1z0-061: Oracle Database 12c: SQL Fundamentals certification video training course by prepaway along with practice test questions and answers, study guide and exam dumps provides the ultimate training package to help you pass.

Oracle 1Z0-061 Exam Prep: SQL Fundamentals for Oracle Database 12c

Introduction to the Course

The Oracle 1Z0-061 SQL Fundamentals Exam is one of the most important certifications for anyone starting their journey into Oracle Database technology. This course is designed to give you a complete training path for preparing and mastering SQL concepts, relational database design, and Oracle 12c fundamentals. The purpose of this training is to not only prepare you for the exam but also to help you develop practical skills that are essential for database management and SQL development.

Why This Exam Matters

The 1Z0-061 certification validates your foundational knowledge of Oracle SQL and Oracle Database 12c. Organizations rely heavily on Oracle databases to store, manage, and secure their data. By passing this exam, you demonstrate to employers and clients that you understand the basics of SQL, can work with queries, and can perform essential database operations confidently. This certification is often the first step toward advanced Oracle certifications and a successful database career.

Course Goals

This course is designed with specific goals in mind. The first goal is to ensure you fully understand SQL concepts. The second goal is to build confidence in writing queries, creating tables, and managing data. The third goal is to help you understand relational database structures and how Oracle implements them. By the end of the course, you should be prepared to take the Oracle 1Z0-061 exam with confidence and apply the knowledge directly in real-world database projects.

Who This Course is For

This course is for anyone new to Oracle databases and SQL. It is ideal for students who want to build a strong foundation in relational database management. It is also suitable for IT professionals who want to expand their career into database administration or development. Business analysts and data professionals who need to query databases will also find this course highly valuable. If you are planning to pursue further Oracle certifications, this training is the best starting point.

No Prior Experience Required

One of the benefits of this course is that no prior Oracle experience is needed. If you are completely new to SQL and databases, you can still take this course. The lessons start from the basics and build up gradually to more advanced topics. All you need is the willingness to learn, practice consistently, and stay dedicated to the training process.

Course Requirements

Although prior experience is not required, there are a few technical and personal requirements for success. You should have access to a computer with the Oracle Database 12c software installed or the Oracle SQL Developer tool. A reliable internet connection is needed if you plan to use Oracle’s cloud-based learning environments. You should also have at least a basic understanding of computers and file systems. A good amount of discipline, motivation, and focus is necessary to complete the course and prepare for the exam.

Course Structure

This training is divided into five main parts. Each part is structured to cover different aspects of SQL and the exam objectives. The first part covers the course overview and foundational topics. The second part covers SQL queries in detail. The third part covers data manipulation and functions. The fourth part focuses on schema objects, constraints, and advanced SQL concepts. The fifth part focuses on exam strategies, practice tests, and real-world applications. Each part contains explanations, examples, and exercises designed to reinforce learning.

Exam Details

The Oracle 1Z0-061 exam is a multiple-choice test that evaluates your ability to work with SQL in the Oracle 12c environment. It includes questions on retrieving data using SELECT statements, using conversion and aggregation functions, managing tables, and understanding constraints. The exam typically consists of around seventy to eighty questions, and you must score above sixty-five percent to pass. Time management during the exam is critical, and this course will help you practice answering questions efficiently.

Learning Outcomes

After completing this course, you will have a strong foundation in Oracle SQL. You will be able to write SQL queries to retrieve and manipulate data, create and modify database structures, and understand relational database principles. You will also gain confidence in approaching the exam with a clear strategy. Beyond the exam, you will have practical skills that can be applied in database administration, development, and data analysis roles.

Importance of SQL in Career Growth

SQL is one of the most in-demand skills across IT and business industries. Almost every company, regardless of size, relies on databases to manage critical information. SQL is the language used to communicate with these databases. By mastering SQL, you open doors to roles such as database administrator, data analyst, software developer, and business intelligence professional. This certification demonstrates your readiness to work with one of the most trusted database systems in the world.

Foundation of Relational Databases

Before diving into SQL, it is important to understand relational databases. A relational database stores data in tables that are connected by relationships. Each table consists of rows and columns, where columns define the attributes and rows represent the data records. Oracle Database 12c uses relational models to structure and organize data. This course will introduce you to the basic principles of database design and explain why relational databases are so widely used in the industry.

Understanding SQL as a Language

SQL stands for Structured Query Language. It is the language used to interact with relational databases. SQL allows you to retrieve information, update records, insert data, and delete unnecessary information. It also allows you to create and modify tables, define relationships, and enforce constraints to ensure data accuracy. Oracle’s implementation of SQL is industry standard, and understanding it gives you the ability to work with almost any relational database system.

