Are you looking for a job where Advanced SQL is a requirement? Or do you work in an organization that requires data analysis of an immense amount of data?
Either way, it's possible that you already know the basics of the SQL programming language. But SQL is dynamic and broad, and you may not master it in a day. If you know the basic SQL, it is time to take them to the next level and learn the advanced SQL. Basic SQL skills allow you to work easily as a data analyst while selecting data, grouping it, and ordering it.
But advanced SQL involves more than this.
So, what is advanced SQL? How long can you take to learn advanced SQL? How does advancing your skills help you to handle advanced queries?
What is Advanced SQL?
SQL or Standard Query Language is a standard language used while working with relational databases.
You can use the SQL programming language to search, enter, modify and delete data from a database. The more time you spend using the SQL on the database, the more effective and creative you become.
For a web developer, the use of SQL could be limited to inserting, modifying, and deleting data from a database. However, there is more that you can do using the language.
For data analysts, data engineers, and data scientists, SQL language comes in handy in helping you analyze an enormous amount of data. You can utilize the SQL language to retrieve data that will provide solutions to your business needs.
So, why is SQL popular among data analysts?
They create extensive trails of data daily as they use various applications, sites, and social platforms. Companies eventually mine the data to understand the business performance, such as customer satisfaction.
However, a large amount of data is useless if it is not analyzed. This is where data analysis comes in.
Data analysts use their advanced SQL skills and other programming languages to organize and analyze the data. They draw correlations that company management boards and executives can use to draw business insights.
Such insights can include identifying potentially profitable areas or where the business is experiencing revenue loss.
As data increasingly becomes vital while making business decisions, so is the demand for people with advanced SQL skills.
Thus, it will be an excellent idea to upscale your SQL skills from the basics and work your way to becoming a master in the language.
How Long Can I Learn SQL Skills and its User Defined Functions?
Pinpointing the exact time it will take you to learn advanced SQL and its functions is not easy as it depends on various factors.
For instance, how easy is it for you to grasp new knowledge? It all depends on whether you have other engagements competing for your time apart from SQL (check out 'Are Coursera Certificates Worth It?'). Plus, some people have better retention abilities than others, which makes them learn faster.
According to experienced SQL programmers, it can take you a few weeks to months to master SQL basics. Also, just like learning any other language, it will take you longer to master advanced SQL. It is important to keep practicing, requires a lot of commitment and practice to become proficient. On a related note, Udemy’s platform and learning system provide the best courses available online - see 'Are Udemy Courses Worth It?' post.
When you start learning, you'll realize that the more you know about SQL, the more you don't know. SQL is a broad programming language that involves many functions, including system-defined functions and other complex user-defined functions in SQL.
As you immerse yourself in learning the language, you'll realize that there is so much to learn about SQL. Therefore, it will take time.
Reasons to Master SQL
Before you invest your time and money to learn advanced SQL and enroll yourself in the best online SQL courses in order for you to master it, it's vital to know if it's worthwhile. Here are a few reasons why you should focus on Advanced SQL and conquer databases:
- SQL is a powerful tool for troubleshooting: Advanced SQL makes it easy to troubleshoot any issues that may arise. Such issues can include simple syntax errors that the program will highlight. You can correct the problem as you write the program instead of coming back to fix it.
- SQL is versatile: As the world moves more into computing, it's becoming easier to use SQL in various fields. Data analysts are now required to analyze data in various fields, including finance, data analytics firms, social media enterprises, scientific computing, etc. Sales teams can use SQL to decide on tactics that work while scientists use the programming language to pore over data from their lab. With SQL programming language, combining data from various sources becomes easy. You can make use of SQL's UNION operators to choose databases that need to be combined.
Advanced SQL - Structured Query Language
Here, we'll look at how you can use Structured Query Language to accomplish more complex operations. We’ll also take a look and list down a set of some of the advanced and useful SQL keywords.
SQL Inline View
For instance, an Inline view in advanced SQL is a statement in the "FROM" clause. A view is a virtual table that comes with a table's characteristics but doesn't hold any data. In an Inline view, you don't specify table name (s) after the "FROM" clause. The source of the data comes from the inline view.
An inline view can also be referred to as a derived table.
Syntax : the syntax for an online view is SELECT"column_name" FROM (inline view).
For example, imagine we have two tables. The first one is a user_address that maps the users to a zip code. The second is a user_score that records the score of each user. How do you write the SQL query to find out the users who scored more than 200?
