Data Management Lecture Notes

These flashcards cover key vocabulary and concepts related to data management and database systems, including types, attributes, and industry practices.

Data Model

A conceptual framework for organizing and storing data.

RDBMS

Relational Database Management System; a type of database that uses a structure that allows us to identify and access data in relation to another piece of data in the database.

NoSQL

A category of database management systems that do not use SQL as their primary interface; designed to handle large volumes of data and diverse data types.

CAP Theorem

A principle that states a distributed data store can only guarantee two of the three following properties: Consistency, Availability, and Partition Tolerance.

Sharding

A method of horizontal partitioning in a database where a single database is split into smaller, more manageable pieces.

Replication

The process of sharing information across multiple databases to ensure consistency.

Vertical Scale

Increasing the resources of a single node (server) to handle increased load.

Horizontal Scale

Adding more nodes (servers) to a system to share the load.

Structured Data

Data that is organized and easily searchable; often resides in relational databases.

Semi-structured Data

Data that does not conform to a rigid structure but contains tags or markers to separate elements; examples include XML and JSON.

Unstructured Data

Information that does not have a predefined data model; examples include text files, images, videos.

Key-Value Store

A type of NoSQL database that uses a simple key-value method for storing data.

Document Store

A type of NoSQL database that stores data in documents, typically in JSON-like format.

Column Family Store

A type of NoSQL database that stores data in columns rather than rows, allowing for efficient data retrieval.

Graph Store

A database that uses graph structures with nodes, edges, and properties to represent and store data.

ElasticSearch

A distributed, RESTful search and analytics engine capable of solving a growing number of use cases.

Caching

Temporary storage of data to speed up data retrieval times.

Analytics-aware Organizations

Organizations that leverage data analytics to enhance decision making.

Evolvability

The ability of a data management system to adapt and evolve over time to accommodate new requirements.