Hands-On Learning

This course is designed to be practical. While you will study theoretical concepts, you will also apply them directly in hands-on exercises. You will practice writing SQL queries in Oracle SQL Developer or other tools connected to Oracle Database 12c. Each exercise is carefully designed to reflect real-world scenarios. By practicing regularly, you will not only prepare for the exam but also build lasting skills.

Building Confidence for the Exam

One of the biggest challenges in certification exams is exam anxiety. Many students feel nervous when faced with multiple-choice questions under time pressure. This course addresses this by including practice sessions, mock tests, and question analysis. You will learn how to break down questions, identify keywords, and eliminate incorrect choices. Over time, your confidence will grow, and you will be fully prepared on exam day.

Introduction to SQL Queries

SQL queries are the foundation of working with relational databases. A query allows you to communicate with the database and extract meaningful information from stored data. In Oracle Database, SQL queries are executed using the SELECT statement, which is one of the most important commands you will master. This part of the course focuses on understanding query structure, building efficient SELECT statements, and applying conditions to filter and retrieve the exact data you need.

Understanding the SELECT Statement

The SELECT statement is the most commonly used command in SQL. It allows you to retrieve data from one or more tables. A simple SELECT statement consists of a list of columns and the table from which the data is retrieved. The basic structure is SELECT column_name FROM table_name. You can retrieve all columns by using an asterisk, such as SELECT * FROM table_name. Although retrieving all columns is convenient, best practice recommends specifying only the columns you need to make queries more efficient and easier to read.

Retrieving Specific Columns

When working with large databases, it is often unnecessary to retrieve every column. Instead, you can choose specific columns to keep queries optimized. For example, if a table contains employee information with many columns but you only need the employee name and salary, you can write SELECT employee_name, salary FROM employees. This approach makes queries clearer and results easier to analyze.

Using Aliases in Queries

Aliases allow you to give temporary names to columns or tables in your query results. This makes the output more readable, especially when working with long or complex column names. For example, SELECT employee_name AS name, salary AS monthly_salary FROM employees will display the output with the column headers name and monthly_salary instead of the original names. Aliases can also be used for tables when joining multiple tables together.

Filtering Data with WHERE Clause

Not all the data in a table is relevant to every query. The WHERE clause allows you to filter rows based on conditions. For example, SELECT employee_name, salary FROM employees WHERE salary > 5000 retrieves only those employees whose salary is greater than 5000. The WHERE clause supports operators like equal to, greater than, less than, not equal, and between. Using conditions effectively is essential to narrowing down large datasets to only what you need.

Working with Comparison Operators

Comparison operators are used to define conditions in a WHERE clause. These operators include = for equality, <> or != for inequality, > and < for greater or lesser comparisons, and BETWEEN for range-based conditions. An example is SELECT employee_name FROM employees WHERE hire_date BETWEEN '01-JAN-2010' AND '31-DEC-2015'. This retrieves employees hired during that date range.

Using Logical Operators

Logical operators allow you to combine multiple conditions in a WHERE clause. The main logical operators are AND, OR, and NOT. For example, SELECT employee_name, salary FROM employees WHERE department_id = 10 AND salary > 3000 retrieves employees from department 10 with salaries above 3000. OR expands conditions to include multiple possibilities, while NOT excludes rows that meet certain conditions.

Understanding NULL Values

NULL represents missing or unknown data in a database. It is important to understand how to work with NULL values in queries. Using = or != does not work with NULL, because NULL is not considered equal or unequal to anything. Instead, the IS NULL or IS NOT NULL operators are used. For example, SELECT employee_name FROM employees WHERE manager_id IS NULL retrieves employees without a manager.

Sorting Data with ORDER BY

When retrieving data, the order in which results appear can be controlled using the ORDER BY clause. By default, rows are not returned in any specific order. You can sort data in ascending order using ORDER BY column_name ASC or descending order using ORDER BY column_name DESC. For example, SELECT employee_name, salary FROM employees ORDER BY salary DESC returns employees sorted by salary from highest to lowest. Multiple columns can be used in sorting, such as ordering by department first and salary second.

Limiting Results with ROWNUM and FETCH

Sometimes you may not need the entire result set. Oracle allows you to limit the number of rows returned using ROWNUM or the FETCH clause. For example, SELECT employee_name FROM employees WHERE ROWNUM <= 10 returns only the first ten rows from the result set. The FETCH FIRST n ROWS ONLY clause can also be used for similar purposes and provides more flexibility in modern Oracle versions.

