From Raw Data to Actionable Insights – Qlik Sense’s Model

The Qlik Sense data model is the underlying structure of the data that is used in a Qlik Sense application. It defines how the data is organized and connected, and how it can be accessed and analyzed.

A Qlik Sense data model consists of three main components:

1. Tables: Tables are the basic units of data in a Qlik Sense data model. They contain rows of data, with each row representing a single record and each column representing a field or attribute. Tables can be connected to other tables through relationships, which define how the data in one table is related to the data in another table.
2. Fields: Fields are the individual attributes or columns in a table. They represent the data that is stored in each column of a table, and can be used to create visualizations and perform analysis.
3. Relationships: Relationships define how the data in one table is related to the data in another table. They are created by linking fields in different tables through common values.By connecting the “Customer ID” field in the “Orders” table to the “ID” field in the “Customers” table, for instance, a relationship between a “Orders” table and a “Customers” table might be established.

The Qlik Sense data model is an important aspect of Qlik Sense applications, as it determines how the data can be accessed and analyzed. Careful design of the data model can make it easier to create accurate and meaningful visualizations and analyses.

The Qlik Sense data model is a multidimensional data structure used to store and organize data in a way that supports efficient analysis and visualization. It has the following key components:

1. Tables: The raw data is stored in tables, each representing a single data source.
2. Fields: Columns in the tables are called fields, which contain the data values.
3. Relations: Relationships between tables are defined using links between the fields in the different tables.
4. Dimensions: Fields that are used to categorize data into groups are called dimensions.
5. Measures: Fields that contain numerical values used for calculation and analysis are called measures.
6. Calculated fields: Custom expressions can be created to derive new fields based on the data.
7. Star and snowflake schemas: The data model can be structured using either a star or snowflake schema to optimize performance and support efficient data analysis.

The Qlik Sense data model enables users to seamlessly combine and analyze data from multiple sources, perform advanced analytics, and create interactive visualizations to uncover insights and drive decision making.