- Hands-On Business Intelligence with Qlik Sense
- Pablo Labbe Clever Anjos Kaushik Solanki Jerry DiMaso
- 297字
- 2021-07-02 13:05:30
Table associations
The power of Qlik Sense Associative resides in how your tables are associated. Unlike SQL tools, you don't have to worry about Many-To-One and One-To-Many relationships and predefine the exploration path between your data. You can load your data, set which fields (usually called key fields) are the links between the tables, and Qlik Sense Associative takes care of the rest.
Now, let's see how we can create the associations between the two tables we have loaded:

On the right-hand side of the screen, you can see a section called Recommended associations. While loading your data, Qlik Sense analyzed your tables and proposed how to associate your tables based on a complex algorithm that considers distinct values of each field, column names, and the frequency of each value for each table.
Press the Preview all button to check how Qlik Sense is proposing to associate our tables. It should look something like this:

As you can see, Qlik Sense will draw a blue association between the two tables and highlight the columns in green that it is using as link keys between the two tables. In our case, Qlik Sense chooses CustomerID for both tables as fields that are eligible to link our tables. As an example, VINET values from Orders will match with VINET values from customers. Now, press the Apply all button; you're going to see that the blue connection becomes a dark gray one, indicating that the association was created:

Now, we have to load all tables using the Load data button, and then create all the associations:

If you go to Data model viewer, you will see your tables linked:

In the following screenshot, we can see our two tables and how they are associated:

- 大數據戰爭:人工智能時代不能不說的事
- Managing Mission:Critical Domains and DNS
- 影視后期制作(Avid Media Composer 5.0)
- Apache Hive Essentials
- Apache Spark Deep Learning Cookbook
- 精通特征工程
- 機器人編程實戰
- Mastering Game Development with Unreal Engine 4(Second Edition)
- TensorFlow Reinforcement Learning Quick Start Guide
- 格蠹匯編
- 過程控制系統
- 運動控制系統(第2版)
- EJB JPA數據庫持久層開發實踐詳解
- Raspberry Pi 3 Projects for Java Programmers
- EDA技術及其創新實踐(Verilog HDL版)