Using DISTINCT to Remove Duplicates

When retrieving data, you may encounter duplicate rows in the result set. The DISTINCT keyword removes duplicates, ensuring only unique values appear. For example, SELECT DISTINCT department_id FROM employees returns each department_id only once. Be careful when using DISTINCT with multiple columns, as it considers the combination of values across those columns.

Concatenating Columns in Queries

In some cases, you may want to combine multiple column values into one output. Oracle allows concatenation using the double pipe symbol. For example, SELECT first_name || ' ' || last_name AS full_name FROM employees concatenates the first and last names into one column called full_name. Concatenation is often useful in creating meaningful output that combines different pieces of data.

Using Arithmetic Expressions in Queries

Oracle SQL allows you to perform arithmetic operations within queries. Operators such as +, -, *, and / can be applied to numeric columns. For example, SELECT employee_name, salary * 12 AS annual_salary FROM employees calculates yearly salary by multiplying monthly salary by twelve. Arithmetic expressions can also be combined with functions to create powerful calculations in your queries.

Understanding Operator Precedence

When working with multiple operators in a query, it is important to understand operator precedence. Multiplication and division are performed before addition and subtraction. Parentheses can be used to change the order of evaluation. For example, SELECT 100 + 20 * 5 returns 200 because multiplication happens first, while SELECT (100 + 20) * 5 returns 600. Using parentheses is a good practice to avoid confusion and errors in query results.

Working with Character Strings

Character strings in SQL are enclosed in single quotes. You can use string comparison in the WHERE clause, such as SELECT employee_name FROM employees WHERE department = 'Sales'. Oracle also supports functions for manipulating strings, including functions to change case, extract substrings, and replace text. These functions are useful in cleaning and transforming textual data during retrieval.

Pattern Matching with LIKE

The LIKE operator allows you to search for patterns within strings. It uses wildcards such as the percent symbol for multiple characters and the underscore for a single character. For example, SELECT employee_name FROM employees WHERE employee_name LIKE 'A%' returns names beginning with the letter A. Similarly, SELECT employee_name FROM employees WHERE employee_name LIKE '_n%' retrieves names where the second character is n. Pattern matching is valuable when working with textual searches.

Using IN and NOT IN Operators

The IN operator allows you to specify multiple possible values in a condition. For example, SELECT employee_name FROM employees WHERE department_id IN (10, 20, 30) retrieves employees in those departments. The NOT IN operator excludes values from the result. These operators simplify queries compared to writing multiple OR conditions. However, you must be careful when NULL values are involved, as they can affect results in unexpected ways.

Understanding Subqueries

Subqueries are queries within other queries. They allow you to build dynamic conditions based on results from another query. For example, SELECT employee_name FROM employees WHERE salary > (SELECT AVG(salary) FROM employees) retrieves employees earning above the average salary. Subqueries can be nested in the WHERE, FROM, or SELECT clauses. They are a powerful way to make queries flexible and responsive to data.

Single Row Subqueries

A single row subquery returns exactly one row of data. It is often used with comparison operators. For example, SELECT employee_name FROM employees WHERE salary = (SELECT MAX(salary) FROM employees) retrieves the employee with the highest salary. Single row subqueries are straightforward and often used to compare one value to a calculated or aggregated result.

Multiple Row Subqueries

A multiple row subquery returns more than one row. It is often used with operators like IN, ANY, and ALL. For example, SELECT employee_name FROM employees WHERE salary IN (SELECT salary FROM employees WHERE department_id = 10) retrieves employees with the same salary as those in department 10. Multiple row subqueries allow comparisons across groups of data.

Correlated Subqueries

A correlated subquery references columns from the outer query. This means the subquery is executed for each row in the outer query. For example, SELECT employee_name FROM employees e WHERE salary > (SELECT AVG(salary) FROM employees WHERE department_id = e.department_id) compares each employee’s salary to the average salary of their department. Correlated subqueries can be powerful but may impact performance due to repeated execution.

Inline Views

An inline view is a subquery in the FROM clause that acts like a temporary table. For example, SELECT department_id, AVG(salary) FROM (SELECT * FROM employees WHERE job_id = 'SA_REP') GROUP BY department_id calculates department averages for sales representatives only. Inline views allow you to simplify complex queries by breaking them into smaller, manageable pieces.

Importance of Query Optimization

As databases grow, query performance becomes critical. Writing efficient queries ensures faster results and less strain on the system. Best practices include selecting only necessary columns, filtering rows early, avoiding unnecessary DISTINCT usage, and indexing frequently used columns. Understanding execution plans and optimizing subqueries or joins is essential for advanced SQL mastery.

