Adding Components for Interactivity

Actual business scenarios are often complex. The calculation results of a single component may not be sufficient to support analytical conclusions. It may require multiple components to interact for better offering important information.

This section will introduce some application scenarios that will be involved in the following examples.

Introduction to OLAP Function

The OLAP function of components makes data analysts efficiently analyze multiple data dimensions through dashboards, and makes the business personnel get rapid and flexible responses from dashboards based on their analysis operations.

• Drilling: When using a dashboard in practice, it is often necessary to first grasp the business problems from a macro level based on statistical charts, and then drill data down step by step through the drilling operation within a single page to locate the specific problems by reaching more-detailed data.

• Jumping: Jump from one dashboard to another dashboard (or another page). You can also set fields to filter while jumping.

• Linkage: When there is a logical relationship between components, clicking a certain value of one component and other related components will be filtered out relevant data.

• Filtering: When it is difficult to analyze too much data deeply and to view the data you want to see easily, you can add a Filter Component to dynamically filter data of the entire dashboard based on time, value, text, etc.

Dashboard

A dashboard is a panel composed of combined components. A well-designed dashboard can not only coordinate organizational work and help identify key issues, but also allow others to understand the content you want to express at a glance, or expand analysis based on your ideas.

For details, see Managing Dashboard.

The Sales Information table will be used for analysis.

Drilling

Problems can be discovered by continuously drilling-down data.

By analyzing the MOM Growth Rate of Gross Profit Margin, you can find a significant decline in gross profit in August.

Given that the lower the gross profit margin, the easier it is to cause a decline in gross profit, the declining reasons can be found through Gross Profit Margin.

Therefore, first create a group table to analyze the problem of product sales by drilling-down from the city to see the gross profit margin of a certain product for a specific store.

Adding Calculation Indicator

To create a new table, you need to add components and switch to the Sales Information table.

Add the field Gross Profit Margin. Click  in the Search area, and click Add calculation indicator. Input Gross Profit Margin as Indicator Name, and SUM_AGG(Gross Profit)/SUM_AGG(Sales) as the formula.

Formula explanation:

Creating a Table

Create a gross profit analysis table that is drilled-down step by step.

1. Drill-down step-by-step from City, Store NO. to Name. Drag the field in the area to be analyzed to create a drill directory.

2. Drag City field from the left side into Dimensions. Drag Gross Profit Margin, Gross Profit, Sales, and Cost fields into Indicators.

Rename this component as Gross Profit Margin Analysis.

However, the drilling table at this time shows the gross profit margin for all months. If you only want to analyze the specific situation of a certain month (such as August), you need to add Year and Month Filtering Component to the dashboard.

Adding Components to the Dashboard

Apart from drilling, a dynamic analysis for a single chart, filtering, linkage, and jumping are all dynamic analysis generated by multiple related components. Therefore, it is necessary to first add the components to the dashboard to prepare for other dynamic analysis.

Click Add dashboard and hold down Shift key to select all components to add to the dashboard.

Proceed as follows:

Filtering

After going to the dashboard, to freely view the data range you want to see, you can add a Filter Component to achieve filtering effects for the entire dashboard.

1. Filtering data by year and month.

Click Filter Component > Year and Month Filter Component.

Select the Date field in the Sales Information table.

Drag it into the upper right field column and click OK.

2. Filtering data by product category.

If you still need to filter by product category, you can add a Text Drop-down Filter Component.

Take the same steps as above. Rename the component as Category, then click OK.

Linkage

Components made from the same table will trigger linkage and filtering effects when clicking on data within the table.

For example, clicking Daily necessities will filter out other components, and display the gross profit information related to this category. Click Clear all linkages in the upper right corner to restore to the default status.

Technique and Beautification

Controlling the Scope of the Filtering Component

You can choose not to filter the components that you don't want to filter. If you use Year and Month Filter Component and hope the combined chart remains unchanged, you can set the control range of the component.

1. Click the year and month filtering component.

2. Tick the components that need to be filtered. Click OK. When the year and month filter component has filtering conditions, it will not affect the combined chart.

Canceling Linkage

How to achieve the effect that no matter which component is clicked, the pie chart will not be linked?

Set the linkage range for all components except the pie chart. Uncheck the pie chart in the components that can be linked.

For example, click the MOM Growth Rate of Gross Profit Margin component, and then click Manually set up linkage. Uncheck the pie chart component and click OK.