28 February 2022 Fan and chasm traps 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 a sales and budget model. In reality, we wanted to teach you about fan and chasm traps in Qlik. This week’s question has triggered an almost unanimous response. The correct answer is D: budgets cannot be shown for customers who haven’t bought anything We can verify this by loading a small dataset and see what happens. In the following set we have two customers, A and B. Customer A has sales amounts of 50 and 100, and a budget of 200. Customer B has no sales and a budget of 200. If we load this data into Qlik Sense and visualize it in a table we see the following result: We can clearly see that there is no association between Customer ID B, on row 3, and the Budget Amount 200, on row 4. The reason for this is the way the data is modelled: The CUSTOMER table is associated with the SALES table through the Customer ID field. In turn, the SALES table is associated with the BUDGET table through the Budget ID field. As Customer ID B does not have any sales, it’s missing the ‘hop’ between the CUSTOMER and BUDGET table. Only once Customer ID B has entries in the SALES table will the data be correctly associated. This issue is known as a ‘Chasm trap‘, where a model may suggest the existence of a relationship between entities (in this case, CUSTOMER and BUDGET), but the pathway does not exist for certain entity occurrences (in this case, Customer ID B). OK, so the correct answer is D, but isn’t C also correct? If you come from an SQL background you may expect that budgets get multiplied for customers who have multiple sales. This issue is known as a ‘Fan trap’ and it would be a correct assumption if we were to JOIN the tables together. In this data model however, that is not the case. This article by Henric Cronström explains it very well. Henric also gives an additional example of a Chasm trap, and a suggestion on how to resolve it. How can we model this correctly? Now that we know what the issue is, how can we model this data correctly so that customers, sales and budget are all correctly related? We’ll leave that topic for another time, although we’re certainly interested in your take on it 😉 We look forward to seeing your comments and hope to see you again next Friday! More from the Bitmetric team Take your Qlik skills to the next level! Since 2013, the Masters Summit for Qlik is the premier advanced training for Qlik. Join us in Vienna and take your Qlik skills to the next level. Join the team! Do you want to work within a highly-skilled, informal team where craftsmanship, ingenuity, knowledge sharing and personal development are valued and encouraged? Check out our job openings. Data Model Friday Qlik Test Prep Solution Hoe kunnen we helpen? Barry heeft meer dan 20 jaar ervaring als Data & Analytics architect, developer, trainer en auteur. Hij helpt je graag met al je vragen. Call us Mail us 8 October 2024 Artificial Intelligence, Machine Learning, and Deep Learning Explained: How They Impact Your Business In today’s rapidly evolving technological landscape, Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are transforming industries and redefining how businesses operate. In this blog post, we will break down these three definitions and elaborate on them. AI 25 September 2024 Building Ethical AI: Practical Frameworks for Responsible Innovation AI is transforming industries with innovation and efficiency. But with great power comes great responsibility. The real question is: How do you turn ethical principles into actionable guidelines for AI development? And what steps should your team take to make it happen? AI 17 September 2024 What is AI Ready Data Data quality is all about how accurate, consistent, complete, and up-to-date your data is. If your data is good, you’ll get reliable insights and be able to make smarter decisions. It’s a key part of making sure your AI and machine learning projects are successful. AI Qlik
8 October 2024 Artificial Intelligence, Machine Learning, and Deep Learning Explained: How They Impact Your Business In today’s rapidly evolving technological landscape, Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are transforming industries and redefining how businesses operate. In this blog post, we will break down these three definitions and elaborate on them. AI
25 September 2024 Building Ethical AI: Practical Frameworks for Responsible Innovation AI is transforming industries with innovation and efficiency. But with great power comes great responsibility. The real question is: How do you turn ethical principles into actionable guidelines for AI development? And what steps should your team take to make it happen? AI
17 September 2024 What is AI Ready Data Data quality is all about how accurate, consistent, complete, and up-to-date your data is. If your data is good, you’ll get reliable insights and be able to make smarter decisions. It’s a key part of making sure your AI and machine learning projects are successful. AI Qlik