In the enterprise’s data analysis project, “data management cockpit” is a very important part in the process of system construction. Through the data management cockpit, the collected data can be visualized, intuitive and specific, so as to provide support for relevant business decisions of enterprises. In other words, the data management cockpit provides a management process, so that the data can be reflected in a more organized form.
What is the data cockpit?
Speaking of the data cockpit, my heart responded: “cockpit? What auto parts should it be?” although the data cockpit has little to do with cars, it still has some similarities with the real cockpit. Their purpose is to provide professional guidance. Therefore, a successful data cockpit first requires an understandable height, and then requires visualization, because not only professional data analysts, but also ordinary employees can observe the data according to the specific application scenarios and obtain the required conclusions.
Secondly, the data cockpit should be unified as a whole, because it needs to include a large number of data combinations with multiple dimensions to uniformly display the overall picture of the business. For example, in the data analysis of the sales industry, it is necessary to include more comprehensive sales performance analysis, sales personnel composition, sales data in different time regions, etc., and use a variety of data charts to reflect the progress of these businesses.
Finally, the data cockpit also needs to be fully flexible and configurable, so that users can flexibly select data from different dimensions for combined analysis according to their own needs to meet the application needs of different scenarios.
How to build a data cockpit?
The construction of cockpit is mainly composed of data application architecture and data visualization platform. Among them, data application architecture means that enterprises need to sort out the current business needs and data applications, clearly know which businesses can be analyzed with data, and uniformly display and manage these data analysis results in the way of “story panel”.
To build a data cockpit, the most important thing is to comprehensively analyze the composition of enterprise business, and select the data to be presented according to different business modules, preferably in a tree or parallel structure.
However, the efficiency of manual mode is relatively low. How to improve the efficiency? Users can improve efficiency with the help of smartbi data analysis platform, which can provide customized and automatic data cockpit construction, which can greatly reduce the workload.
For example, the smartbi data analysis platform has a powerful “story panel” function. Users can not only organize multiple charts and output story Kanban in the same panel, but also directly generate slide show through text boxes, components and charts. Without exporting data and charts, they can quickly report and solve business problems in time.
If you want to build a data cockpit, improve work efficiency, respond to and solve business problems in time, smartbi can help you!