Quo vadis Qlik? Part 2 – Advanced Analytics with the Associative Engine

May 18, 2025

Reading time: 3 min

By Maris Svilans,

Head of Sales, Co-Founder, The Infotrust

Personal note: Writing this from Copenhagen Airport, en route to Qlik Connect in Orlando, which is the the perfect moment to continue my Qlik reflection series.

In Part 1, I explored how Qlik embraces open Lakehouse architecture by integrating Apache Iceberg and real-time data pipelines to build a robust, scalable data foundation. We highlighted streaming data in near real-time, unlimited scalability, and open storage solutions. Now, let’s explore how this strong data backbone empowers analytics, focusing specifically on Qlik’s unique Associative Engine.

The Associative Engine

Qlik’s Associative Engine stands out as a uniquely powerful analytics tool, enabling users to freely and intuitively navigate complex, multi-dimensional datasets without predefined drill-down paths or rigid pre-aggregated structures. Every interaction – selection=click (hence the name – QLIK) – triggers an instant recalculation of related data, dynamically showing hidden relationships and associations. By keeping data fully loaded in-memory, Qlik delivers results at the speed of thought, promoting fast, insightful decisions at the speed of thought.

Moreover, the associative engine goes beyond traditional query-based analytics:

• Users can ask questions spontaneously, uncovering associations across seemingly unrelated data points without waiting on prebuilt aggregations.
• Qlik automatically highlights both associated and excluded data upon user interaction, dramatically increasing transparency and context – awareness. In contrast, other tools typically limit users to predefined filters, requiring developer intervention whenever additional filters are needed. Qlik empowers users by enabling any data element to act as a filter, offering immediate and flexible data exploration.
• By loading data from cloud platforms like Snowflake directly into memory, Qlik significantly accelerates queries and reduces compute and query-related costs.

Inside the QIX Engine

At the heart of Qlik’s associative analytics capability lies the Qlik Indexing (QIX) Engine, which enables the unique associative experience. The QIX Engine handles complex, interactive data analysis with exceptional speed and flexibility through several critical components:

• Symbol Tables and Data Tables. Data is stored in a highly compressed format, organized into symbol tables (storing unique field values) and data tables (containing references to these symbol tables). This setup ensures efficient memory usage and extremely fast data retrieval.
• State Vectors. These manage the selection states across the entire data model, instantly recalculating visualizations based on user interactions and selections.
• Logical Inference Engine. Unlike traditional query-based engines, the QIX Engine dynamically infers associations between data points. This enables users to freely explore their data, discovering insights without the constraints of pre-set drill paths.

For a deeper understanding, watch Henric Cronström‘s insightful presentation on the QIX Engine: “QIX Engine: Under the Hood”. This recording was made during an event organized by The Infotrust in Vilnius, where Henric participated as a guest speaker.

Global Search Capability

Another distinctive feature powered by the QIX Engine is Qlik’s global search functionality. Users can instantly search across the entire dataset with a single query, uncovering relevant associations and insights without needing predefined queries or structured paths. To learn more about this capability in action, please check Michael Tarallo‘s awesome demonstration.

This global search leverages the associative capabilities of the QIX Engine to rapidly index and retrieve information across all dimensions and measures, making it remarkably intuitive and efficient.

Customer Success Story – BOM Cost & Margin Analysis

Let me share a story which will be unveiled at our Qlik Customer event in Vilnius. A leading manufacturer reliant on commodities was looking for a solution to effectively manage profitability impacted by volatile raw material costs, traditionally tracked using SAP’s Bill of Materials (BOM). Precise, proactive analysis was critical to maintaining competitive margins amid rapid market fluctuations.

Leveraging Qlik, we successfully provided a tailored solution enabling the customer to:

• Integrate near-real-time commodity prices, foreign exchange rates, and other essential market variables.
• Dynamically recalculate complete BOM structure costs in real-time, instantly assessing impacts across multiple product lines simultaneously.
• Immediately visualize the effects of market changes on product-level profitability, empowering the sales team with proactive margin insights.

The solution significantly enhanced their ability to conduct complex “what-if” scenario analyses with ease, addressing questions such as:

• “What if copper prices rise by 15% next quarter?”
• “What would a sudden spike in energy costs mean for Product X’s margin across different market regions?”

This advanced capability delivered immediate business benefits:

• Finance teams gained the ability to forecast margins with remarkable accuracy and speed.
• Procurement teams could dynamically adjust their hedging strategies based on instantaneous scenario outcomes.
• Supply Chain teams swiftly adapted production schedules, increasing agility and significantly reducing operational costs.

As a result, the manufacturer achieved greater financial predictability, strategic agility, and improved profitability in a volatile market environment.

Bridging Robust Data Infrastructure and Agile Decision-Making

The Lakehouse architecture outlined in Part 1 ensures data freshness, accuracy, and integrity, providing an ideal foundation for the Associative Engine. From data ingestion to actionable insights, the entire analytics process can occur in minutes – significantly improving responsiveness and agility in volatile market conditions.

Anticipating Qlik’s Next Leap in AI

At Qlik Connect in Orlando, I’m particularly excited to explore upcoming advancements like Qlik’s Agentic AI capabilities. Stay tuned for Part 3, where I will share the latest updates and innovations from Qlik’s main annual event.

Interested in learning more? Join us at our upcoming Qlik events in the Baltics:

• Riga – May 20, 2025
• Vilnius – May 22, 2025

Seats are limited, so register now at events.theinfotrust.com. You’ll hear firsthand updates from Qlik Connect and inspiring customer success stories, including insights from manufacturing company SEDAMYL , insurance company BTA Baltic Insurance Company AAS, banking ( Citadele banka), and logistics & milling company OtankiMill .

See you there!