Calculating product of values in a column in SQL and its business usecase

SQL supports most aggregate functions except one fundamental aggregation to calculate product of values in a column. If you are wondering what could be a scenario where you may have to calculate product of values in a column, here is a business scenario that demands it. Business Scenario: For the sake of brevity, let's say... Continue Reading →

Why is SQL one of the most powerful tools in the arsenal of an Analyst?

Out of information analysis, comes wisdom. It’s this information analysis that is one of the important reasons that created the need for storage of data. The world of databases was sprouted to address this need of data storage and many languages were born to interact and deal with the data stored in these databases. But... Continue Reading →

A White Paper – Solving Relational Division problem in SQL – The Analyst Way

Hi readers..!! Here I go posting a white paper on one of the classical and intellectually challenging problems that an analyst might come across. The paper is titled - "Understanding and Solving Relational Division problems in SQL - The Analyst way". Hope you enjoy reading this paper. Please leave your comments and suggestions, if any, here.... Continue Reading →

Complement Negation: SQL Design Pattern to solve a frequently occurring interesting business data analysis problem

Here is an interesting business data analysis problem that I have come across multiple times in the recent times. Since I have seen this problem surfacing multiple times and the solution boils down to the same technique, it becomes an SQL Design Pattern and I named this baby as "Complement Negation". Have shared the justification... Continue Reading →

Truncate time part from Datetime column or literal in Oracle SQL

I have shown how to truncate the time part from a datetime column value in SQL Server T-SQL in one of my previous posts here - Here is the same (how to truncate the time part from a datetime column value) in Oracle SQL: TRUNC(datetime_column) or TRUNC(datetime_expression) very straight forward...!! isn't it.. ? 🙂

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