# Qlik Sense Metadata Extraction

This article outlines the metadata extraction process for Qlik Sense applications, including scripts, measures, dimensions, sheets, visual objects, and internal data models. The extracted metadata provides visibility into application structure, calculations, transformations, reporting components, and data relationships.

The metadata supports dataset-level and column-level lineage, report cataloging, metadata enrichment, dependency tracking, and impact analysis by tracing data flows from source systems to Qlik Sense reports and visualizations.

## Metadata Extraction

Metadata is extracted for each Qlik Sense application to understand the structure, logic, calculations, visual elements, and internal data model. This information supports end-to-end lineage, report catalog mapping, impact checks, and column-level metadata enrichment.

The table below outlines the main metadata components:

**Metadata Components Summary**

<table><thead><tr><th width="124.45458984375">Component</th><th width="260.99993896484375">Description</th><th>Key Details</th></tr></thead><tbody><tr><td>Script Info</td><td>Load the script used in the application</td><td>Data extraction logic, transformations, variables, Section Access, load constructs</td></tr><tr><td>Measures</td><td>Metrics created in the app</td><td>Names, expressions, formatting, tags, field dependencies</td></tr><tr><td>Dimensions</td><td>Grouping and descriptive fields</td><td>Names, expressions, hierarchies, tags</td></tr><tr><td>Sheets</td><td>Report pages inside the app</td><td>Titles, owners, descriptions, order, hierarchy</td></tr><tr><td>Cells</td><td>Visual objects inside sheets</td><td>Object types, dimensions, measures, logic, visibility</td></tr><tr><td>Data Model</td><td>Internal data model of the app</td><td>Tables, fields, links, keys, relationships</td></tr></tbody></table>

## Detailed Metadata Explanation

### Script Info

The Script Info section explains the complete load script used inside the Qlik application. It describes how data is extracted, transformed, and prepared before it is loaded into the data model. It also shows how variables, mappings, and access rules influence the application's structure and behavior.

<div align="left"><figure><img src="/files/MIcjKRAWiqvsMBYLrFs3" alt=""><figcaption></figcaption></figure></div>

<div align="left"><figure><img src="/files/tEwIidUsLjA4cU0u5fo4" alt=""><figcaption></figcaption></figure></div>

#### What It Contains

The Script Info file holds the complete Qlik Sense load script, including:

* Logic for extracting data from source systems such as databases, files, APIs, and QVDs
* Transformations like joins, concatenations, filters, and calculations
* SET statements and variables
* Section Access
* Resident loads, preceding loads, mapping loads, and other script constructs

#### How It Is Used

* Parse load statements to build source to target lineage
* Identify upstream data sources and map them to database objects
* Extract derived fields and transformation logic

### Measures

The Measures section explains the calculations that define the business metrics inside the application. It shows how each measure is built using expressions and which fields are involved. It helps identify how these measures contribute to visual objects and how changes to fields may affect calculated results.

<div align="left"><figure><img src="/files/cBHYvhTt30uoz0HxIfhl" alt=""><figcaption></figcaption></figure></div>

<div align="left"><figure><img src="/files/tEom1yOJJRTrtr4VQm1C" alt=""><figcaption></figcaption></figure></div>

#### What It Contains

The Measures file lists all measures present in the application and includes:

* Measure names and IDs
* Expression definitions such as SUM, AVG, and conditional logic
* Formatting details
* Tags, descriptions, and labels
* Fields used in the expression

#### How It Is Used

* Extract business metrics into the catalog
* Parse expressions to identify field relationships
* Build lineage from fields to measures and visualizations
* Support impact checks for fields referenced in measures

### Dimensions

The Dimensions section explains the descriptive or grouping fields used inside charts, filters, and navigation components. It shows whether a dimension is based on a direct field or an expression and whether any hierarchy is applied. This information helps understand how users segment, filter, and explore the data inside the application.

