Big Data Articles

Sara A. Metwalli

Updated on July 22, 2025

Superposition is a quantum principle that describes a quantum system’s ability to be in multiple states at the same time until it is measured.

Stephen Gossett

Updated on July 15, 2025

Chief data officers, or CDOs, are C-suite executives responsible for the developing and implementing an organization’s data strategy.

Julius Černiauskas

Updated on July 15, 2025

Cloudflare announced it will now block AI scrapers by default, but will this improve relationships between AI builders and content creators? Our expert weighs in.

Margo Steines

Updated on July 14, 2025

Data brokers collect, clean up, analyze and sell access to data about individuals and organizations. These are the top data brokers to know.

Alyssa Schroer

Updated on July 14, 2025

These companies leverage data insights for marketing and advertising purposes.

Jenny Lyons-Cunha

Updated on June 26, 2025

From interactive dashboards to intricate diagrams, data visualization comes in all kinds of formats, helping users draw conclusions, identify patterns and make more informed decisions. engaging formats.

Anthony Corbo

Updated on June 23, 2025

Inferential statistics is a branch of statistics that uses sampled data to draw conclusions or make predictions about a larger population.

Chris Dowsett

Updated on June 18, 2025

Selection effect is a bias that occurs when a sample or method favors a specific subset of a population, leading to results that don’t accurately represent the whole. If unchecked, selection effect can lead to false positives and bad investments.

Abdishakur Hassan

Updated on June 18, 2025

Cluster analysis is a data analysis technique that groups together data points that are similar to each other within a data set. Here’s how it’s useful, its applications, types, algorithms, tips for assessing clustering and an example of cluster analysis.

Adam Thomas

Updated on June 18, 2025

Normalization organizes data into separate tables to reduce redundancy and prevent anomalies, improving data integrity. Denormalization combines tables and adds redundancy to speed up queries and simplify data access, often at the cost of consistency.