Artificial intelligence and data

Building the Data Warehouse

Building the Data Warehouse is W. H. Inmon's foundational 1992 data warehousing book (QED/Wiley, four editions through 2005), defining the warehouse as subject-oriented, integrated, time-variant, nonvolatile data for management decisions, contrasting with Kimball's bottom-up approach.

Bundle adjustment

Bundle adjustment is a nonlinear least-squares optimization that jointly refines camera poses and 3D point positions so reprojected points match observed image features, typically as the final structure-from-motion step.

Business analytics

Business analytics is the practice of gathering and analyzing data using statistical and quantitative methods, predictive models, and fact-based management to drive business decisions, spanning descriptive, predictive, and prescriptive analytics.

Business glossary

Business glossary: a centralized repository of business terms and definitions giving an organization a common language, distinct from a data dictionary (technical metadata) and data catalog (platform), with five pillars: clarity, consistency, context, connection, curation.

Business intelligence

Business intelligence (BI) is the set of techniques and practices that transforms raw data from an organization into meaningful information. Richard Devens first used the term in 1865.

Business intelligence developer

A business intelligence developer designs, builds, and maintains the reporting layer of an organization's data stack: data models, SQL queries, and dashboards in tools such as Power BI, Tableau, and OLAP platforms, distinct from data analysts who use these systems.

Business Process Model and Notation

Business Process Model and Notation (BPMN) is a graphical standard for modeling business processes, maintained by the Object Management Group; version 2.0.2 was adopted in 2014.

Butterfly optimization algorithm

The butterfly optimization algorithm is a swarm-based metaheuristic introduced by Sankalp Arora and Satvir Singh in 2018, which models butterfly foraging and mating behavior to solve global optimization problems.

Butterworth filter

The Butterworth filter, also called the maximally flat filter, is an electronic or digital signal filter with no passband ripple, designed by Stephen Butterworth in 1930 and widely used in audio.

BYOL

BYOL (Bootstrap Your Own Latent) is a self-supervised algorithm introduced at DeepMind in a 2020 NeurIPS paper that learns image representations without labels, using no negative pairs.

Byte-pair encoding

Byte-pair encoding (BPE) is a data compression algorithm adapted for NLP that repeatedly merges the most frequent symbol pairs to build a subword vocabulary for tokenizing text.

ByteTrack

ByteTrack is a multi-object tracking algorithm introduced in 2021 that assigns identities across video frames by associating every detection box, including low-confidence ones, to recover occluded objects.

Bytewax

Bytewax: Python framework with a Rust engine built on Timely Dataflow for stateful stream and event processing, an Apache-2.0 alternative to Flink; latest release v0.21.1 (November 2024), community-maintained since May 2025.

Byzantine fault

A Byzantine fault, also called the Byzantine generals problem, is a distributed-system fault in which a faulty component gives conflicting information to different processes, defined by Lamport, Shostak, and Pease in 1982.

C4.5 algorithm

C4.5 is a decision tree learning algorithm that extends ID3 by using gain ratio, pruning, and handling continuous attributes and unknown values, ranking among the top 10 data mining algorithms.

Cache replacement policies

Cache replacement policies, also known as cache algorithms, are the rules a cache uses to decide which entry to evict when full, determining the hit ratio in systems from CPU caches to Redis.

California Consumer Privacy Act

The California Consumer Privacy Act is a 2018 California law, effective 2020, giving residents rights over the personal data businesses collect, including opting out of its sale.

California Privacy Protection Agency

The California Privacy Protection Agency, also branded as CalPrivacy, is the California state agency that implements and enforces the California Consumer Privacy Act, created by voters in 2020.

Call stack

A call stack is the stack data structure a program's runtime uses to track active function calls, pushing a frame for each call and producing stack traces and stack overflow errors.

Camera calibration

Camera calibration is the process of estimating a camera's intrinsic parameters, its internal geometry and optics, and optionally its extrinsic pose, from images of a known reference pattern.

Camera matrix

The camera matrix, also called the projection matrix, is the 3 × 4 matrix that maps 3D world points to 2D image points under a pinhole camera model.

Camera pose estimation

Camera pose estimation is the task of computing a camera's position and orientation, its six-degree-of-freedom pose, from image data, underpinning visual SLAM, visual odometry, and Structure from Motion.

Camera resectioning

Camera resectioning, also known as geometric camera calibration, is the problem of finding a camera's position and orientation in space from known scene points and their corresponding image positions.

Canada permanent resident card

The Canada permanent resident card, also called the Maple Leaf Card, is a document issued by Immigration, Refugees and Citizenship Canada as official proof of permanent resident status.

Canny edge detection

Canny edge detection is a multi-stage image processing algorithm that detects edges in digital images, introduced by John Canny in 1986 and still the classical baseline.

Canny edge detector

The Canny edge detector, also called the Canny operator, is a multi-stage algorithm for finding edges in images, developed by John F. Canny at MIT in 1983.

CAP theorem

The CAP theorem, also called Brewer's theorem, states that a distributed system cannot guarantee consistency, availability, and partition tolerance simultaneously; it was proved by Seth Gilbert and Nancy Lynch in 2002.

Capsule network

A capsule network is a neural network architecture in which groups of neurons called capsules output vectors, routing information by agreement instead of max pooling, introduced by Geoffrey Hinton's group in 2011.

Cardinality estimation

Cardinality estimation, or selectivity estimation, predicts how many rows a database query will return without executing it; cost-based query optimizers rely on these estimates to choose execution plans.