RDBMS - SQL Course - Step by Step Guide to learn SQL

download and install oracle virtualbox on windows, meet prerequisites of 8–16 gb ram, 64-bit processor, and 500 gb disk, then run virtualbox.

Learn to download and install Ubuntu using Oracle VirtualBox, including prerequisites, VM creation, ISO selection, and Ubuntu installation.

Learn to install and configure MySQL on Ubuntu by updating repositories, upgrading packages, installing the MySQL server, setting a root password, and verifying with show databases.

Explore the difference between data and information, and understand data types like numeric, text, alpha-numeric, image, audio, and video, and see how data becomes meaningful information through processing.

Discover why data matters for future use, insights, patterns, and correlations, and how data drives personalization, opportunities, and technological advancement through informed business decisions.

Explore different ways of storing data, from lists and folders to hierarchical organization and tabular tables with columns like country, state, city, picture, and date for easy filtering.

Explore historical data storage systems from text files and spreadsheets to semi-structured JSON and XML, and discover how RDBMS emerged as a data storage solution.

Trace the evolution from flat files to the DBMS era and the rise of RDBMS, and learn the relational model and data independence.

Learn how a relational database management system stores, manages, queries, and retrieves data in a relational model, performs crud operations, and handles backups and access control.

Explore the database concept as a collection of related data and its metadata, organized in a structured format for optimized information management, retrieval, and insights in a relational database.

Discover the database components: relations, tables, domains, columns, tuples, rows, and how tables, entities, attributes, and records interrelate to store data.

Explore rdbms concepts by creating a database and a table in MySQL on Ubuntu, then insert and query data using commands like create database, use, show tables, insert, and select.

Discover core SQL data types, including string types, such as fixed-length chars and variable-length strings, binary data, numeric types like int, float, and decimal, and date and time types.

Explore data types through hands-on practice by creating a MySQL table, defining int, char, and date columns, describing the table schema, and inserting and querying rows.

Identify database objects such as tables, indexes, sequences, views, and synonyms, and learn how they store or reference data in relational databases, with vendor similarities and naming guidance.

Understand how indexes serve as lookup pointers that speed up row retrieval by locating data without disk scans. Create an index on a table column, illustrated using the cars example.

Learn how sequences, user-created database objects, generate unique integers for primary keys, with ascending or descending values and defined ranges. See auto_increment as MySQL's simple sequence alternative.

Learn how views act as virtual tables that derive a subset of columns from one or more tables, provide data access without storing data, and how to create a view.

Demonstrates creating views in MySQL by selecting columns from a single table and joining two tables to expose related data, while clarifying that views reference data rather than store it.

Learn how database design uses conceptual, logical, and physical models to plan, build, and maintain high‑performance data systems across RDBMS like Oracle, PostgreSQL, and MySQL.

Learn entity relationship modeling to create the conceptual view of a database and uncover design issues. Explore entities, attributes, relationships, and cardinality through ER diagrams that remain independent of RDBMS.

Explore ER diagram components with concrete university examples. Learn how entities, attributes, and relationships form diagrams, and how cardinality: one-to-one, one-to-many, and many-to-many shapes data models.

Analyze requirements and identify entities, attributes, relationships, and cardinalities to model a university database, including department, course, module, student, lecturer, and their many-to-many and one-to-many connections.

Explore keys in SQL and learn how primary, candidate, super, foreign, surrogate, and composite keys identify rows in a relation and establish table relationships.

Identify super keys as the set of one or more attributes that uniquely identify each record, possibly with extra attributes, before moving to candidate and primary keys.

Identify candidate keys as minimal, non-null sub-sets of super keys that uniquely identify a tuple; select a primary key from them, illustrated by ID, phone, or ID plus phone.

Define a primary key as the column that uniquely identifies each row in a table, using student id as the example, and show its declaration with non-null, non-duplicate rules.

Explore unique, alternate, composite, and surrogate keys in RDBMS, including when to use nulls, non-clustered indexes, and artificial keys to uniquely identify records.

discover how foreign keys connect tables in a relational database by linking a table's primary key to another table's column, ensuring matching data types and optional nullability.

Explore data integrity in databases, showing how constraints, data typing, and keys ensure accuracy, completeness, consistency, and regulatory compliance.

Explore domain integrity constraints within data integrity, focusing on check constraints that restrict value ranges in a column, such as salary greater than zero, enforced during inserts.

demonstrate the check constraint on the salary column in a MySQL database by creating an employee table and validating inserts. reject zero or negative salaries, while positive values insert.