<figure><img src="/files/5KNBWgHGzZbN4ayq4I6W" alt=""><figcaption></figcaption></figure>

<figure><img src="/files/HxTFmsZZkJrkir9tto15" alt=""><figcaption></figcaption></figure>

#### What It Contains

Dimension metadata includes:

* Dimension names and IDs
* Underlying fields or expressions
* Hierarchy information, if available
* Tags and descriptions

Dimensions may be basic field-based dimensions or calculated dimensions using expressions.

#### How It Is Used

* Catalog descriptive attributes
* Parse derived expressions for lineage
* Identify field usage across reports
* Support semantic alignment with glossary terms

### Sheets

The Sheets section describes the layout of the application by listing each report page along with its title, owner, and description. It explains how sheets organize the visual objects and define navigation across the application. It provides clarity on how information is arranged for reporting and analysis.

<figure><img src="/files/N0UnYwOzYb0iJm6k8XID" alt=""><figcaption></figcaption></figure>

<div align="left"><figure><img src="/files/9W2GmPC27dTKfKgUJEKt" alt=""><figcaption></figcaption></figure></div>

#### What It Contains

Sheets represent report pages or dashboards. Sheet metadata includes:

* Sheet titles and IDs
* Creator or owner information
* Descriptions
* Display order
* Navigation hierarchy

#### How It Is Used

* Catalog each sheet as a report entity
* Link visual objects and KPIs to sheets
* Provide lineage showing which data is used in each sheet

### Cells (Visual Objects)

The Cells section explains each visual object placed on the sheets, such as charts, tables, KPIs, and filters. It shows which measures and dimensions each visual object uses and how expressions or visibility rules affect the displayed output. This information supports detailed lineage by linking visual elements back to fields, calculations, and data sources.

<figure><img src="/files/LPanmhqZEO5RFOaovsfL" alt=""><figcaption></figcaption></figure>

<div align="left"><figure><img src="/files/YFuOaD55PGCJnnIZcweo" alt=""><figcaption></figcaption></figure></div>

#### What It Contains

Cells correspond to visual elements such as:

* Charts
* Tables and pivot tables
* KPIs
* Filters and list boxes
* Extension objects

Each visual object includes:

* Dimension and measure references
* Visualization type
* Expressions and calculations
* Sort and limit logic
* Conditional visibility settings

#### How It Is Used

* Build lineage from visual objects to fields
* Document each visual component for catalog use
* Enable impact checks for changes to fields used in visuals

### Data Model

The Data Model section explains the structure of all tables and fields stored inside the application after the load script is executed. It shows how tables are connected, which fields serve as keys, and whether synthetic keys or circular references are used. This section helps trace each field back to its origin in the script and understand how data is associated inside the application.

<figure><img src="/files/xRQzrWlWsvfgs53wZrSj" alt=""><figcaption></figcaption></figure>

<div align="left"><figure><img src="/files/OaDXyvqBPmdqCNRZzIdq" alt=""><figcaption></figcaption></figure></div>

#### What It Contains

The Data Model metadata outlines the internal data structure of the application:

* List of tables in the model
* Table attributes
* Field details, including names, origins, types, and key flags
* Links and associations between tables
* Any synthetic keys, concatenated tables, or circular references

#### How It Is Used

* Rebuild the semantic data layer
* Map each field to its script origin
* Build column-level lineage from sources to the Qlik model to reports
* Identify join paths and associations used in the app

## Value of Metadata Extraction

**Metadata extraction enables:**

* Dataset-level lineage from source systems through load scripts to sheets and visualizations
* Column-level lineage showing transformations and expressions
* Semantic documentation covering measures, dimensions, and logic
* Impact checks for changes to fields, tables, or objects
* Cataloging of all Qlik reports and metadata elements

{% hint style="info" %}
Each metadata file plays a specific role in tracking lineage and understanding report behavior. Missing or incomplete metadata may affect analysis accuracy.
{% endhint %}

***

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