Data Glossary

Browse 103 data terms defined in plain English, from the cultural dictionary of computing.

103 Data Terms

Ad Tech
The ecosystem of software, infrastructure, and data systems used to buy, sell, target, measure, and optimize digital advertising. It includes exchanges,...
Apache Arrow
A cross-language columnar memory format designed for efficient analytical processing. Unlike Parquet (on-disk), Arrow defines how data lives in RAM, enabling...
Apache Iceberg
An open table format for large analytic datasets that brings ACID transactions, schema evolution, time travel, and partition evolution to data lakes. Works...
Apache Kafka
A distributed event streaming platform that handles high-throughput, fault-tolerant, real-time data feeds. Messages are organized into topics, partitioned for...
Apache Kafka
A distributed event-streaming platform used for high-throughput messaging, logs, and data pipelines.
Apache Parquet
A columnar storage file format optimized for analytics workloads. Stores data by column rather than by row, enabling efficient compression (similar values...
Backfill
Re-processing historical data through a pipeline to fill gaps caused by bugs, schema changes, new features, or late-arriving data. Requires idempotent...
Benchmark Contamination
When benchmark test data leaks into a model's training set, inflating evaluation scores without genuine capability improvement. A pervasive problem in LLM...
Bias
Systematic errors in an AI model's outputs that reflect prejudices in training data, algorithm design, or deployment context. An AI trained on biased data...
Big Data
A term for datasets or data-processing problems large or complex enough to require specialized tools, distributed systems, or new workflows. In culture, big...
Binary
As a noun, a compiled, executable file containing machine code. As an adjective, relating to the base-2 numeral system (0 and 1) that underpins all digital...
bitmask
A pattern of bits used with bitwise operations (AND, OR, XOR) to manipulate or test specific bits within a value. Bitmasks are used for permission systems...
Business Intelligence
The tools and practices used to analyze company data for operational, financial, and strategic decisions, often through dashboards, reports, and ad hoc...
Chart
A visual representation of data such as a line graph, bar chart, area chart, or pie chart used to communicate patterns, comparisons, or trends. In software...
Control Vector
A data or representation concept centered on control vector and how information is prepared or encoded for models. It influences how models are trained,...
Copy
To duplicate data, files, objects, or values so the same content exists in another location or memory region. In software discussions, copy can also imply...
Corpus
A data or representation concept centered on corpus and how information is prepared or encoded for models. It influences how models are trained, evaluated, or...
Custom Serializer
A serializer implemented to convert data into a specific wire format, storage format, or schema with rules beyond the defaults. Custom serializers are useful...
Dark Data
Data that an organization collects, stores, or generates but does not actively use, understand, or manage well. In data culture dark data is often seen as both...
Data Access Layer
A Data Access Layer is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code...
Data Access Object
A Data Access Object is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code...
Data Annotation
A data or representation concept centered on data annotation and how information is prepared or encoded for models. It influences how models are trained,...
Data Augmentation Detail
A data or representation concept centered on data augmentation detail and how information is prepared or encoded for models. It influences how models are...
Data Binding
A Data Binding is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier...
Data Cleaning ML
A data or representation concept centered on data cleaning ml and how information is prepared or encoded for models. It influences how models are trained,...
Data Contract
A formal agreement between data producers and consumers that defines the schema, semantics, quality expectations, SLAs, and ownership of a data asset. Like API...
Data Culture
The norms and behaviors an organization has around collecting, sharing, interpreting, and acting on data. Strong data culture values evidence and literacy...
Data Curation
The careful selection, cleaning, labeling, and organization of data so it is suitable for training, evaluation, or retrieval. Data curation is often one of the...
Data Drift
A data or representation concept centered on data drift and how information is prepared or encoded for models. It influences how models are trained, evaluated,...
Data Driven
Describing decisions or processes that are strongly informed by data, metrics, or analysis rather than intuition alone. In tech culture the phrase is often...
Data Ethics
The ethical questions surrounding how data is collected, stored, used, shared, and interpreted, including privacy, consent, fairness, and power. In modern...
Data Flow
A Data Flow is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier to...
