6 April 2022 Literal values vs search strings in Qlik Set Analysis 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 search strings in Set Analysis: This is typically a relatively tough question, but fortunately everyone who participated is above average! The correct answer is D You may wonder why this is a tough question, that’s because in the past both single and double quotes would be evaluated as a search expression by Qlik. This has lead to single and double quotes being used interchangeably, while formally only the double quotes are correct. The single quotes (‘) are used to denote a literal value. So by using single quotations in Set Analysis, you are looking for an exact match with that value. In this case the answer B solution will be looking for literally Internal* as field value. By using double quotes (“) Qlik will interpret this as a search value. In this example, the correct answer D, will be conducting a search for Internal*. The asterisk is a wildcard that can match any (sequence of) character(s). In this case Internal-Call, Internal-Chat and Internal-Email would be matched. What about flag fields? Yes, if this particular condition is one you want to test more often then it can be beneficial to create flag fields in your data model. This will make your Set Analysis easier and in cases more performant as well. In the context of this question though, we only wanted to test if you knew the difference between single and double quotes in Set Analysis. We’ve already established that you’re all above average 😉 That’s it for this week. See you 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. Expressions Friday Qlik Test Prep Set Analysis Solution How can we help? Barry has over 20 years experience as a Data & Analytics architect, developer, trainer and author. He will gladly help you with any questions you may have. 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