Learn how to use a default constraint to insert a default value into a column, such as the current timestamp for an employee date, via create table or alter table.

Learn how the not null constraint enforces domain integrity by preventing null values in a column, illustrated with an employee table and create or alter table examples.

Understand how the unique constraint enforces domain integrity by preventing duplicate values across one or more columns, and compare it to the primary key with an employee table example.

Understand entity integrity by enforcing a primary key to prevent duplicates and not null values, and explore composite primary keys to uniquely identify records.

Explore entity integrity by building tables with primary key and composite primary key in MySQL, enforcing not null and uniqueness while preventing duplicates through hands-on examples.

Explore referential integrity constraints that enforce valid foreign key references to primary keys, preserve relationships between department and student tables, and keep data synchronized during updates.

Explore referential integrity with a two-table example, showing how a child table's foreign key references a parent table's primary key, handling nulls and enforcing valid department ids.

Explore normalization as a systematic approach to decompose tables, eliminate data redundancy, and prevent anomalies within the database design's conceptual, logical, and physical phases, covering first through Boyce-Codd normal form.

Explore the need for normalization with an employee data example, showing how splitting a single table into separate employee, address, and subordinates tables minimizes redundancy and enables joins.

An exploration of functional, transitive, and partial dependencies, using an employee table to show determinants and dependents and the role of candidate keys in normalization from 1NF to BCNF.

Master the first normal form in normalization by ensuring atomic, single-valued cell values in a table, using an employee data example to decompose multi-valued addresses into atomic fields.

Explain second normal form, requiring first normal form and every non-prime attribute to be fully dependent on the primary key, and decompose into student and project tables.

Discover how the third normal form extends second normal form by removing transitive dependencies and ensuring all determinants of non-key attributes are candidate keys, using a student–subject data split.

Explore Boyce-Codd normal form, requiring dependencies to have a superkey and a prime attribute; decompose relations into student and professor tables to achieve Boyce-Codd normal form.

Understand transactions as a single logical unit of work that reads or writes the database, illustrated by bank transfers, debits, and credits, and learn how properties ensure consistency during failures.

Explore the acid properties of database transactions, ensuring validity even during errors or power failures. Learn atomicity, consistency, isolation, and durability and how they guarantee reliable commits.

Learn atomicity as part of acid transactions: a bank transfer commits only if all steps succeed, otherwise the entire transaction aborts, leaving no partial updates.

Grasp how consistency preserves database correctness before and after a transaction by maintaining integrity constraints, as illustrated by a $100 transfer example.

Isolation ensures concurrent transactions occur independently, preventing database state inconsistencies. It hides uncommitted changes until a transaction commits, as shown in transfers between accounts.

Durability ensures that once a transaction completes, updates are written to the disk permanently, surviving system failures and guaranteeing lasting modifications within the database.

Introduction to SQL explains how structured query language stores, retrieves, and manages data in relational databases, offering high performance, high availability, security, scalability, and robust transactions.

Learn sql data definition language (ddl) concepts, including create, alter, and drop commands to build and modify databases and tables, with hands-on examples using a university database and students table.

Use rename as a DDL operation with alter table to rename database objects, including tables and columns, demonstrated by renaming student details to students and a column to first name.

explain drop and truncate in sql, show how drop removes a table with its data and structure, while truncate deletes only the data, keeping the table intact.

Learn how SQL comments improve readability and testing, covering single-line, multi-line, and inline comments, with hands-on MySQL examples showing how to comment out code and verify results.

Explore data manipulation language concepts by learning how to insert, update, and delete records. Use insert into, update with set and where, and delete from to modify table data.

Practice insert, update, and delete commands on Bliss Mars Academy's students table, including creating and dropping tables, inserting multiple records, updating row 10,002 to Bangalore, and deleting a record.

Master the three ways to insert data into tables: standalone inserts, loading from files, and inserting from other tables, and their key syntax.

Explore multiple data insertion methods in sql: standalone inserts with values, inserting into specific columns, loading data from files, and inserting from another table using select.

Explore data control language (DCL) and how grants and revokes manage user access and privileges for databases and tables within an RDBMS.

Learn to manage access in MySQL using data control language through hands-on examples of grant, revoke, and select privileges.

Explore transaction control language concepts, including commit, rollback, save point, and starting a transaction, to understand preserving or reverting SQL updates.

Practice TCL commands in MySQL hands-on, using transactions, auto commit control, and savepoints to manage updates, commits, and rollbacks.

Master data query language (dql) in sql by using the select statement to retrieve data from schema objects, with examples like select star from employee and applying where and limit.