Data Flywheel
A data or representation concept centered on data flywheel and how information is prepared or encoded for models. It influences how models are trained,...
Data Governance
The policies, roles, processes, and controls used to manage data quality, access, lineage, retention, and compliance. In data-heavy organizations governance is...
data gravity
The principle that large datasets attract applications, services, and additional data to their location, much like physical mass attracts objects through...
Data Labeling
A data or representation concept centered on data labeling and how information is prepared or encoded for models. It influences how models are trained,...
Data Lakehouse
An architecture that combines the cheap storage and flexibility of data lakes with the ACID transactions, schema enforcement, and performance of data...
Data Layer
A Data Layer is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier...
Data Lineage
The tracking of data's journey from source through transformations to final consumption — which systems produced it, what transformations were applied, and who...
Data Literacy
The ability to read, interpret, question, and use data meaningfully without being misled by charts, dashboards, or metrics. In workplace culture, data literacy...
Data Loader
A Data Loader is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier...
Data Mapper
A Data Mapper is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier...
Data Model
A Data Model is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier...
Data Oriented Design
A Data Oriented Design is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make...
Data Parallelism ML
A data or representation concept centered on data parallelism ml and how information is prepared or encoded for models. It influences how models are trained,...
Data Quality
The degree to which data is accurate, complete, relevant, consistent, and usable for a specific AI task. Poor data quality often causes more serious problems...
Data Race
A Data Race is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier to...
Data Scaling
Increasing the amount or effective use of training or retrieval data to improve model behavior, often in line with scaling-law considerations. Data scaling is...
Data Science
A field combining statistics, programming, domain knowledge, and data analysis to extract insight, build models, or support decisions from data. In tech...
Data Serialization
A Data Serialization is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code...
Dataset Bias
A data or representation concept centered on dataset bias and how information is prepared or encoded for models. It influences how models are trained,...
Dataset Card
A data or representation concept centered on dataset card and how information is prepared or encoded for models. It influences how models are trained,...
Dataset Distillation
A data or representation concept centered on dataset distillation and how information is prepared or encoded for models. It influences how models are trained,...
Dataset Versioning
A data or representation concept centered on dataset versioning and how information is prepared or encoded for models. It influences how models are trained,...
Data Store
A Data Store is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier...
Data Transfer Object
A Data Transfer Object is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make...
Data Type
A Data Type is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code easier to...
Data Validation
A Data Validation is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code...
Data Visualization
The visual presentation of data through charts, graphs, maps, and other forms intended to make patterns easier to understand. In culture, good data...
dbt
Data Build Tool — a transformation framework that lets data analysts write modular SQL to transform raw data into analytics-ready tables. Models are...
Deserialization
A Deserialization is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to make code...
EHR
Electronic Health Record — a digital version of a patient's medical history maintained by healthcare providers. EHR systems (Epic, Cerner) are notoriously...
ETL
Extract, Transform, Load — the three steps of moving data between systems. Extract from sources, transform into the desired format, load into the destination....
Event Sourcing
An architectural pattern where state changes are stored as an immutable sequence of events rather than just the current state. The current state is derived by...
Export Culture
A team or product habit where users repeatedly export data to spreadsheets, CSVs, or other tools because the core system does not support the analysis or...
Face Embedding
A data or representation concept centered on face embedding and how information is prepared or encoded for models. It influences how models are trained,...
Fake Data
Artificial or simulated data used for testing, demos, prototyping, or development instead of real production data. In engineering culture fake data is useful,...
Graph Culture
A team habit of thinking heavily in terms of graphs, dependencies, relationships, and network-like structures, whether in data, architecture, or social...
Idempotent Pipeline
A data pipeline that produces the same output regardless of how many times it's run with the same input. Achieved through techniques like UPSERT/MERGE,...
Immutable
Data that cannot be changed after creation. Instead of modifying existing data, you create new copies with the changes applied. A cornerstone of functional...
Immutable Data Structure
An Immutable Data Structure is a development concept used to shape how software is built, executed, or maintained in real systems. Developers rely on it to...
Labeled Data
A data or representation concept centered on labeled data and how information is prepared or encoded for models. It influences how models are trained,...
