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Flashcards based on key concepts from the D492 lecture notes covering various aspects of relational and non-relational databases.
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Relational Database
A type of database that uses tables to store data, utilizing a tabular schema with rows and columns.
RDBMS
Relational database management system, software that maintains relational databases.
NoSQL
A non-relational database that addresses the need for web-based databases to handle large amounts of data.
Normalization
The process of structuring data for optimal storage and use within a database.
First Normal Form (1NF)
Eliminates redundant information in tables; each set of related data is stored in a dedicated table.
Foreign Key
A key used in one table to refer to a primary key in another table, creating a relationship between the two.
One-to-One Relationship
A relationship where one record in one table is associated with only one record in another table.
Cascade Update
The action of automatically updating a primary key across all related tables when the key changes.
Denormalized Data
Data that is not structured into tables using normalization and contains redundant or repetitive elements.
ETL Process
Extract, Transform, Load; the method of moving data from source systems to data warehouses.
Data Warehouse
A technology for storing company data from various sources for reporting and decision-making.
Data Lake
A storage repository that holds large amounts of structured and unstructured data in its raw format.
Schemas in Data Warehousing
Common configurations for relating data tables, including star schemas and snowflake schemas.
Data Profiling
The process of analyzing data to understand its quality, structure, and relationships.
QuickSight
Amazon Web Services' tool for dashboarding and data visualization.
API
Application Programming Interface; a set of protocols that allows different software systems to communicate.
Web Scraping
The process of extracting information from websites using automated tools.
Master Data Management
Tools and processes used to create and maintain a single source of truth for critical data.
Data Validation
The process of confirming that data is accurate, follows data quality standards, and is appropriate for analysis.