Explore dql commands hands-on by creating an employee table, inserting data, and querying with select all, limited rows, and selective columns, including basic where filtering.

Learn that SQL keywords are not case sensitive, while database object names are. Write statements in one or multiple lines, avoid keyword abbreviations, and use indentation to improve readability.

Learn how SQL aliasing creates temporary names for tables and columns to simplify joins and subqueries, improving readability without changing the actual database.

Learn how to use distinct to find unique values and avoid duplicates in sql queries, illustrated with selecting distinct ages from an employee table.

Explore SQL operators as reserved words or characters used in statements like where clauses to perform arithmetic, comparison, logical, and bitwise operations, with a high level overview and future drill-down.

Explore arithmetic operators and operator precedence in SQL, including addition, subtraction, multiplication, division, modulo, and how parentheses override order for row-wise salary calculations.

Explore arithmetic operators in sql through a hands-on exercise on an employee table, covering addition, subtraction, multiplication, modulus, operator precedence, and using parentheses or the mod function.

Master sql operators for comparison: =, >, <, >=, <=, !=, and use them on an employee table to compare ages and salaries.

Learn how to use sql logical operators like and and between to filter data by combining conditions and ranges, illustrated with an employee table.

Explore the in and not in operators in sql, using employee_id examples to filter multiple values, exclude entries, and even combine with not and between.

Explore how the like and or operators filter data by pattern matching using % and _ wildcards, including ends-with and starts-with queries on an employee table.

Explore exists and not exists operators to test whether a record exists in a subquery, using the employee and department tables to illustrate true or false results.

Explore aggregate functions in SQL, including count, sum, average, max, and min, and learn how to use group by, order by, and null handling on an employee table.

Explore aggregate functions in SQL with hands-on examples on an employee table. Master count, sum, average, max, min, group by, where, and handling nulls and distinct values.

Learn how SQL clauses restrict and manage data for analysis, including where, order by, group by, and having, to filter, sort, and group results with user-friendly queries.

Learn how the where clause filters rows by a condition, used with select, update, and delete statements, with examples like filtering by location, deleting a record, and updating an employee.

Master the where clause with hands-on MySQL examples on the university employee table, filtering by location, deleting by name, and updating by employee ID.

Learn how to use the order by clause to sort records by a column in ascending or descending order. Explore sorting by multiple columns, null values, and where conditions.

Master how to use the order by clause to sort data in ascending order, by column name or number, including multi-column sorting and conditions like salary > 30000.

Learn to use the order by clause to sort data in descending order, with age and salary examples, and explore column name versus column number and where conditions in MySQL.

Use the order by clause to sort by multiple columns, applying ascending to one and descending to another, with the first column taking priority and no same-column dual orders.

Explore sorting by commission in ascending order while handling null values in MySQL, using order by commission, order by commission is null, and the coalesce function on the employee table.

Explore how order by descending handles null values, with nulls pushed to the end, and how to bring nulls to the front using commission and coalesce, demonstrated on employee table.

Master the group by clause to group data by a column, apply aggregate functions such as sum, average, max, and min, and optionally use where and order by.

See how the group by clause aggregates salaries by department id using sum, with an example using an employee table and an age filter via a where clause.

Explore advanced group by techniques by grouping on two columns, such as department ID and location, and calculate salary sums while handling errors and column numbering.

Explore how the having clause filters groups after group by, using aggregate conditions, combining where, order by, and examples with sum and count.

Perform hands-on practice with the having clause to filter grouped results, using sum and count with department-based groups, and compare where versus having along with order by.

Learn how to insert null values into tables and update cells to null in sql, including explicit nulls and leaving columns blank, with examples in an employee table.

insert and manage null values in a MySQL table by practicing explicit nulls, omitting columns during insert, and updating salary to and from null in the employee six table.

This lecture clarifies null versus empty space, showing empty space is a real value (zero characters) while null is the absence of a value, and explains count(*) and counting.

Explore how empty space differs from null in sql by inserting records and observing that empty space is counted in column counts, while nulls are ignored by count(column).

Learn to locate null values in SQL tables using is null and is not null, with practical examples on an employee table and salary column, and methods to count nulls.

Explore hands-on techniques to locate and count null values in SQL tables, using is null and is not null conditions, and compute null counts with count and case expressions.

Explore how null values affect sql arithmetic expressions and comparisons, demonstrating that any null operand yields null, while nulls are ignored in comparisons and impact salary calculations.

Explore how null values affect SQL arithmetic and comparisons with hands-on practice on the employees table's salary column, showing that null yields null and comparisons ignore nulls.

