---
Brand: klarmetrics.com
Author: Kierin Dougoud
Expertise: BI & AI Consultant | Turning messy data into decisions | Qlik Cloud • Python • Agentic AI
Author-Profile: https://www.linkedin.com/in/mkierin/
Canonical-URL: https://klarmetrics.com/qlik-sense-synthetic-keys/
---

# Qlik Sense Synthetic Keys: How to Identify and Fix Data Model Problems

**Synthetic Keys** appear when two or more tables share multiple common fields and can drastically hurt performance. Fix strategies: **field renaming**, **compound keys**, **star schema**, and **qualified fields**. A clean **star schema** with a central fact table reduces memory usage by up to 70% and improves query performance by 3-5x.

# What Are Synthetic Keys in Qlik Sense?

**Synthetic Keys** are anonymous fields that Qlik Sense creates automatically when two or more tables share multiple common fields. These keys represent all possible combinations of the composite key fields.

# How Do Synthetic Keys Form?

When **Table A** and **Table B** both contain the fields ProductID AND CategoryID, Qlik Sense creates a **Synthetic Key** that represents all combinations of these two fields.

**Example: How Synthetic Keys Are Created**

Table: Sales
├── ProductID
├── CategoryID
├── Revenue
└── Date

Table: Products
├── ProductID
├── CategoryID
├── ProductName
└── Price

→ Synthetic Key: ProductID + CategoryID

# Why Are Synthetic Keys a Problem?

Although **Synthetic Keys** work technically, they can cause significant performance and memory issues, especially with large data volumes.

# How Do Synthetic Keys Affect Performance in Qlik Sense?

Memory usage: Up to 300% higher with complex Synthetic Keys
Query speed: 3-10x slower with multiple chained Synthetic Keys
Reload time: 50-200% longer data loading with Synthetic Key chains

# Critical Problems with Synthetic Keys

* **Exponential memory consumption:** Each additional Synthetic Key multiplies memory requirements

* **Cascade effects:** Chained Synthetic Keys can destabilize the entire data model

* **Unpredictable performance:** Response times vary depending on user selections

* **Difficult troubleshooting:** Performance issues are hard to identify and trace

# How Do You Identify Synthetic Keys in Qlik Sense?

# How Do I Use the Data Model Viewer?

The [Data Model Viewer for diagnosing synthetic keys](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/Visualizations/data-model-viewer.htm) is your primary tool for identifying and understanding data model issues.

# Step-by-Step Identification in the Data Model Viewer

* **Open Data Manager:** Navigate to Data Manager → Data model viewer

* **Look for Synthetic Keys:** Anonymous tables named $Syn 1, $Syn 2, etc.

* **Analyze connections:** Which tables are linked via Synthetic Keys?

* **Check field overlaps:** Which fields are involved in creating the Synthetic Key?

# How Does Script-Based Detection Work in Qlik Sense?

// Synthetic Key Detection Script

// List all table names (including Synthetic Keys)
FOR i = 0 TO NoOfTables() - 1
    LET vTableName = TableName($(i));

    // Check if it is a Synthetic Key (starts with $Syn)
    IF Left('$(vTableName)', 4) = '$Syn' THEN
        TRACE 'WARNING: Synthetic Key found: $(vTableName)';
    ENDIF
NEXT i

// Analyze field overlaps between tables
FOR i = 0 TO NoOfTables() - 1
    FOR j = $(i) + 1 TO NoOfTables() - 1
        LET vTable1 = TableName($(i));
        LET vTable2 = TableName($(j));

        // Count common fields
        LET vCommonFields = 0;
        FOR k = 0 TO NoOfFields('$(vTable1)') - 1
            LET vField = FieldName($(k), '$(vTable1)');
            IF FieldIndex('$(vField)', '$(vTable2)') >= 0 THEN
                LET vCommonFields = $(vCommonFields) + 1;
            ENDIF
        NEXT k

        IF $(vCommonFields) > 1 THEN
            TRACE 'WARNING: $(vCommonFields) common fields between $(vTable1) and $(vTable2)';
        ENDIF
    NEXT j
NEXT i

