DBMS for Programmers: Unit 1 Overview

Database management systems (DBMS) are covered, focusing on topics important to programmers.
Topics include introduction to databases, entities-relationships (E-R) diagrams, normalization, transactions, indexing, and SQL.

Introduction to Databases: Focuses on foundational database concepts.
Data: Covers the raw facts and figures stored in the database.
Information: Interpreted data used to make decisions.
Knowledge: Understanding and application of information.
Characteristics of the Database Approach: Explores essential aspects of database design.

E-R Modeling: Covers the technique used for visual representation of databases and their relationships.
Notation for E-R Diagrams: Detailed explanation of symbols and techniques for drawing E-R diagrams.
Attributes: The characteristics (e.g., name, age) of database entities.
Relationships: Connections between entities (e.g., one customer can have multiple orders).
Strong and Weak Entities: Describes different types of entities.
One-to-One Relationship: Relationship where one entity can only be linked to another.
One-to-Many Relationship: Relationship where one entity could relate to many others.
Many-to-Many Relationship: Relationship involving multiple entities on both sides.

Types of Keys: Different types of keys (composite, primary, candidate, secondary) used in databases are explained.
Super key: A set of one or more attributes that uniquely identify an entity in a database
Candidate Key: A minimal super key (a super key that loses no attributes without losing its uniqueness).
Primary Key: Chosen candidate key to uniquely identify an entity, making it the primary indicator for each entry.
Alternate Key: Other candidate keys apart from the primary key.
Composite key: A combination of multiple attributes to form a primary key.
Foreign Key: A primary key attribute in a related table used to link entities in different tables.

Basic Functional Dependency: Understanding the fundamental dependencies within data.
Types of Functional Dependency: Different relationships between attributes.
Inference Rules/Axioms Rules: Rules for deriving relationships between attributes.
Closure set of Attributes: Set of attributes that can be derived from one another with functional dependencies (fd).

Introduction to Normalization: Focuses on structuring data to reduce redundancy and dependency issues.
1NF, 2NF, 3NF, 4NF: Various normal forms with their specific rules for structured database tables.
Decomposition of Relation: Breaking down relations to achieve normalization.
Lossless and Lossy Decomposition: Describing decomposition approaches.
Dependency-Preserving Decomposition: Methods that maintain relationships among attribute in relations during decomposition.

Transaction Processing: Covers the process of executing transactions.
Properties of Transactions: Explores the ACID properties (Atomicity, Consistency, Isolation, Durability) required for transactions.
Transaction State Diagram: A visual representation of different possible states of a transaction.
Types of schedules: Explores different schedules for transactions (various scheduling types).
Testing of Serializability: Methods to determine if a set of transactions are properly managed and synchronized before execution.
Conflict Serializable: Deals with transactions that are in conflict and their effects.
View Serializable: Refers to transactions that are consistent with the view.

Two-Phase Locking (2PL): A protocol that controls how locks are acquired and released.
Version of 2PL: Variations in the original Two-Phase Locking (2PL) protocol.
Timestamp-Based Protocol: Technique that orders transactions based on timestamps from a clock.
Strict Timestamp-Based Protocol: A protocol where if a transaction aborts, it must release all its locks, preventing conflicts.
Thomas Write Rule: A protocol that allows a transaction to write to a record even if previous reads were not completed.

Indexing and Types of Indices: Details on using indexes for faster data retrieval.
Primary Index: An index based on a unique attribute.
Secondary Index: An index based on a non-unique attribute.
Clustering Index: A combination between the logical order of records and the physical order of records.
Hash Index: Index structure relying on hashing algorithms.
Multi-level Indexing: Hierarchical indexing structure to improve performance.
Multi-way search Tree: Details on how B-Trees and B+ Trees are constructed.
B-Tree: A tree-like structure for indexing data.
B+ Tree: A variant of B-Tree that reduces overhead and improves efficiency.
B-Tree creation & Insertion: Describes the process of creating and adding entries to a B-tree.
B-Tree Deletion: Discusses the procedure for removing entries from a B-tree.
B+ Tree creation, deletion, & insertion: Processes covered for handling data addition, removal, and organization in a B+ Tree.
Difference between B-Tree and B+ Tree: Comparison of these structures, pointing out their distinctions in terms of implementation and efficiency.

Introduction to SQL: Overview of the Structured Query Language.
Data Definition Language (DDL): Covers SQL commands for defining database schemas.
Data Manipulation Language (DML): Describes SQL commands for modifying data in tables.
SQL Basic Operations: Explores fundamental SQL operations such as SELECT, UPDATE, INSERT, and DELETE.
Aggregate Functions: Functions that work on a group of rows to produce a single output value (such as COUNT, AVG).
SQL Constraints: Rules restricting the types of data that can be stored in a database.
Set Operations: SQL operations like union, intersection, and difference over sets of attributes in tables.

Introduction to Relational Algebra: Details about relational algebra operations (set operations).
Select Operation: Retrieving specific rows that satisfy a condition.
Project Operation: Extracting certain attributes from a table.
Rename Operation: Changing the names of attributes.
Union Operation: Combining the results of two similar tables.
Set Difference Operation: Finding the difference between rows in two tables.
Cartesian Operation: Creating a new relation by combining rows from two tables.
Join Operation: Finding common relations between two tables.
Intersection Operation: Finding common tuples between two relations.
Division Operation: Finding tuples in one relation that satisfy a specific relation with another relation.
Outer Join: Produces all rows from one relation that have matches and nulls for other attribute places.