Introduction to Data Manipulation

Data manipulation is one of the most essential tasks in SQL. Once a database has been created and tables are defined, users need to add new information, update existing records, and remove data that is no longer required. These tasks are handled through the Data Manipulation Language, which includes INSERT, UPDATE, DELETE, and MERGE statements. In addition, Oracle provides transaction control commands such as COMMIT, ROLLBACK, and SAVEPOINT that ensure data consistency. Understanding how to manipulate data is a crucial step toward becoming proficient in SQL and preparing for the exam.

INSERT Statement Overview

The INSERT command allows you to add new rows of data into a table. It can be used in two primary ways: inserting a single row of values or inserting multiple rows returned by a query. The basic syntax for inserting one row is INSERT INTO table_name (column1, column2) VALUES (value1, value2). You must supply values for mandatory columns, while optional columns may be left out or filled with NULL values.

Inserting Data into All Columns

When you insert values into all columns of a table, you do not need to specify the column list if you provide values for every column in the correct order. For example, INSERT INTO employees VALUES (101, 'John', 'Smith', 5000, 'IT') inserts a new employee into all columns. Although this method is convenient, best practice is to list columns explicitly to avoid errors if the table structure changes.

Inserting Data into Specific Columns

If you only want to insert values into certain columns, you must specify those columns in the INSERT statement. For example, INSERT INTO employees (employee_id, first_name, last_name) VALUES (102, 'Jane', 'Brown') fills only the specified columns, while other columns either remain NULL or use default values. This approach provides flexibility when working with tables that contain many optional fields.

Inserting Data with Subqueries

In addition to inserting a single row, you can use a subquery to insert multiple rows at once. For example, INSERT INTO sales_archive SELECT * FROM sales WHERE sale_date < '01-JAN-2020' copies older sales data into an archive table. This method is powerful for bulk data movement and avoids having to insert rows one at a time.

UPDATE Statement Overview

The UPDATE command modifies existing data in a table. It is used to change values in one or more columns for rows that meet specific conditions. The general syntax is UPDATE table_name SET column_name = value WHERE condition. Without a WHERE clause, all rows in the table will be updated, so caution is required.

Updating Specific Columns

You can update one or multiple columns in a single UPDATE statement. For example, UPDATE employees SET salary = salary * 1.10 WHERE department_id = 10 increases salaries by ten percent for all employees in department 10. When updating multiple columns, you separate assignments with commas.

Using Subqueries in Updates

Subqueries can be used in UPDATE statements to make changes based on values from other tables. For example, UPDATE employees SET department_id = (SELECT department_id FROM departments WHERE department_name = 'Marketing') WHERE employee_id = 105 moves an employee to the marketing department by referencing a value from the departments table.

DELETE Statement Overview

The DELETE command removes rows from a table. The basic syntax is DELETE FROM table_name WHERE condition. If the WHERE clause is omitted, all rows in the table will be deleted. Because of its irreversible nature once committed, DELETE should be used carefully.

Deleting Specific Rows

DELETE is commonly used to remove rows that match certain criteria. For example, DELETE FROM employees WHERE department_id = 20 removes all employees from department 20. By controlling conditions, you can ensure only the intended rows are deleted.

Deleting All Rows with TRUNCATE

Although DELETE without a WHERE clause removes all rows, Oracle also provides the TRUNCATE command. TRUNCATE TABLE employees deletes all rows quickly by deallocating storage, and it cannot be rolled back. Unlike DELETE, TRUNCATE resets storage space and performs faster on large tables.

MERGE Statement Overview

The MERGE statement is a powerful command that allows you to insert, update, or delete data in a target table based on a source table. It is also known as an UPSERT operation. For example, MERGE INTO employees e USING new_employees n ON (e.employee_id = n.employee_id) WHEN MATCHED THEN UPDATE SET e.salary = n.salary WHEN NOT MATCHED THEN INSERT (employee_id, name, salary) VALUES (n.employee_id, n.name, n.salary) ensures employee records are synchronized between two tables.

Introduction to Transactions

Every data manipulation statement occurs within a transaction. A transaction is a logical unit of work that may consist of one or more SQL statements. Transactions ensure that changes to data are consistent, reliable, and recoverable. By default, Oracle treats data manipulation as part of an ongoing transaction until you explicitly save or discard changes.

Using COMMIT

The COMMIT command permanently saves changes made by data manipulation statements. Once committed, changes cannot be undone. For example, after inserting new employees, issuing COMMIT makes those changes permanent in the database.

