Cloud, Data, AI and Cybersecurity Glossary
Clear definitions of essential technology concepts.
All Definitions
C
Change Data Capture (CDC)
Change Data Capture (CDC) is a technique for identifying and capturing changes made to data in a source system, such as inserts, updates, and deletes, and delivering those changes to…
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Data Accuracy
Data accuracy is a data quality dimension that measures how correctly data represents the real-world objects, events, or conditions it describes. Accurate data reflects verified facts, such as a customer’s…
Read definition →Data Aggregation
Data aggregation is the process of collecting, grouping, and summarizing data to produce meaningful results for analysis and decision-making. It involves applying calculations such as sums, counts, averages, minimums, and…
Read definition →Data Analytics
Data analytics is the process of collecting, cleaning, transforming, and analyzing data to identify patterns, draw conclusions, and support informed decisions. It helps organizations understand what happened, investigate why it…
Read definition →Data Anonymization
Data anonymization is the process of modifying or removing personally identifiable information (PII) from a dataset so individuals cannot reasonably be identified from the remaining data. Common examples include removing…
Read definition →Data Backfill
Data backfill is the process of processing or loading historical data into a data system to fill gaps, restore missing records, or apply updated processing logic to previously collected information.…
Read definition →Data Cataloging
Data cataloging is the process of discovering, organizing, documenting, and classifying an organization’s data assets so people can find and understand the information they need. It creates a searchable inventory…
Read definition →Data Cleansing
Data cleansing is the process of identifying and correcting or removing inaccurate, incomplete, duplicate, outdated, or inconsistent data from a dataset. Also known as data cleaning or data scrubbing, it…
Data Completeness
Data completeness is a data quality dimension that measures whether a dataset contains all the information required for its intended purpose. It focuses on missing records, empty fields, incomplete attributes,…
Read definition →Data Consistency
Data consistency is a data quality dimension that describes whether information remains uniform and compatible across records, databases, applications, and systems. Consistent data follows agreed definitions, formats, relationships, and business…
Read definition →Data Decoding
Data decoding is the process of converting encoded data back into a form that an application, device, or person can interpret. It uses the rules of an encoding scheme to…
Read definition →Data Discoverability
Data discoverability is the ability to find, identify, and understand relevant data assets within an organization. It helps employees locate datasets, reports, dashboards, and other information resources without relying entirely…
Data Encoding
Data encoding is the process of converting data from one format or representation into another so it can be stored, transmitted, processed, or interpreted by a computer system. It uses…
Read definition →Data Enrichment
Data enrichment is the process of improving existing data by adding relevant information from internal or external sources. It fills gaps in datasets and provides additional context, such as customer…
Read definition →Data Export
Data export is the process of extracting data from a database, application, platform, or other source and saving it in a format that can be used outside the original system.…
Read definition →Data Federation
Data federation is a data integration approach that allows users to access, query, and combine data from multiple sources through a unified interface without necessarily moving all the underlying data…
Read definition →Data Filtering
Data filtering is the process of selecting, excluding, or narrowing down data based on predefined conditions to retain only the records or values relevant to a specific task. It helps…
Read definition →Data Flattening
Data flattening is the process of converting nested, hierarchical, or multi-level data structures into a simpler, flatter format that is easier to store, query, analyze, or exchange between systems. It…
Read definition →Data Freshness
Data freshness is a data quality dimension that describes how up to date data is relative to the time it was created, collected, updated, or expected to become available. Fresh…
Data Import
Data import is the process of bringing data from an external file, database, application, or platform into a target system. Organizations use data import to populate databases, transfer records between…
Read definition →Data Ingestion
Data ingestion is the process of collecting data from different sources and transferring it to a destination, such as a database, data warehouse, data lake, or analytics platform, for storage,…
Read definition →Data Integration
Data integration is the process of combining data from different sources into a unified, consistent view for analysis, reporting, and business operations. It connects information from databases, applications, APIs, files,…
Read definition →Data Integrity
Data integrity is the assurance that data remains accurate, consistent, complete where required, and protected from unauthorized or unintended changes throughout its lifecycle. It covers how information is collected, stored,…
Read definition →Data Masking
Data masking is the process of replacing or altering sensitive information so that its original values are concealed while the data remains useful for approved purposes. It helps protect personal,…
Data Migration
Data migration is the process of moving data from one system, database, storage environment, or application to another. It is commonly performed when organizations upgrade infrastructure, adopt cloud platforms, replace…
