Database Concepts: Midterm Study

• Study session structured around key database concepts for midterm preparation.

Database Fundamentals

• Database is a standardized data collection designed for multiple users.
• Databases support decision-making, legal and descriptive reporting, and trend analysis.
• Database Management System (DBMS) is a software for database creation, organization, and management.
• DBMS features include query tools, security measures, and multi-user handling capabilities.

Database Life Cycle

• Requirements collection and analysis involve identifying data needs for decision-making, as exemplified by Highline University's report analysis.
• Conceptual modeling is the abstract representation of data.
• Logical modeling involves defining data structure using a relational data model.
• Physical modeling is the implementation of the actual storage structure.
• Application design focuses on interfaces and database interactions.

Conceptual Modeling

• Purpose is to abstract real-world data and define its structure while avoiding duplication and redundancy.
• Uses Chen’s notation and Crow’s Feet notation.
• Requires adhering to specific rules for model creation.

Database Concepts

• Database design involves structuring data for storage and management.
• Database modeling refers to creating a structured data model.
• Problem domain defines the clearly defined area that the database covers.
• Data integrity & consistency are crucial for making accurate decisions.

Conceptual Modeling Concepts

• Conceptual modeling includes extracting abstract data structures.
• Keys include primary, candidate, surrogate, and composite keys.
• Attributes are the properties of entities.
• Relationships include unary, binary, ternary, and N-ary relationships.
• Focus is mainly on binary relationships.
• Relationships can also have attributes.
• Mapping ratios define relationships as one-to-one (1:1), one-to-many (1:N), or many-to-many (N:M).
• Min/max cardinalities define entity participation in relationships.
• Participation can be optional or mandatory.

Conceptual Model Components

• Entities are real-world concepts that are stored in the database.
• Attributes are characteristics of entities.
• Relationships define associations between entities.
• Entity-Relationship Diagrams (ERD) help with visual representation.
• Crow’s Feet Notation provides a graphical representation for relationships.
• Min/Max Cardinalities specify relationship participation constraints.

Business Rules in Database Design

• Standardizes company data representation.
• Defines data relationships.
• Facilitates communication between users and designers.
• Captures business processes effectively.

Data to Wisdom Progression

• Data progresses to information, then knowledge, and finally to wisdom.
• Proper database design improves decision-making overall.
• Human judgment is required even with automation.

Queries & Relational Model

• Queries are requests for information from the database.
• Relational Model structures data into relations (tables).
• Conceptual Model translates into Logical Model (Relational Model).
• Translation rules depend on min/max cardinalities.
• Domain constraints define valid attribute values.
• Entity constraints ensure unique record identification.
• Data constraints are rules governing data accuracy.

ER-Relational Model Translation

• Entities become relations (tables).
• 1:N relationships are implemented using Foreign Keys.
• N:M relationships require a separate relation (junction table).
• Relationship Attributes are stored in junction tables.

Data Warehouses & Data Mining

• Data warehousing involves centralized data storage from different sources.
• Customer segmentation.
• Marketing & promotions.
• Market basket analysis.
• Fraud detection.
• Financial modeling.

SQL (Structured Query Language)

• Structured Query Language is used to retrieve and manipulate data.
• Allows structured data access.
• DDL (Data Definition Language) defines schema.
• DML (Data Manipulation Language) performs CRUD (Create, Read, Update, Delete) operations.
• Common SQL statements include:
  • CREATE TABLE defines structure.
  • INSERT INTO adds records.
  • SELECT retrieves data.
  • UPDATE modifies data.
  • DELETE removes data.
• Referential Integrity ensures consistent relationships between tables.

Course Progression & Contemporary Issues

• Database implementation applies concepts to real-world databases.
• Big Data & Innovation are emerging trends in data storage.
• Large Language Models & AI are creating new data management challenges.