Using ROLLBACK

If you make a mistake during data manipulation, you can use ROLLBACK to undo changes since the last commit. For example, if you accidentally delete rows without intending to, issuing ROLLBACK will restore the data as long as you have not committed. ROLLBACK is an essential tool for preventing permanent mistakes.

Using SAVEPOINT

A SAVEPOINT is a marker within a transaction that allows partial rollbacks. For example, SAVEPOINT step1 creates a restore point, and if you later issue ROLLBACK TO step1, only changes after that savepoint are undone. SAVEPOINT is particularly useful in long transactions with multiple steps.

SQL Functions Overview

SQL functions extend the power of queries by performing operations on data values. Functions can be categorized into single-row functions and multiple-row functions. Single-row functions operate on individual values and return one result per row, while multiple-row functions operate on groups of rows and return a single result per group. Functions are essential in transforming and analyzing data during retrieval.

Character Functions for Data Transformation

Oracle provides a wide range of character functions. The UPPER and LOWER functions convert text to uppercase and lowercase. INITCAP capitalizes the first letter of each word. LENGTH returns the number of characters in a string. SUBSTR extracts a substring from a string, while INSTR finds the position of a substring. For example, SELECT UPPER(employee_name) FROM employees converts all names to uppercase.

Character Functions for Modification

The REPLACE function substitutes occurrences of a substring with another string. The TRIM function removes leading and trailing characters, typically spaces. The LPAD and RPAD functions pad a string with characters on the left or right to reach a certain length. These functions are helpful in formatting and cleaning textual data.

Numeric Functions for Calculations

Oracle includes numeric functions for mathematical calculations. The ROUND function rounds a number to a specified number of decimal places. The TRUNC function truncates a number without rounding. The MOD function returns the remainder of a division. ABS returns the absolute value of a number. These functions are widely used in financial, statistical, and scientific applications.

Date Functions for Time Calculations

Dates are an important data type in Oracle. The SYSDATE function returns the current system date and time. The ADD_MONTHS function adds a specified number of months to a date. The MONTHS_BETWEEN function calculates the difference in months between two dates. The NEXT_DAY function returns the next occurrence of a specified weekday. For example, SELECT SYSDATE FROM dual retrieves today’s date.

Conversion Functions

Conversion functions allow you to change data from one type to another. The TO_CHAR function converts numbers or dates to strings, useful for formatting. The TO_NUMBER function converts character strings to numeric values. The TO_DATE function converts character strings into dates. For example, SELECT TO_CHAR(SYSDATE, 'DD-MON-YYYY') FROM dual formats the current date.

General Functions

Oracle provides general functions such as NVL, NVL2, COALESCE, and NULLIF. These functions are particularly important when working with NULL values. NVL replaces NULL with a specified value. NVL2 allows different results depending on whether a value is NULL or not. COALESCE returns the first non-NULL value from a list. NULLIF compares two values and returns NULL if they are equal.

Group Functions Overview

Group functions, also known as aggregate functions, operate on sets of rows and return a single value. These include SUM, AVG, COUNT, MAX, and MIN. For example, SELECT AVG(salary) FROM employees calculates the average salary. Group functions are essential in summarizing large datasets and performing statistical analysis.

Grouping Data with GROUP BY

The GROUP BY clause groups rows that share the same values in specified columns, allowing group functions to be applied to each group. For example, SELECT department_id, AVG(salary) FROM employees GROUP BY department_id calculates the average salary per department. GROUP BY is one of the most powerful features of SQL.

Filtering Groups with HAVING

While the WHERE clause filters individual rows, the HAVING clause filters groups after aggregation. For example, SELECT department_id, AVG(salary) FROM employees GROUP BY department_id HAVING AVG(salary) > 5000 returns departments where the average salary exceeds 5000. HAVING is always used with GROUP BY and allows refined control over aggregated results.

Nesting Functions

Functions in Oracle can be nested within one another to perform complex operations. For example, SELECT UPPER(SUBSTR(employee_name, 1, 5)) FROM employees converts the first five characters of each name to uppercase. By nesting functions, you can chain multiple transformations together in one query.

Importance of Practice with Functions

Functions are a critical part of SQL mastery. The more you practice, the more natural it becomes to apply the right function in the right context. This course includes exercises where you will apply character, numeric, date, and group functions in real scenarios. By practicing regularly, you will not only be prepared for exam questions but also ready to solve real business challenges.

Prepaway's 1z0-061: Oracle Database 12c: SQL Fundamentals video training course for passing certification exams is the only solution which you need.