Business Intelligence Mastery with SQL and Tableau [2-in-1]

Celebrate reaching the milestone in business intelligence mastery with SQL and Tableau, joining the top 50% of learners and staying motivated to complete the course.

Create and connect a test database in pgadmin, then design tables for customers, products, and transactions using create table syntax with data types and primary/foreign keys.

Build a classroom database and a science class table with enrollment number, name, and signs marks using sql in the query tool, guided by practice exercises.

Learn to insert data into the customer table using insert into, with optional column names and correct value ordering, including single and multi-row inserts and handling not null constraints.

Import data from files into a table using the copy command in Postgres. Specify the table, columns, file location, delimiter, and file type (csv or text) with header handling.

Learn to retrieve data from the customer table using the select command, selecting specific columns or all columns with a wildcard, and view the resulting records.

Practice SQL select and where to filter student scores, retrieving names above 60, data for scores between 35 and 60 marks, and the remaining records using logical operators.

Master how to use the alter table command to reshape a table by adding, deleting, modifying, or renaming columns, managing constraints and indexes, with pgadmin examples.

Apply and remove constraints on SQL tables using alter table, including not null and check constraints. Demonstrate adding primary keys and foreign keys, and observe constraint enforcement during inserts.

Update Popeye's science class score from 33 to 45. Delete Rob's row and alter the table to rename the column from name to student_name.

Create the supermarket database by building customer, product, and sales tables from CSV files and loading data with PostgreSQL's copy command. Define primary keys and verify data.

Back up your database into a tar file, then restore it after accidentally dropping the science class table, mastering backup and restoration workflows.

Explore the like condition in sql for pattern matching with wildcards, using percent and underscore to filter strings by start or end, and not like, distinct, and escape character.

Apply SQL operators in where clauses to filter distinct cities in the north or east regions, select sales orders between 100 and 500, and find customers with four-character last names.

Master the order by command to sort query results, using ascending or descending order, multiple columns, and column numbers, for strings and integers, with optional where clauses.

Limit the number of rows returned by a query with the limit statement, using order by to show the top eight oldest customers and the ten youngest ones.

Sort the result set by discount in descending order to show orders with positive discounts, placing the maximum discount at the top and limit to the top ten orders.

Explore aggregate functions in SQL, focusing on count, sum, average, min, and max; learn counting non-null values, using where clauses, aliases, and distinct to analyze sales data.

Explore the avg function to compute a column’s mean with select avg(column) from table, illustrated by average customer age and average commission values.

Learn how to use min and max functions in SQL to find the lowest and highest sales within a date range, with practical examples from June 2015.

Apply aggregate functions to sum sales, count North region customers aged 20–30, and determine the average age in the East region plus min and max ages in Philadelphia.

Explore how the having clause filters groups by applying conditions to aggregate functions, contrasting it with the where clause that filters non-aggregates, through practical examples.

Learn to use case expression as a conditional expression to categorize data with when-then-else-end, aliasing the result as age category.