Advanced self-service analytics tools are usually very easy to use and practically any user can create visualizations without prior experience and only require little training. However, there are a few basic rules that you should follow to make your visualization eye-catching and to give it a high degree of expressiveness and clarity.
1.Setting basic question – What purpose is to serve the graphics? Who is the target audience? What matters is the target audience? Which further questions stimulate the graphics? By addressing such issues, make sure that users use their time as sensibly as possible with your visualization and gain targeted insights from it.
2.Keep it simple – The most common mistake when creating a visualization piece is to overloading with information. A successful piece should meet strict selection, and make only the relevant indicators. It is also recommended to avoid using too many colors and shapes because that could increase level of complexity and hinder your audience to understand the information.
3.Data from all relevant sources – The combination of data from different sources provides a better insight into the subject and increases or accelerates the gain in knowledge. For example, by combining your customer data with publicly available demographic data, you may certainly develop better prediction and take preventive measures, instead of just reacting.
4.Make sure data is updated – Make sure that the data used for the visualization is updated and that the selected indicators relate to timely business challenges. Try to use tools or approaches that can be used to create the visualization once and then are able to update automatically. This saves tedious and repeating work, and accelerates the reporting cycle and releases workforces free for more important tasks.
5.Choose the suitable chart type – The use if chart type depends on what content you want to show. For example, to track a trend over time, you can use line, area and bar charts. Before deciding the appropriate chart type, you should experiment and view your data from different perspectives. If you have enough knowledge to interpret your data, you can gain completely new insights through this visual exploration. These are the most common chart types for typical application scenarios.
Following are some examples of the most commonly used chart types for visualization (examples from Google Charts Gallery):
The line chart
Line charts are among the most commonly used types of charts. The line chart connects single numerical data points and thus represents a simple, straightforward solution to visualize data as a sequence of values. Line charts are primarily used to display trends over a certain period.
The bar chart
Bar charts are perfect for comparisons and rankings; for example, comparing data in different countries, regions or business segments. Because the human brain can very quickly compare the length and the horizontal and vertical position of graphic elements, this chart type is particularly popular. Horizontal bars have the advantage that the viewer can read the labels without having to turn his head. Different colours can be used to categorize different data groups. By arranging the bar size according to size, the audience is immediately drawn to the longest bar.
The pie chart
Pie charts are used to illustrate the proportions of the whole. However, caution is required when there are too many segments because pie chart will be less understandable if there are too many sub-groups (slices). For more segments, the brain can no longer recognize the differences well, since it has to compare too many different angles.
Interactive maps can not only display geographic distributions, they can also be used to serve as a filter for other charts and graphs as well. Interactive maps can help to show detailed information in the data and to enable in-depth data research. For example, by clicking a country on the map, the information related to that country can be shown as number, table and charts.
The scatter chart
To determine whether there is a potential relationship between two indicators, a correlation analysis can be done by means of a scatter diagram. For example, scatter chart can be used to show correlation between sales volume and price for a company.
The Gantt chart
Compliance with the deadlines is vital to the success of a project, and the project task completion status must be visible at all times. Gantt charts are a great way to show the start and end dates of individual project elements. Except for project management, Gantt charts are also used to plan certain resources. For example, determine how long it takes an employee to reach certain milestones.