Data Management on English AI Terms Dictionary

Intelligent database

Sat, 18 Jul 2026 10:02:57 +0000

Definition

An intelligent database leverages machine learning and AI to enhance standard database functionalities beyond simple storage and retrieval. It can automatically optimize query performance, predict usage patterns, detect anomalies, and even generate natural language summaries of data trends. This reduces the administrative burden on DBAs and enables users to extract actionable insights without deep technical expertise.

Summary

A database system that incorporates AI capabilities to automate data management, query optimization, and insights generation.

Feature Store

Sat, 18 Jul 2026 09:58:07 +0000

Definition

A Feature Store acts as a bridge between data engineering and machine learning teams, providing a unified view of features for both batch training and real-time inference. It ensures consistency by preventing training-serving skew, where features used during training differ from those used at prediction time. Key capabilities include versioning, lineage tracking, and low-latency serving, which streamline the MLOps lifecycle and facilitate collaboration across organizations.

Summary

A centralized repository designed to manage, share, and serve features consistently across machine learning training and inference.

Data-centric AI

Sat, 18 Jul 2026 09:52:47 +0000

Definition

Data-centric AI represents a paradigm shift in artificial intelligence development, focusing on systematically improving the data used to train models rather than solely optimizing algorithms or hyperparameters. Proponents argue that high-quality, well-labeled, and diverse datasets yield better performance gains than complex model tweaks. This methodology involves rigorous data auditing, labeling consistency checks, and iterative data refinement. By treating data as a first-class citizen, organizations can build more robust, fair, and accurate AI systems with less computational overhead.

Croissant

Sat, 18 Jul 2026 09:52:00 +0000

Definition

Developed as part of the MLCommons initiative, Croissant uses JSON-LD to provide a standardized way to describe datasets, including their structure, citations, and licensing. It aims to solve the fragmentation problem in dataset documentation by creating a universal language for data sharing. This format allows tools and platforms to automatically ingest and understand dataset properties, streamlining the process of finding, loading, and using data for machine learning projects.

Summary

Croissant is an open metadata format for describing datasets, facilitating discoverability and interoperability in AI.

Chunking

Sat, 18 Jul 2026 09:49:17 +0000

Definition

Chunking is a critical preprocessing step in Retrieval-Augmented Generation (RAG) and other NLP pipelines. It involves dividing text into fixed-size or semantic units (chunks) to fit within the context window limits of language models. Effective chunking strategies balance context preservation with retrieval accuracy, ensuring that each segment contains sufficient information to be useful when queried. This technique enables the handling of vast amounts of data that exceed the memory constraints of individual model inputs.

Knowledge Base

Sat, 18 Jul 2026 09:41:26 +0000

Definition

A knowledge base serves as a digital library containing curated data, documents, or facts that AI systems can query to provide accurate, context-aware responses. In modern architectures like Retrieval-Augmented Generation (RAG), it bridges the gap between static pre-trained models and dynamic real-world information. By indexing external data sources, it allows language models to ground their outputs in verified facts, reducing hallucinations and enabling specialized domain expertise without requiring full model retraining.

View

Sat, 18 Jul 2026 09:37:52 +0000

Definition

In database management, a view acts as a saved SQL query that behaves like a table but contains no data itself. It provides a simplified or customized perspective of underlying data, enhancing security by restricting access to specific columns. Views simplify complex joins and aggregations for users, allowing them to interact with structured data representations without needing to understand the base schema’s complexity.

Summary

A virtual table in a database resulting from a stored query, presenting data from one or more tables without storing it physically.