21 Mar 2024 Tihomir Babic 15 Tricky SQL Interview Questions for Experienced Users SQL interview questions for experienced users usually contain some trick(y) questions. Interviewers use them to test your gumption, which is typically a result of extensive experience and a high level of SQL knowledge. I will show you 15 tricky SQL interview questions (mostly coding) in this article. Mind you, these are not necessarily complex questions. Actually, that’s their main characteristic: they seem very easy and straightforward, but that’s the interviewer trying to deceive you. Read more 4 Apr 2018 Aldo Zelen How to Become a Database Analyst Curious about becoming a database analyst? Maybe you've taken some database courses at university and they really struck a chord. Or maybe you learned online. Now you're thinking about making a career out of working with databases. Where would you start? What should you expect at each phase of your professional development? In this post, we'll explore the challenging and exciting world of databases analysis. We'll go from the very beginning of a career to the apex of professional success. Read more 15 Dec 2017 Dejan Sarka Statistics in SQL: Dependencies Between Discrete Variables In my previous article, we looked at how you can calculate linear dependencies between two continuous variables with covariance and correlation. Both methods use the means of the two variables in their calculations. However, mean values and other population moments make no sense for categorical (nominal) variables. For instance, if you denote "Clerical" as 1 and "Professional" as 2 for an occupation variable, what does the average of 1.5 signify? Read more 12 Dec 2017 Aldo Zelen Simplify SQL Code: Recursive Queries in DBMS Hey SQL users! Are you repeating the same query in every report? Are your queries getting too complicated? Use recursive queries to simplify SQL code! Too many SQL reports can lead to clutter on your desktop and in your head. And is it really necessary to code each of them separately? Ad-hoc queries can share much of the same SQL code with managerial reports and even regulatory reports. Suppose you’ve been writing basic SQL code for a while. Read more 31 Aug 2017 Aldo Zelen Common SQL Window Functions: Positional Functions Positional SQL window functions deal with data's location in the set. In this post, we explain LEAD, LAG, and other positional functions. SQL window functions allow us to aggregate data while still using individual row values. We've already dealt with ranking functions and the use of partitions. In this post, we'll examine positional window functions, which are extremely helpful in reporting and summarizing data. Specifically, we'll look at LAG, LEAD, FIRST_VALUE and LAST_VALUE. Read more 7 Aug 2017 Aldo Zelen SQL Window Functions: Partitions and Ranking Functions You’ve started your mastery of SQL window functions by learning RANK, NTILE, and other basic functions. In this article, we will explain how to use SQL partitions with ranking functions. Mastering SQL window functions (AKA analytical functions) is a bumpy road, but it helps to break the journey into logical stages that build on each other. In the previous Common SQL Functions article, you learned about the various rank functions, which are the most basic form of window functions. Read more 4 Aug 2017 Ignacio L. Bisso SQL Window Function Example With Explanations Interested in how window functions work? Scroll down to see our SQL window function example with definitive explanations! SQL window functions are a bit different; they compute their result based on a set of rowsrather than on a single row. In fact, the “window” in “window function” refers to that set of rows. Window functions are similar to aggregate functions, but there is one important difference. When we use aggregate functions with the GROUP BY clause, we “lose” the individual rows. Read more 24 Jul 2017 Dejan Sarka High Performance Statistical Queries –Skewness and Kurtosis In descriptive statistics, the first four population moments include center, spread, skewness, and kurtosis or peakedness of a distribution. In this article, I am explaining the third and fourth population moments, the skewness and the kurtosis, and how to calculate them. Mean uses the values on the first degree in the calculation; therefore, it is the first population moment. Standard deviation uses the squared values and is therefore the second population moment. Read more