Label Smoothing
A data or representation concept centered on label smoothing and how information is prepared or encoded for models. It influences how models are trained,...
Machine Learning
Machine learning is a subset of artificial intelligence in which systems learn patterns from data rather than being explicitly programmed with rules. Instead...
Medallion Architecture
A data organization pattern with three layers: Bronze (raw ingestion, no transformation), Silver (cleaned, deduplicated, conformed), and Gold (aggregated,...
Metadata
Data that describes other data — such as a file's creation date, an image's resolution and EXIF tags, a database table's schema, or an API response's...
Migrate
To move code, data, traffic, or users from one system, version, or platform to another in a controlled way. In practice the word often implies more hidden risk...
NoSQL
A category of databases that don't use traditional relational tables and SQL — including document stores (MongoDB), key-value stores (Redis), column stores...
Object
Object in programming is a fundamental concept in object-oriented programming (OOP) representing a self-contained unit that bundles related data (called...
OpenStreetMap
A collaboratively maintained open geographic database used in mapping applications and spatial tools.
oracle (blockchain)
A service that feeds external real-world data (prices, weather, sports scores, API responses) into a blockchain, since smart contracts cannot natively access...
Pipeline
A series of automated steps that process data or code sequentially. In CI/CD, a pipeline builds, tests, and deploys code. In data engineering, a pipeline...
Property
A named attribute of an object or class that stores data or computes a value. In many languages, properties use getter/setter methods behind a field-like...
Query
A request for data from a database or search engine, typically expressed in a structured language like SQL, GraphQL, or a search DSL. As a verb, to query means...
Schema
A formal description of the structure of data — including tables, columns, types, constraints, and relationships in a database, or the shape of JSON, XML, or...
Schema Registry
A centralized service for managing and enforcing schemas for Kafka messages (Avro, Protobuf, JSON Schema). Producers register schemas before sending messages;...
Self-Instruct
A method of generating synthetic instruction-following data using models themselves, often to expand training datasets without fully manual labeling....
Series
A one-dimensional labeled array in data libraries like pandas, capable of holding any data type and supporting vectorized operations, alignment by index, and...
Slowly Changing Dimension
A data warehousing technique for tracking how dimension attributes change over time. Type 1 overwrites the old value, Type 2 adds a new row with version dates...
Star Schema
A dimensional modeling pattern where a central fact table (events, transactions) connects to multiple dimension tables (who, what, when, where) via foreign...
State
The current set of data values that determine a program's behavior and UI at any given moment, managed locally in components, globally in stores, or on the...
Stream
A sequence of data elements made available over time, processed incrementally rather than loaded entirely into memory, used for file I/O, network...
Stream Processing
Processing data continuously as it arrives rather than in periodic batches. Handles unbounded datasets using windowing (tumbling, sliding, session) for...
Sync
Short for synchronous — describes an operation that blocks the calling thread until it completes and returns a result, as opposed to async operations that...
synthetic training data
Training data generated by AI models rather than collected from humans, used to train or fine-tune other models. While dramatically cheaper to produce,...
Table
A structured collection of data organized in rows and columns within a relational database, where each row represents a record and each column represents a...
Time Series
A sequence of data points indexed by timestamp, typically collected at regular intervals — used for metrics, sensor readings, and financial data, and stored in...
Timestamp
A value representing a specific point in time, typically stored as seconds or milliseconds since the Unix epoch (January 1, 1970 UTC) or as an ISO 8601 string...
Training Data
The dataset used to teach a machine learning model. The quality, size, and representativeness of training data fundamentally determine a model's capabilities...
Training Data Licensing
The legal and contractual framework governing whether data can be used to train or fine-tune AI models.
Type Provider
An F# compiler feature that generates types at compile time from external data sources (databases, APIs, CSV files). Gives you IntelliSense and type safety for...
Unstructured
Lacking a predefined schema, formal format, or consistent organization. The term appears in data work, writing, communication, and sometimes in criticism of...
Unstructured Data AI
AI systems or workflows focused on processing unstructured data such as documents, images, conversations, audio, or free-form text rather than neatly labeled...

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