# How Do You Apply Fix Strategies for Synthetic Keys in Qlik Sense?

# How Do I Rename Fields in Qlik Sense?

# Implementation: Using the AS Keyword

// Before the fix: Both tables contain ProductID and CategoryID

// Sales table - rename CategoryID
Sales:
LOAD
    ProductID,
    CategoryID AS SalesCategoryID,   // Rename to avoid Synthetic Key
    Revenue,
    Date
FROM [lib://DataFiles/Sales.xlsx];

// Products table - keep CategoryID as-is
Products:
LOAD
    ProductID,                       // Remains as the link field
    CategoryID,                      // Unique name in this table
    ProductName,
    Price
FROM [lib://DataFiles/Products.xlsx];

// Result: Only ProductID is shared → No Synthetic Key

# How Do You Create Compound Keys in Qlik Sense?

# Implementation: Creating Composite Keys

// Compound Key for unique identification

Sales:
LOAD
    ProductID & '-' & CategoryID AS ProductCategoryKey,  // Compound Key
    ProductID,
    CategoryID,
    Revenue,
    Date
FROM [lib://DataFiles/Sales.xlsx];

Products:
LOAD
    ProductID & '-' & CategoryID AS ProductCategoryKey,  // Identical Compound Key
    ProductID,
    CategoryID,
    ProductName,
    Price
FROM [lib://DataFiles/Products.xlsx];

// Result: Unique connection via ProductCategoryKey

# How Do I Implement a Star Schema in Qlik Sense?

# Implementation: An Optimal Data Model Structure

// Star Schema: One central Fact Table + Dimension Tables

// Central Fact Table
FactSales:
LOAD
    ProductID,       // Link to DimProducts
    CustomerID,      // Link to DimCustomers
    DateID,          // Link to DimDate
    Revenue,         // Measure
    Quantity,        // Measure
    Discount         // Measure
FROM [lib://DataFiles/Sales.xlsx];

// Dimension Tables (separate connections)
DimProducts:
LOAD
    ProductID,       // Primary Key
    ProductName,
    CategoryID,
    CategoryName,
    Price
FROM [lib://DataFiles/Products.xlsx];

DimCustomers:
LOAD
    CustomerID,      // Primary Key
    CustomerName,
    Region,
    Country
FROM [lib://DataFiles/Customers.xlsx];

DimDate:
LOAD
    DateID,          // Primary Key
    Date,
    Year,
    Quarter,
    Month
FROM [lib://DataFiles/Calendar.xlsx];

// Result: Clean 1:n relationships, no Synthetic Keys

# How Do You Use the QUALIFY Statement in Qlik Sense?

# Implementation: Automatic Field Qualification

// QUALIFY statement for automatic field renaming

// Prefix all fields with the table name
QUALIFY *;

Sales:
LOAD
    ProductID,       // Becomes Sales.ProductID
    CategoryID,      // Becomes Sales.CategoryID
    Revenue,         // Becomes Sales.Revenue
    Date             // Becomes Sales.Date
FROM [lib://DataFiles/Sales.xlsx];

Products:
LOAD
    ProductID,       // Becomes Products.ProductID
    CategoryID,      // Becomes Products.CategoryID
    ProductName,     // Becomes Products.ProductName
    Price            // Becomes Products.Price
FROM [lib://DataFiles/Products.xlsx];

// Define the shared link field
UNQUALIFY ProductID;   // ProductID in both tables without prefix

// Result: Only ProductID is shared, all other fields are qualified

# What Are the Best Practices for the Star Schema?

The **star schema** is the optimal data model structure for Qlik Sense and avoids Synthetic Keys by design. For comprehensive guidance on data modeling patterns, see the [Qlik data modeling best practices](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/Scripting/data-modeling.htm) documentation.

# What Are the Advantages of the Star Schema in Qlik Sense?

3-5x faster query performance through fewer table hops
40-70% lower memory usage through optimized associations
Easier to understand for developers and end users
Simpler to maintain and extend the data model

# How Do You Implement a Star Schema in Qlik Sense?

Component
Purpose
Fields
Best Practice

**Fact Table**
Central transaction data
Foreign Keys + Measures
A single large fact table

**Dimension Tables**
Descriptive attributes
Primary Key + Attributes
Normalized, smaller tables

**Date Dimension**
Time-based attributes
DateID + Calendar hierarchies
Always as a separate dimension

**Bridge Tables**
Many-to-many relationships
Foreign Keys
Only when absolutely necessary

# How Do I Optimize a Data Model Optimization Workflow in Qlik Sense?

# The 8-Step Optimization Process

* **Analysis:** Open the Data Model Viewer and identify Synthetic Keys

* **Documentation:** Document all affected tables and fields

* **Business Logic Review:** Are all relationships logically correct?

