Database Specialist (1D0-541)
1 Introduction to Databases
1-1 Definition and Purpose of Databases
1-2 Types of Databases
1-3 Database Management Systems (DBMS)
1-4 Evolution of Databases
2 Relational Database Concepts
2-1 Relational Model
2-2 Tables, Rows, and Columns
2-3 Keys (Primary, Foreign, Composite)
2-4 Relationships (One-to-One, One-to-Many, Many-to-Many)
2-5 Normalization (1NF, 2NF, 3NF, BCNF)
3 SQL Fundamentals
3-1 Introduction to SQL
3-2 Data Definition Language (DDL)
3-2 1 CREATE, ALTER, DROP
3-3 Data Manipulation Language (DML)
3-3 1 SELECT, INSERT, UPDATE, DELETE
3-4 Data Control Language (DCL)
3-4 1 GRANT, REVOKE
3-5 Transaction Control Language (TCL)
3-5 1 COMMIT, ROLLBACK, SAVEPOINT
4 Advanced SQL
4-1 Subqueries
4-2 Joins (INNER, OUTER, CROSS)
4-3 Set Operations (UNION, INTERSECT, EXCEPT)
4-4 Aggregation Functions (COUNT, SUM, AVG, MAX, MIN)
4-5 Grouping and Filtering (GROUP BY, HAVING)
4-6 Window Functions
5 Database Design
5-1 Entity-Relationship (ER) Modeling
5-2 ER Diagrams
5-3 Mapping ER Diagrams to Relational Schemas
5-4 Design Considerations (Performance, Scalability, Security)
6 Indexing and Performance Tuning
6-1 Indexes (Clustered, Non-Clustered)
6-2 Index Types (B-Tree, Bitmap)
6-3 Indexing Strategies
6-4 Query Optimization Techniques
6-5 Performance Monitoring and Tuning
7 Database Security
7-1 Authentication and Authorization
7-2 Role-Based Access Control (RBAC)
7-3 Data Encryption (Symmetric, Asymmetric)
7-4 Auditing and Logging
7-5 Backup and Recovery Strategies
8 Data Warehousing and Business Intelligence
8-1 Introduction to Data Warehousing
8-2 ETL Processes (Extract, Transform, Load)
8-3 Dimensional Modeling
8-4 OLAP (Online Analytical Processing)
8-5 Business Intelligence Tools
9 NoSQL Databases
9-1 Introduction to NoSQL
9-2 Types of NoSQL Databases (Key-Value, Document, Column-Family, Graph)
9-3 CAP Theorem
9-4 NoSQL Data Models
9-5 NoSQL Use Cases
10 Database Administration
10-1 Installation and Configuration
10-2 User Management
10-3 Backup and Recovery
10-4 Monitoring and Maintenance
10-5 Disaster Recovery Planning
11 Emerging Trends in Databases
11-1 Cloud Databases
11-2 Distributed Databases
11-3 NewSQL
11-4 Blockchain and Databases
11-5 AI and Machine Learning in Databases
SQL Fundamentals

SQL Fundamentals

1. SELECT Statement

The SELECT statement is used to retrieve data from a database. It allows you to specify which columns you want to retrieve and from which table. The basic syntax is:

        SELECT column1, column2, ...
        FROM table_name;
    

Example: To retrieve all customer names and their email addresses from a "Customers" table, you would use:

        SELECT Name, Email
        FROM Customers;
    

Analogies: Think of the SELECT statement as asking a librarian for a specific book or a list of books from a catalog.

2. WHERE Clause

The WHERE clause is used to filter records based on specific conditions. It helps in narrowing down the data to only those that meet the specified criteria. The basic syntax is:

        SELECT column1, column2, ...
        FROM table_name
        WHERE condition;
    

Example: To retrieve all customers who live in New York from the "Customers" table, you would use:

        SELECT Name, Email
        FROM Customers
        WHERE City = 'New York';
    

Analogies: The WHERE clause is like applying a filter to a search engine to get only the relevant results.

3. JOIN Operation

The JOIN operation is used to combine rows from two or more tables based on a related column between them. It allows you to query data that is spread across multiple tables. The basic syntax is:

        SELECT column1, column2, ...
        FROM table1
        JOIN table2
        ON table1.column_name = table2.column_name;
    

Example: To retrieve customer names along with their order details from the "Customers" and "Orders" tables, you would use:

        SELECT Customers.Name, Orders.OrderID
        FROM Customers
        JOIN Orders
        ON Customers.CustomerID = Orders.CustomerID;
    

Analogies: The JOIN operation is like combining two spreadsheets by matching a common column, such as a customer ID.