AI Glossary: 80 Essential Artificial Intelligence Terms Explained

A data catalog is a searchable inventory of available data assets, sources, datasets, and associated metadata.

Data ingestion refers to the process of collecting, importing, transferring, and storing raw data from various sources for further use or archival and storage.

Data labeling is the process of assigning labels or tags to data in order to enrich that data. Data labeling is used to train neural networks and evaluate existing AI systems, such as for instance spam detection or sentiment analysis.

A data lake (or data warehouse) is a centralized repository for the storage of vast amounts of raw, unprocessed data. It is a flexible, scalable infrastructure that facilitates analytics, data processing, and data exploration across an organization.

A data pipeline is a set of processes and tools for collecting, transforming, transporting, and enriching data from various sources. Data pipelines control the flow of data from source through transformation and processing components to the data’s final storage location.

Data sanitization is the process of ensuring that sensitive information is removed or masked in datasets to protect privacy and comply with data protection regulations. Sanitizing data involves identifying and appropriately handling personally identifiable information (PII) or other sensitive data to prevent unauthorized access or disclosure.

Data validation is the process of ensuring data is accurate, consistent and meets pre-defined criteria or standards. Data validation can be completed in a range of ways, including the use of neural networks, algorithms, or human assessment.

A data warehouse (or data lake) is a centralized repository for the storage of vast amounts of raw, unprocessed data. It is a flexible, scalable infrastructure that facilitates analytics, data processing, and data exploration across an organization.

A dataset is a structured collection of data, usually with some sort of schema, that can be used for analysis, research, and large language or machine model training and evaluation.