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Questions and Answers
What is the primary purpose of the SELECT command in SQL?
To retrieve data from a database
What is the main difference between HAVING and WHERE clauses in SQL?
HAVING filters grouped data, while WHERE filters individual data
What is the purpose of data modeling?
To create a conceptual representation of data structures and relationships
What is the difference between an entity and an attribute in ER modeling?
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What is the main purpose of a data warehouse?
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What is ETL in the context of data warehousing?
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What is the primary goal of normalization in database design?
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What is the difference between First Normal Form (1NF) and Second Normal Form (2NF) in normalization?
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What is the main difference between logical and physical database design?
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What is the goal of performance tuning in physical database design?
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Study Notes
SQL
- Structured Query Language: a standard language for managing relational databases
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Basic SQL commands:
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SELECT: retrieve data from a database -
INSERT: add new data to a database -
UPDATE: modify existing data in a database -
DELETE: delete data from a database
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SQL syntax:
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FROMclause: specify the tables to retrieve data from -
WHEREclause: filter data based on conditions -
GROUP BYclause: group data based on one or more columns -
HAVINGclause: filter grouped data based on conditions
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SQL data types:
- Integer: whole numbers (e.g., 1, 2, 3, etc.)
- String: character strings (e.g., "hello", "goodbye")
- Date: dates and timestamps (e.g., "2022-01-01", "2022-01-01 12:00:00")
Data Modeling
- Data modeling: the process of creating a conceptual representation of data structures and relationships
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Entity-Relationship (ER) modeling:
- Entities: objects or concepts with independent existence (e.g., customers, orders)
- Attributes: characteristics of entities (e.g., customer name, order date)
- Relationships: connections between entities (e.g., one customer can have many orders)
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Data modeling notations:
- ER diagrams: visual representations of entities, attributes, and relationships
- UML (Unified Modeling Language): a standardized notation for data modeling
Data Warehousing
- Data warehousing: the process of collecting, storing, and managing data from various sources for analysis and reporting
- Data warehouse: a central repository of data from various sources, optimized for querying and analysis
- Data mart: a subset of a data warehouse, focused on a specific business area or department
- ETL (Extract, Transform, Load): the process of extracting data from sources, transforming it into a standardized format, and loading it into a data warehouse
Normalization
- Normalization: the process of organizing data to minimize data redundancy and improve data integrity
- First Normal Form (1NF): each table cell must contain a single value
- Second Normal Form (2NF): each non-key attribute in a table must depend on the entire primary key
- Third Normal Form (3NF): if a table is in 2NF, and a non-key attribute depends on another non-key attribute, then it should be moved to a separate table
- Boyce-Codd Normal Form (BCNF): a table is in BCNF if and only if it is in 3NF and there are no transitive dependencies
Database Design
- Database design: the process of creating a logical and physical structure for a database
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Logical database design:
- Conceptual design: identifying entities, attributes, and relationships
- Logical design: defining tables, fields, and relationships
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Physical database design:
- Storage: defining file organizations, storage structures, and access methods
- Performance tuning: optimizing database performance for queries and updates
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Description
Test your knowledge of database concepts, including SQL, data modeling, data warehousing, normalization, and database design. Covering topics such as SQL commands, data types, entity-relationship modeling, and database normalization forms.
