Oracle SQL for beginners Training Course

Relational Database Models

• The structure of a relational database for government operations.
• Types of table connections for efficient data retrieval and management.
• Normalization and denormalization techniques in databases to optimize performance and ensure data integrity.
• Relational operators used in query construction for precise data manipulation.

Downloading Data

• Best practices for writing SQL queries to extract accurate information.
• Syntax guidelines for the SELECT statement to retrieve specific data fields.
• Selecting all columns from a table to view comprehensive datasets.
• Performing arithmetic operations within SQL queries to derive calculated values.
• Using column aliases to enhance query readability and clarity.
• Incorporating literals into SQL statements for static value representation.
• Applying the concatenation operator to combine data from multiple columns or fields.

Limiting Results

• The WHERE clause for filtering specific records based on conditions.
• Comparison operators for precise data selection and filtering.
• The LIKE condition for pattern matching in text-based searches.
• The BETWEEN ... AND condition for selecting a range of values.
• The IS NULL condition to identify missing or undefined data entries.
• The IN condition for specifying multiple possible values in a single clause.
• Boolean operators (AND, OR, NOT) for combining and negating conditions.
• Applying multiple conditions within the WHERE clause for complex queries.
• The order of operations to ensure correct evaluation of query conditions.
• The DISTINCT clause for eliminating duplicate records from result sets.

Sorting Data

• The ORDER BY clause for arranging data in a specified sequence.
• Sorting by multiple columns or expressions to refine the order of results.

SQL Functions

• Differences between single-row and multi-row functions for data manipulation.
• Text, numeric, and date functions for various data transformations.
• Explicit and implicit conversion techniques for ensuring data compatibility.
• Conversion functions to change data types within queries.
• Nesting functions for complex data processing tasks.
• Using the DUAL table to view function performance in Oracle databases.
• The SYSDATE function for retrieving the current date and time.
• Handling NULL values in SQL functions to ensure accurate results.

Aggregating Data Using Grouping

• Grouping functions for summarizing data based on specific criteria.
• How grouping functions handle NULL values to maintain data integrity.
• The GROUP BY clause for creating groups of data based on common attributes.
• Grouping by multiple columns to refine and organize result sets.
• The HAVING clause for limiting the results of grouping functions based on additional conditions.

Retrieving Data from Multiple Tables

• Types of joins for combining data from different tables.
• The NATURAL JOIN for automatically matching and joining common columns.
• Table aliases to improve query readability and manage complex joins.
• Joins in the WHERE clause for specifying join conditions explicitly.
• The INNER JOIN for retrieving only matching records from multiple tables.
• Outer joins (LEFT, RIGHT, FULL OUTER) for including non-matching records.
• The Cartesian product for generating all possible combinations of records.

Subqueries

• Using subqueries within the SELECT command to enhance query functionality.
• Differentiating between single-row and multi-row subqueries for varied data retrieval needs.
• Single-row subquery operators for precise condition matching.
• Grouping features in subqueries for advanced data aggregation.
• Multiline subquery operators (IN, ALL, ANY) for complex conditions.
• Treating NULL values within subqueries to ensure accurate results.

Collective Operators

• The UNION operator for combining the results of multiple SELECT statements without duplicates.
• The UNION ALL operator for combining results including all duplicates.
• The INTERSECT operator for finding common records between two or more datasets.
• The MINUS operator for retrieving records that exist in one dataset but not another.

Insert, Update, and Delete Data

• The INSERT command for adding new records to a table.
• Copying data from one table to another using the INSERT command.
• The UPDATE command for modifying existing records in a table.
• The DELETE command for removing specific records based on conditions.
• The TRUNCATE command for quickly deleting all records from a table.

Transactions

• Using the COMMIT, ROLLBACK, and SAVEPOINT commands to manage transactional integrity.

DDL Commands

• Key database objects for structuring data storage and retrieval systems.
• Naming conventions for database objects to ensure clarity and consistency.
• Creatin tables with defined columns and constraints.
• Data types available for defining column properties in tables.
• The DEFAULT option for specifying default values for columns.
• The NULL and NOT NULL options for managing the presence of data in columns.

Managing Tables

• Maintaining referential integrity with CHECK, PRIMARY KEY, FOREIGN KEY, and UNIQUE constraints.
• Creating tables based on query results for dynamic data storage.
• The DROP TABLE command for removing tables from the database schema.
• The DESCRIBE command for viewing table structure and column details.

Other Schema Objects

• Sequences for generating unique numeric values.
• Synonyms for creating alternative names for objects.
• Views for presenting customized or aggregated data to users.