Here are five popular SQL queries frequently used in data analysis. 1. SELECT with Aggregations Summarize data by calculating aggregates like counts, sums, averages, etc. SELECT department, COUNT(*) as employee_count, AVG(salary) as average_salary FROM employees GROUP BY department; 2. JOIN Operations  Combine data from multiple tables based on a related column. SELECT e.employee_id, e.name, d.department_name FROM employees e JOIN departments d ON e.department_id = d.department_id; 3. WHERE Clause for Filtering Filter records based on specified conditions. SELECT * FROM sales WHERE sale_date BETWEEN '2024-01-01' AND '2024-12-31'   AND amount > 1000; 4. ORDER BY Clause for Sorting Sort results in ascending or descending order based on one or more columns. SELECT product_name, price FROM products ORDER BY price DESC; 5. GROUP BY with HAVING Clause Group records and apply conditions to the aggregated results. SELECT department, SUM(salary) as total_salaries FROM employ

SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences. Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle) SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum  FROM your_table; This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column. Using Subqueries (e.g., MySQL, SQLite): SELECT t1.id, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON t1.id >= t2.id GROUP BY t1.id, t1.value ORDER BY t1.id; This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than or

SQL query runs faster when you write it in a specific method. You can say it as tuning. There are five tuning tips: List of Performance Tuning Tips use index columns, use group by, avoid duplicate column in SELECT & Where, use Left Joins use a co-related subquery. Five top SQL Query Performance Tuning Tips SQL Performance Tuning Tip: 01 Use  indexes in the where clause of SQL . Let me elaborate more on that. Be sure the columns that you are using in the WHERE clause should be already part of the Index columns of that database Table. An example SQL Query: SELECT *  FROM emp_sal_nonppi WHERE dob <= 2017-08-01; SQL Performance Tuning Tip: 02 Use GROUP BY . Some people use a  DISTINCT clause to eliminate duplicates . You can achieve this by GROUP BY. An example SQL Query: SELECT E.empno, E.lastname FROM emp E,emp_projact EP WHERE E.empno = EP.empno GROUP BY E.empno, E.lastname; SQL Performance Tuning Tip: 03 Avoid using duplicates in the Query. Some people use the same col

SQL DATE function for all Developers. DATE Function is powerful in SQL. In SQL projects, people use this Function variety of ways. All projects depends in DATE, and without it there is no way of existing of project.  The Quick tour helps you use this function effectively.  You can learn Oracle SQL step by step for all Developers. Below is the list of SQL DATE functions SYSDATE - It returns current local DATE and Time CURRENT_DATE - Return local DATE and TIME and adjusted to current session Time Zone. ROUND (DATE) - Rounds to nearest DAY TRUNC (DATE) - Truncates Time MONTHS_BETWEEN(date1,date2) - Returns number of months between date1 and date2' LAST_DAY(DATE)- Returns last of the month ADD_MONTHS(date,integer_months) - Adds specified number of months to specified date. NEXT_DAY(date, day_of_week) - Returns to next day of the week that comes after the specified DATE Also Read   The Best SQL Book for all Developers.

There are three kinds of Views in SQL. The three views are Read-only, Force, and Updatable. Views real usage is to hide data. And you need to ensure base tables are present before you create a View. You can call views as logical tables. The advantage of Views is you can show only some of the fields of base tables. What is a View in SQL A view can be constructed with another view so it is called a nested view. You can create or replace an existing view A view can be created without having base tables. This is possible with the FORCE option. #1: Read-Only Views The standard syntax for the view is as follows: CREATE OR replace VIEW invoice_summary AS SELECT vendor_name count(*) AS invoice_count, SUM(invoice_total) AS invoice_total_sum FROM vendor JOIN invoices ON vendors.vendor_id*invoices.vendor_id GROUP BY vendor_name; Notes: You cannot update Read-only Views #2: Force Views CREATE FORCE VIEW products_list AS SELECT product_description, product_price FROM products;

SAMPLE PL/SQL CREATE TABLE dummy ( dummy_value VARCHAR2(1)); DECLARE -- Define local variable. my_string VARCHAR2(1) := ' '; my_number NUMBER; BEGIN -- Select a white space into a local variable. SELECT ' ' INTO my_string FROM dummy; -- Attempt to assign a single white space to a number. my_number := TO_NUMBER(my_string); EXCEPTION WHEN no_data_found THEN dbms_output.put_line('SELECT-INTO'||CHR(10)||SQLERRM); END; / Output and Error: The program returns the following output, which illustrates formatting user- defined exceptions.  The CHR(10) inserts a line return and provides a clean break between the program's SQLCODE and SQLERRM messages: RAISE my_error SQLCODE [1]  SQLERRM [User-Defined Exception]