29 June 2022 How to use the Lookup() function in Qlik Sense Share this message Every Friday at Bitmetric we’re posting a new Qlik certification practice question to our LinkedIn company page. Last Friday we asked the following Qlik Data Architect certification practice question about the Lookup() function in Qlik: The correct answer is C: Roller, UMW, Cobretti, Grotti Most of you got this answer right and that is no surprise. Things like vertical lookup, horizontal lookup and maybe even index match must be very familiar topics for many, but why still use Excel when we have Qlik, right? The lookup() function will evaluate a field from the current or a previously loaded table and find the matching field you enter. Or to put it as the syntax: lookup(field_name, match_field_name, match_field_value [, table_name]) To evaluate the right answer let’s visualize what lookup() has exactly done in the figure below: The Lookup() function is told to find the field value of ‘Manufacturer’ in the target table and match this to the field value of ‘ManufacturerID’ in the target table and ‘ManufacturerID’ in the current table. In the last part of the syntax we determine the target table which in this example is ‘ManufacturerData’. After the match is made it is added to the current table as the column ‘Manufacturer’. Please notice that all the input which refer to the target table are given in quotes. This is mandatory since the arguments without quotes refer to the current table. In this example we also immediately notice some of the limitations of lookup(). When Lookup() is being used, it will always return the value based on the load order and if no match is found it will return NULL. So in this example we are missing ManufacturerID = 4, so it returns NULL and since ManufacturerID = 5 is duplicated, it will return Grotti, since that value is loaded first. And hopefully this is the moment many of you hear the alarm bells ring about data quality. There are quite some things to fix in this data model, we agree, and probably lookup shouldn’t even be used here. Other options like ApplyMap() or even a join could just as well be used and are maybe even better, since the performance of lookup() is not known to be the fastest. So why use lookup? The main reason of this example is not to only show the disadvantages of lookup() but also bring us to the advantages. The strength of lookup() doesn’t lie in applying the lookup to whole tables, but more to get single values from a table, for example as use in variables: LET vExcludeManufacturer =Lookup('Manufacturer', 'ManufacturerID', 1, 'ManufacturerData'); LET vExcludeManufacturerID =Lookup('ManufacturerID', 'Manufacturer', 'Roller' , 'ManufacturerData'); These will result in: vExcludeManufacturer = Roller vExcludeManufacturerID = 1 And while this is an example in a very small dataset, the use case for large datasets is quite clear. So to cut it short, while ApplyMap() or Join would be the better and most of the times faster solutions to join fields to another table, Lookup() is a great way to quickly find individual values from a table, for example to use in a variable. That’s it for this week. See you next Friday? More from the Bitmetric team Bitmetric Qlik Support Keep your Qlik environment running smoothly with proactive support that prevents issues before they appear. Available on flexible monthly plans. Learn more. Qlik vs Power BI Series See how Qlik and Power BI perform when theory meets reality. Three apps rebuilt, every step examined. Learn more. Friday Qlik Test Prep Functions Performance Solution How can we help? Whether something’s still unclear or you’re ready to take the next step, Barry and Eric are happy to talk it through. Email us, call us, or book a meeting at a time that works for you. Call us Mail us 6 November 2026 Qlik Cloud overage: who decides how much risk you face? A small error in Qlik Cloud can lead to unexpected overage charges. But how large can that financial risk become? We share our own experience, explain how Data for Analysis overage works, and discuss why customers should be able to decide how much additional capacity they want to allow. We also look at ways to prevent overages and at developments surrounding Usage Bank. 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6 November 2026 Qlik Cloud overage: who decides how much risk you face? A small error in Qlik Cloud can lead to unexpected overage charges. But how large can that financial risk become? We share our own experience, explain how Data for Analysis overage works, and discuss why customers should be able to decide how much additional capacity they want to allow. We also look at ways to prevent overages and at developments surrounding Usage Bank. Data Analysis Governance Qlik
6 November 2026 Microsoft Fabric and Power BI: The Most Important Updates from October 2026 AI agents that build Power BI reports, independently perform data engineering, and provide increasingly accurate answers to questions about business data. In October, Microsoft once again made significant progress with Fabric and Power BI. But what do these developments mean in practice? We discuss the most important updates and share our experiences and insights. Agentic […] Microsoft Fabric Power BI
4 November 2026 Qlik Cloud Update October 2026: Semantic Models, AI, and Modern Development October brought 24 updates to Qlik Cloud. The introduction of Semantic Models in Data Products stands out in particular. Qlik Code for VS Code, AI-assisted development, and improvements to the Direct Access gateway also deserve attention. Our consultants discuss what these developments mean in practice. Qlik