Using inline view, you can simplify the SQL as:
SELECTa2.ZIP_CODE,COUNT(a1.User_ID)
FROM
(SELECT User_ID,SUM(Score) FROM User_score GROUP BY User_ID HAVING SUM(Score) >200) a1.User_Address a2
WHEREa1.User_ID =a2.User_ID
GROUP BY a2.ZIP_CODE;
The bolded code represents the inline view.
SQL UNION
The SQL UNION query helps to combine the results of two queries and helps to remove duplicates. With SQL UNION, only unique values are returned.
The syntax of SQL UNION is as follows:
[SQL Statement 1]
UNION
[SQL Statement 2]
SQL UNION ALL
SQL UNION combines the results of two queries without removing duplicates.
The syntax of SQL UNION ALL is as follows:
[SQL Statement 1]
UNION ALL
[SQL Statement 2]:
SQL INTERSECT
The SQL INTERSECT command combines the results of two statements and returns only data present in the two statements.
INTERSECT can be looked at as an AND command, while UNION and UNION ALL can be seen as an OR command.
The syntax for INTERSECT is:
[SQL Statement 1]
INTERSECT
[SQL Statement 2]
For INTERSECT to work, the columns selected as [SQL Statement 1] and [SQL Statement 2] need to be of the same data type.
SQL MINUS
The MINUS command in SQL works on two statements. It takes the results in the first statement and substracts the one in the second statement. If the second SQL statement results are not present in the first statement, such data is ignored.
The following is the syntax for MINUS:
[SQL Statement1]
MINUS
[SQL Statement 2];
The first and second statement results should be of the same data type for the MINUS command to work.
SQL LIMIT
The LIMIT clause is present in MySQL, and it restricts the number of results returned from a statement.
The syntax for the LIMIT is:
[SQL Statement 1]
LIMIT [N];
[N] represents the number of commands to be returned. The ORDER BY clause should be included in the SQL statement. Without it, the results you get will depend on what the database default is.
SQL TOP
The SQL TOP command restricts the number of results returned from a Microsoft SQL Server.
The SQL TOP syntax is as follows:
SELECT TOP [TOP Argument] "column_name"
FROM "table_name"
The argument can be in two types including:
[N]: the first N records are returned
[M] percent: number of records corresponding to M% of all records are returned
SQL SUBQUERY
An SQL SUBQUERY statement has another SQL query embedded in the HAVING or WHERE clause.
The syntax for SQL SUBQUERY when the embedded statement is part of a WHERE clause is:
SELECT "column_name1"
FROM "table_name1"
WHERE "column_name2" [Comparison Operator]
(SELECT "column_name3"
FROM "table_name2
WHERE "condition");
Comparison operator can be equality operators such as =, <, >, <=, >=. You can also use a text operator such as LIKE. The bolded portion is the inner query.
SQL EXISTS
EXISTS is a Boolean operator used to test whether the inner query in a subquery returns any row. If it returns, the outer query responds; if it doesn't, the outer query doesn't execute.
The syntax for EXISTS is as follows:
SELECT "column_name1"
FROM "table_name1"
WHERE EXISTS
(SELECT *
FROM "table_name2"
WHERE "condition");
Instead of *, you can use one or two columns in the inner query, and you"ll get identical effects.
SQL CASE
The CASE command is used to provide the if-then-else type of logic.
The syntax for a simple CASE expression is:
SELECT CASE ("column_name")
WHEN "value1" THEN "result1"
WHEN "value2" THEN "result2"
...
[ELSE "resultN"]
END
FROM "table_name";
SQL AUTO_INCREMENT
The command is used in MYSQL to develop a numerical primary key value for each additional row of data.
The syntax for AUTO_INCREMENT is:
CREATE TABLE TABLE_NAME
(PRIMARY_KEY_COLUMN INT NOT NULL AUTO_INCREMENT
...
PRIMARY KEY (PRIMARY_KEY_COLUMN));
SQL IDENTITY
The IDENTITY is used in Microsoft SQL Server to automatically insert numerical primary key values to a table as new data is inserted. It is similar to the AUTOINCREMENT command in MYSQL.
The syntax for identity is:
CREATE TABLE TABLE_NAME
(PRIMARY_KEY_COLUMN INT PRIMARY KEY IDENTITY ( [Initial_Value], [Interval] ),
...);
The [initial_value] is the primary key's first value, and [interval] refers to two consecutive identity values. If you don't specify any [initial_value] or [interval], the default for both is 1.
Conclusion
There you have it. A detailed guide of what advanced SQL is and how long it will take to learn the language. We have also highlighted why you may want to pursue advanced SQL and some advanced SQL keywords that you will come across along the way.
