Level<\/em><\/a><\/p>\n \n Guide to Financial Statement Analysis For Beginners<\/em><\/a><\/p>\n1. Summary Data Analysis for Financial Statements<\/span><\/h2>\n
![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*JIexDHnqoUnzRZf9StSH6A.png\")
<\/figure>\n![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*nu0EMVr0JAcUtbLMauRGaw.png\")
2. Development Trend\u00a0Analysis<\/span><\/h2>\n
![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*VxEuiRWH0bLb0DNhaYKhug.png\")
<\/figure>\n![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*uVFkHwNJRg7ubhGyIufiHA.png\")
3. Data Comparison Analysis for Financial Statements<\/span><\/h2>\n
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![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*37K_Wfcif3DCiMpB2MTK3A.png\")
<\/figure>\n![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*hBeg_zv6OqmGRNlm7Pj_Cw.png\")
<\/figure>\n![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*uIavt4SQNLjG7O9LWVyjGw.png\")
![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*AwVIq_rkiPohdGbYuir73w.gif\")
4. Composition Analysis for Financial Statements<\/span><\/h2>\n
![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*r5NY1weoXL2dzjceSfzbIA.gif\")
<\/figure>\n![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*0__k5eWKxTq9mmMtzSKhiQ.gif\")
5. Progress Analysis for Financial Statements<\/span><\/h2>\n
![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*EUVc8V6COqovlanVS4_eXA.gif\")
<\/figure>\n![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*6qK0BuiCMA5_lryuQWBMvg.png\")
<\/figure>\n6. Map Analysis for Financial Statements<\/span><\/h2>\n
![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*NT0_YUrcGTZZcPWTiOLqXw.gif\")
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![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*dgSHu7PcxlpGYuu7RHt-nQ.gif\")
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![](\"https:\/\/cdn-images-1.medium.com\/max\/1600\/1*0u5vYwHzeN6INrJkxTwnKQ.png\")
<\/figure>\nIn the end of Financial Statements<\/span><\/h2>\n
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