Big data

Big data consists of datasets whose size, speed of change, or complexity exceeds what conventional data-management methods can handle efficiently. It is characterized by the need for specialized storage, processing, and analytical systems.

Distributed computing: A computing approach that divides work among multiple networked computers. Big-data systems split storage and computation across machines to handle scale.
Database: An organized collection of data managed for storage, retrieval, and updating. Big-data systems extend database ideas to larger, faster, and less uniform collections.
Data mining: The process of discovering patterns and useful relationships in large datasets. Big data supplies the large collections searched for recurring patterns.
Data privacy: The protection and appropriate use of information relating to identifiable people. Combining large datasets can expose personal details beyond what each source reveals.
Relational database: A database that stores related data in tables governed by a defined schema. Relational systems remain effective when data is structured and transactions need strong consistency.
MapReduce: A programming model that processes large datasets through parallel map and reduce operations. It established a widely used pattern for parallel processing across clusters.
Volume, velocity, and variety: Three commonly cited dimensions of big data: amount, arrival speed, and diversity of formats. These dimensions describe distinct pressures that make datasets difficult to manage.
Machine learning: Methods that enable computer systems to learn patterns from data and make predictions. Large datasets can provide examples for training and evaluating predictive models.
Algorithmic bias: Systematic and unfair differences in outcomes produced by algorithmic systems. Patterns in biased or unrepresentative data can be reproduced at scale.
NoSQL: A family of database systems designed for models beyond traditional relational tables. NoSQL systems trade some relational conventions for flexible schemas or distributed scale.

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