
Work through exercise 3 solutions, selecting from band where name equals 'Icarus', then use year IS NULL with AND; avoid year = NULL, which returns no rows.
Explore data aggregation with count, group by, and where to compute row counts and group results by band_id and year using the album table.
Explore left outer joins to retain rows with no matches, using NULLs for missing band data, and see how where vs on clause affects results.
Explore solving sql exercises by counting Led Zeppelin albums per year using a calendar_year lookup. Apply left outer joins, group by year, and count(album_id) to show zero years.
Explore self joins to relate rows within the same table, using a music instrument hierarchy to show parent, grandparent, and child relationships with left outer joins.
Learn to query a music instruments hierarchy in a single table using self-joins across levels, left joins, and counts of non-null ids to identify the bottom of the hierarchy.
Explore cross joins, or cartesian joins, which pair every row from the first table with every row from the second when no join condition is specified.
Learn how except all (also called minus) subtracts rows from one query and how duplicates are retained or removed. Explore null values, not in, and coalesce effects on results.
Explore the intersect and intersect all operators to find common rows across queries, handle duplicates, and manage null values with cautious subqueries and coalesce considerations.
Overview of functions and operators in SQL, including logical and comparison operators, the like operator, mathematical operators, and concatenation ||; learn the most frequently used SQL functions.
Use update to modify existing rows, not add new ones, with syntax: update table set column = value where condition; you can also update from another table via a join.
The course has everything you need to start writing your own SQL queries.
Why learn SQL? Short answer is - if you know SQL well, you'll always be able to find a job! That's because it is used in a variety of different job roles:
- Data Analysts
- Data Scientists, Data Engineers
- Database / Datawarehouse Developers and Designers
- Software Quality Assurance Engineers
- And more!
The SQL language seems simple - and that's true. However, some topics can cause mistakes - things like NULL values, duplicate rows and missing rows, etc. This course covers the frequent mistakes, and how to avoid them.
You will learn SQL syntax applicable to most relational databases. In the practice exercises you will use PostgreSQL, but the knowledge is easily transferable to other databases: PostgreSQL, Oracle, Microsoft SQL Server, MySQL, Teradata and so on. The standard SQL is the same in all ANSI-compliant SQL databases.
Why this course? Because it was made based on the author's experience from the industry - so the course focuses on the topics and features that are really used on a day-to-day basis for data analysis.
Features:
- High-quality video lectures
- English subtitles (closed captions) hand-made for you (NOT auto-generated)
- Practice tests
- Practice exercises to test and enhance your knowledge (with explained solutions)
- And more!
I'll be happy to see you inside the course. Check out the free preview videos for more information!