Explains subqueries in SQL, showing how a nested inner query feeds the main query, and covers rules, group by, having, and use in select, insert, update, and delete.

Practice subqueries in MySQL with the EMP and department tables, finding max salaries and using subqueries in select, insert, update, delete, and group by with having.

Explore row level sub queries and their types: single row, multi row, and correlated, using employee and department data, with maximum salary examples and in, any, and all operators.

Explore the types of subqueries and correlated subqueries, where the inner query depends on the outer query for per-row comparisons in departments. Compare readability versus performance with joins.

Learn row-level subqueries in sql with hands-on practice using a university database, covering single-row and multi-row results, and applying subqueries in where and select clauses across multiple tables.

Explore row level sub queries and correlated subqueries with hands-on practice using a university employee table to compare individual salaries to department averages and perform iterative, self-join style queries.

Explore how joins bring together two tables by comparing one or more keys to retrieve data from multiple tables with a common field.

Learn how rdbms joins combine two tables—left and right—using a common key, such as customer id, with an inner join and iterative row comparisons to produce matched results.

Inner joins return records with matching values from two tables based on a specified condition. Aliasing and the left-right table order influence results, illustrated with customers and orders.

Explore inner joins by creating customers and orders tables, linking them on customer_id, using aliases and on conditions, and applying where filters to reveal matched records.

Master outer joins in SQL, including left, right, and full outer joins, using a common key to combine customers and orders, and handling unmatched rows with nulls.

Explore left outer, right outer, and full outer joins in MySQL using customers and orders, mastering join syntax, on conditions, and null handling through hands-on practice.

Learn how to perform a self-join by joining a table to itself using aliases, and see how inner joins can identify customers with the same address.

Apply self joins to find customers who share the same address, using aliases and an inner join to compare Neha's address with others.

Learn about cross joins, or cartesian products, where every row from one table matches every row from another. Use select * from table1 cross join table2 to see the result.

Explore cross joins with hands-on examples in a MySQL database, linking meals and drinks to produce a Cartesian product of nine records, with optional column selection, ordering, and limiting.

Learn how SQL set operators combine rows from two queries using union, union all, minus, and intersect, with rules on column counts, order by, and data type alignment.

Combine two or more select queries with the union set operator to remove duplicates, preserve nulls, align column sequences and data types, and apply a final order by.

Learn how to use the union set operator to combine records from multiple tables, excluding duplicates, ensure matching data types and column order, and apply where and order by clauses.

Explore the union all set operator by combining two queries, preserving duplicates, and compare it with union while covering syntax, column alignment, ordering, and duplicate handling.

Demonstrates the union all set operator in MySQL by combining two tables, showing duplicates preserved, with optional column selection, where conditions, and ordering.

learn how intersect set operator identifies common records between two select statements, and implement a mysql workaround using inner join with student tables to return the shared rows including nulls.

Discover how the minus set operator returns rows unique to the first query, its Oracle support versus MySQL limitations, and practical alternatives using left and right joins.

Learn how to simulate the minus operation in MySQL using left join and null checks to return records unique to student one or student two, using roll numbers as keys.

Explore string functions in relational databases, including case manipulation, trimming, substring, locate, replace, reverse, and concat. Learn essential character operations for SQL data handling.

Explore string case manipulation in SQL with lower, upper, and init cap functions and practice on a student table, noting MySQL versus Oracle support.

Learn how to add and remove spaces in strings using length, trim, rtrim, and padding functions like lpad, with examples from a student table.

Learn how to trim spaces in SQL using ltrim and trim, remove leading or trailing spaces, and use the length function to measure strings on table columns.

Learn to pad strings in SQL using left and right padding functions, specify total length, and pad with characters like hashes or spaces, with hands-on examples.

Learn to manage spaces in SQL by adding, trimming, and padding using length, trim, ltrim, rtrim, lpad, and rpad on customer data in a university database.

Explore the substring function in SQL, learning how to extract parts of a string using start position and length, with examples of substring, substr, and mid.

Learn how the substring function in SQL extracts characters from a table column, using position, length, and even negative positions, and how to update a column with the result.

Learn to use MySQL substring functions with hands-on examples on the university database, extracting parts of names and cities, handling positive and negative positions, and updating data with substring.

Learn how substring index extracts a string segment using a delimiter with a three-argument syntax, handling left-to-right or right-to-left extraction via positive or negative counts, with url and ip examples.

Learn how to use the substring_index function in sql to extract parts of a string or url by delimiter, counting from left or right with positive and negative numbers.