When business analysts are performing data analysis, they may encounter scenarios where the existing data cannot meet their own needs and need to upload Excel data locally for analysis. At this time, we can achieve this through the relevant functions of the Smartbi product!
Data collection in 1 minute, data preparation in 3 minutes, and dashboard report generation in 5 minutes. It is easy to control and realize data analysis without professionalism.
We first upload the local data through the Excel import function, then prepare the data through the self-service data set, and finally use the prepared data to create the self-service dashboard.
Whether it is data import or data preparation, the entire operation interface is visualized without any code; secondary semantic layer modeling can be performed and packaged as a personalized "data mart"; when the amount of data is large, extraction rules can be defined to the cache to speed up subsequent analysis application!
No formulas are required for data analysis, and various aggregations can be realized; no presets are required, and intelligent screening and linkage are possible; one-key layout, arbitrary switching of theme colors; one-time design to meet the needs of different terminals.
data collection
Import Excel, collect data using tables
We first import the data in Excel to the relational data source by importing the Excel file. Select Load Excel data, then create a new data table, select the data information to be loaded, and click Import Data to upload local data.
data preparation
Secondary modeling, encapsulation of personality "data mart"
After successfully importing data, create a new self-service data set, perform secondary semantic layer modeling according to requirements, and encapsulate it into a personalized "data mart".
1. If necessary, you can drag and drop other data resources to perform related queries. The self-service data set supports automatic association according to the field name, and the association relationship can also be edited;
2. Supports data processing operations such as field classification, rename, and display in a visual manner;
3. Support generating calculated fields, time dimensions, etc. For example, in the dimension "end of month" creation time dimension is "year quarter month", as shown in the figure:
After completing the settings, we can save the data set and name it.
data analysis
Simplify the dimensions, filter the required data and display it in charts
1 Create a new self-service dashboard
Click Analysis Display in the system navigation bar to display the main menu of the "Analysis Display" interface, and click the shortcut menu of the self-service dashboard to enter the "New Self-Service Dashboard" interface:
2 Select data source
In the "data area" on the left, you can directly select the data source by searching, or search from the resource catalog area and select the self-service data set we created before.
3 Select the settings component
We can choose the corresponding components according to our own needs. The product includes a wealth of component types, which can be selected and used by dragging and dropping.
For each component, we can set its data, style, etc. according to its own properties, and adjust its position and size by dragging.
For example, drag the graphic component from the toolbar to the right side of the display area, and double-click in the resource to select the field dimension "car company" and measurement "scale" to be associated:
4 Add filter
The component filter refers to the chart as the filter. We can set the filter linkage to filter data, such as selecting "year" as the filter, and set the filter to apply to the components that need linkage, and realize the linkage between charts.
5 Select page theme
We can choose other themes according to our own preferences. For example, select "dark theme" in the theme options, save and rename it.
note
1. When setting the dashboard style, we must pay attention to the unity principle of data visualization, pay attention to the overall layout layout, and make key data prominently displayed;
2. Try to use the same color system, so that the visual elements are evenly distributed throughout the frame, so that the data can be viewed more intuitively.
Data presentation
Adjust the layout to be applicable to mobile devices
1 Adjust the dashboard layout
We can select the mobile device in the toolbar to switch to the mobile page, and then adjust the layout of the components in the mobile phone by dragging, and we can choose the order of the components according to our actual needs.
2 Save the current self-service dashboard
When the dashboard is finished, you can save the dashboard so that it can be browsed on the browse interface. If the data is updated, upload the new data through the data connection to update it in real time.
With the rapid development of the data age, data analysis has become a more important link in the development of technology, and data visualization is a key skill and the ultimate means of presenting the intrinsic value of data. Master the true visual expression thinking, quickly split data, and create a beautiful and intuitive data analysis dashboard, you can stand out and become an old driver of data visualization.