Data-driven model - A data-driven model is a model whose relationships or parameters are learned substantially from observed data.
Data editing - Data editing is the process of checking data for errors, omissions, and inconsistencies and handling identified problems through documented procedures.
Data entry - Data entry is the process of recording information in a computer system so it can be stored, processed, and used.
Data event - A data event is a recorded indication that something relevant has happened in a data-producing or data-processing system.
Data exchange - Data exchange is the transfer of information between systems or organizations in a form the receiving side can interpret and use.
Data exfiltration - Data exfiltration is the unauthorized transfer of information out of a system or controlled environment.
Data exhaust - Data exhaust is the digital information generated as a by-product of using systems, devices or services.
Data exploration - Data exploration is the process of examining a dataset to understand its structure, quality, patterns and limitations before drawing firm conclusions or...
Data extraction - Data extraction is the process of obtaining selected data from a source so it can be used elsewhere or in a later processing step.
Data fabric - A data fabric is an architectural approach for connecting and managing data across different systems through coordinated integration, metadata, governance...
Data farming - Data farming is the purposeful generation of data from simulation models through designed experiments.
Data-flow diagram - A data-flow diagram, or DFD, is a visual model of how information enters a system, moves through processes, reaches data stores and leaves for other people...
Data fusion - Data fusion combines information from multiple sources to form a joint estimate, representation, or assessment.
Data generating process - A data generating process, often abbreviated DGP, is the mechanism or probabilistic specification that produces observations.
Data Generation Bias - Data generation bias is a distortion introduced when synthetic or redundant examples are added to a dataset in ways that misrepresent the intended...
Data governance - Data governance is the system of decision rights, responsibilities, policies, and oversight through which an organization directs how its data is managed...
Data grid - A data grid is a distributed infrastructure that helps manage and access data held across multiple resources or locations.
Data hierarchy - Data hierarchy describes how smaller data components are organized into larger structures.
Data hub - A data hub is a shared point for discovering, accessing, exchanging or integrating data from multiple sources.
Data Imputation - Data imputation replaces missing values with estimates or specified substitutes so that incomplete records can be used in an analysis or machine-learning...
Data independence - Data independence is the ability to change how data is organized or stored while preserving the interfaces and behavior on which applications or users rely.
Data ingestion - Data ingestion is the process of bringing data from its sources into a destination where it can be stored or processed.
Data integrity - Data integrity is the condition in which data remains consistent with its intended content and applicable rules, and is protected against improper...
Data-intensive computing - Data-intensive computing is computing in which the amount, movement, organization or arrival rate of data is a major design challenge.
Data item - A data item is an identifiable unit of information that a system treats as a value or structured part of its data.
Data lake - A data lake is a repository designed to hold substantial amounts of data in varied formats, often including source data before it has been shaped for a...
Data Lakehouse - A data lakehouse is a data-platform architecture that combines the flexible storage approach of a data lake with database-style table management and...
Data leakage - Data leakage is when information from outside a model's legitimate training view, often the answer itself, slips into its inputs, making test results look...
Data lifecycle - The data lifecycle is the sequence of activities through which data is planned, obtained, processed, used, maintained, shared, preserved, and eventually...
Data loading - Data loading is the process of writing incoming data into a target system so it can be stored and used there.
Data management plan - A data management plan, often shortened to DMP, is a document describing how a project's data will be created or obtained, organized, protected, documented...
Data manipulation language - Data manipulation language, commonly abbreviated DML, is the part of a database language used to work with data held in existing database structures.
Data mart - A data mart is a collection of data organized for the analytical needs of a particular subject area, business function or group of users.
Data masking - Data masking conceals sensitive values by replacing or obscuring them while allowing an intended use of the resulting data.
Data matrix - A data matrix is a rectangular arrangement of data values used for analysis or learning.
Data minimization principle - The data minimization principle requires personal data to be sufficient and relevant for a defined purpose while limiting it to what that purpose needs.
Data mining - Data mining is the use of computational and statistical methods to discover patterns or build useful models from data.
Data model - A data model is a representation of how data is organized, what it means, how its elements relate and which rules apply.
Data Modeling - Data modeling is the process of designing and documenting how information should be represented, related and governed by rules.
Data normalization - Data normalization is the transformation of numerical data into a scale or form suitable for analysis or machine learning.
Data-oriented parsing - Data-oriented parsing, or DOP, is an approach to analyzing language by combining fragments of previously analyzed utterances.
Data parallelism - Data parallelism is a way of speeding up a computation by applying the same operation to different portions of data at the same time.
Data Partitioning - Data partitioning is dividing a dataset into defined portions so that storage, processing or management can operate on those portions.
Data philanthropy - Data philanthropy is the contribution of privately held data, access to those data, or insights derived from them to support a public-benefit purpose.
Data physicalization - Data physicalization represents data through the geometry or material properties of physical artifacts.
Data pipeline - A data pipeline is a defined sequence or network of steps that moves data from sources toward a usable destination, often transforming and checking it along...
Data point - A data point is one unit of information considered in an analysis or machine-learning task.
Data poisoning - Data poisoning is deliberate interference with data used by an AI system in order to cause unwanted behavior.