* **Choose a fix strategy:** Field renaming vs. compound keys vs. star schema

* **Script backup:** Save the existing script before making changes

* **Implementation:** Apply the chosen solution step by step

* **Testing:** Compare memory usage and performance before and after

* **Validation:** Verify the factual correctness of results

# How Do I Monitor Performance in Qlik Sense?

# Key Performance Indicators (KPIs) to Monitor

* **Memory Usage:** Target below 2 GB for standard apps

* **Reload Time:** Target below 5 minutes for typical ETL processes

* **Query Response:** Target below 2 seconds for standard charts

* **User Experience:** Smooth navigation with no noticeable delays

# What Common Mistakes Should You Avoid with Qlik Sense Synthetic Keys?

# The Top 5 Data Modeling Mistakes

* **Descriptive fields as keys:** Fields like «Comment» or «Description» should not be used as join fields

* **Multiple fact tables:** Avoid complex multi-fact schemas without a star schema design

* **Circular references:** Loops in the data model lead to unpredictable results

* **Unqualified auto-joins:** Qlik Sense automatically creates associations for fields with matching names

* **Missing data governance:** Consistent naming conventions and documentation are often absent

# How Do You Apply Proactive Prevention Strategies?

# Best Practices for Clean Data Models

* **Naming conventions:** Use clear and consistent field names

* **Documentation:** Document every table and relationship

* **Regular reviews:** Conduct monthly data model audits

* **Automated testing:** Script-based validation of model quality

* **Team training:** Regular training sessions on data modeling best practices

# How Does Performance Compare Before and After Optimization?

Metric
With Synthetic Keys
After Star Schema
Improvement

**Memory Usage**
8.5 GB
2.8 GB
-67%

**Reload Time**
25 minutes
8 minutes
-68%

**Chart Response**
8-15 seconds
1-3 seconds
-75%

**User Satisfaction**
65%
92%
+42%

# What Further Resources Are Available on Qlik Sense Synthetic Keys?

# Related Qlik Sense Guides

* [Qlik Sense Performance Optimization Best Practices](https://klarmetrics.com/qlik-sense-performance-optimization-best-practices/)

* [Qlik Sense Chart Types Complete Guide](https://klarmetrics.com/qlik-sense-visualization-guide/)

* [Qlik Cloud Migration Strategy Guide](https://klarmetrics.com/qlik-cloud-migration-strategy-guide/)

# How to Identify and Fix Synthetic Keys in Qlik Sense?

**Synthetic Keys** are a sign that a data model needs attention. By consistently applying **star schema principles**, **clean field renaming**, and **strategic compound keys**, you can drastically improve the performance of your Qlik Sense applications.

Goal: No Synthetic Keys through optimal star schema design
Result: 3-5x better performance and 40-70% lower memory usage
Benefit: Better user experience and easier maintenance

Invest in data model quality from the start — the performance gains and reduced maintenance costs justify the initial effort many times over.

# How to identify and fix synthetic keys in Qlik Sense?

Source
Title
URL

Qlik Help
Synthetic keys
[help.qlik.com/synthetic-keys](https://help.qlik.com/en-US/sense/May2025/Subsystems/Hub/Content/Sense_Hub/Scripting/synthetic-keys.htm)

Qlik Community
How to solve synthetic key in Qlik Sense
[community.qlik.com/synthetic-key-solutions](https://community.qlik.com/t5/Visualization-and-Usability/How-to-solve-synthetic-key-in-Qlik-sense/td-p/1201628)

Ometis
Synthetic Keys in Qlik Sense
[ometis.co.uk/synthetic-keys](https://ometis.co.uk/blog-news/synthetic-keys-in-qlik-sense)

Qlik Help
Viewing and transforming the data model
[help.qlik.com/data-model](https://help.qlik.com/en-US/sense/May2025/Subsystems/Hub/Content/Sense_Hub/DataModeling/view-data-model.htm)

Ometis
Data Modelling Best Practices
[ometis.co.uk/data-modelling-best-practices](https://ometis.co.uk/blog-news/qlik-best-practice-data-modelling-in-qlik-sense)

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