Read definition →Data Normalization
Data normalization is the process of organizing data to improve consistency, reduce redundancy, and make it easier to manage and analyze. In relational databases, it involves structuring data into related…
Read definition →Data Orchestration
Data orchestration is the process of coordinating and managing data workflows across multiple systems, tools, and processing stages. It determines when data tasks should run, which tasks depend on others,…
Read definition →Data Ownership
Data ownership is the assignment of accountability and decision-making authority for a dataset to a person, team, or business function within an organization. A data owner is responsible for defining…
Read definition →Data Parsing
Data parsing is the process of analyzing raw data and breaking it into structured components that applications can interpret and use. It converts input such as text, files, API responses,…
Read definition →Data Pipeline
A data pipeline is an automated sequence of processes that collects data from sources such as databases, APIs, business applications, files, and event streams, then moves it to a destination…
Read definition →Data Profiling
Data profiling is the process of examining a dataset to understand its structure, quality, completeness, and overall characteristics. It helps identify missing values, duplicate records, inconsistent formats, unusual patterns, and…
Read definition →Data Provenance
Data provenance is the record of where data originates, how it has been created or collected, and what happens to it throughout its lifecycle. It captures information about data sources,…
Read definition →Data Reconciliation
Data reconciliation is the process of comparing two or more datasets to identify and resolve discrepancies and ensure that data remains consistent across systems. It helps organizations verify that records,…
Read definition →Data Reliability
Data reliability is the degree to which data remains dependable and consistently available for its intended use. Reliable data can be accessed when needed, processed predictably, and trusted to meet…
Read definition →Data Replay
Data replay is the process of processing previously captured or stored data again to recover from failures, rebuild application state, validate processing logic, or reproduce past events. It is commonly…
Read definition →Data Replication
Data replication is the process of copying and maintaining data across multiple databases, servers, storage systems, or geographic locations so that the same information is available in more than one…
Read definition →Data Routing
Data routing is the process of directing data from a source to the appropriate destination based on predefined rules, conditions, metadata, or processing requirements. It is used in data pipelines,…
Read definition →Data Sampling
Data sampling is the process of selecting a subset of observations from a larger population or dataset to analyze patterns, estimate characteristics, or test assumptions without examining every record. It…
Read definition →Data Standardization
Data standardization is the process of converting data into consistent formats, structures, units, or statistical scales so that it can be compared, combined, and analyzed reliably. In data management, standardization…
Read definition →Data Stewardship
Data stewardship is the practice of managing, maintaining, and improving an organization’s data to ensure it remains accurate, consistent, secure, and usable. It involves assigning responsibility for data quality, defining…
Read definition →Data Streaming
Data streaming is the continuous flow of data generated by sources such as applications, databases, IoT devices, financial transactions, and website activity. Instead of waiting for data to accumulate into…
Read definition →Data Synchronization
Data synchronization is the process of keeping data consistent and up to date across two or more systems, applications, databases, or devices. It detects changes in one location and applies…
Read definition →Data Timeliness
Data timeliness is a data quality dimension that measures whether information is available when it is needed for a particular task, decision, or business process. Timely data reaches users or…
Read definition →Data Tokenization
Data tokenization is a data security technique that replaces sensitive information with a substitute value called a token. The token represents the original data without exposing it directly to the…
Read definition →Data Traceability
Data traceability is the ability to track data as it moves through systems, processes, and workflows, making it possible to determine where information originated, how it changed, and where it…
Read definition →Data Transcoding
Data transcoding is the process of converting data from one encoding, format, or representation into another so it can be used by a different application, device, platform, or system. It…
Read definition →Data Transfer
Data transfer is the process of moving data from one location, system, device, or application to another. It can involve transferring files, database records, application data, or continuous streams of…
Read definition →Data Transformation
Data transformation is the process of converting data from its original format, structure, or values into a form that meets the requirements of a target system or analytical task. It…
Read definition →Data Trustworthiness
Data trustworthiness is the degree to which data can be relied upon for a particular purpose based on its quality, origin, integrity, transparency, and suitability. Trustworthy data has clear provenance,…
Read definition →Data Validation
Data validation is the process of checking whether data meets predefined rules, formats, and requirements before it is stored, processed, or used for analysis. It helps identify invalid, incomplete, inconsistent,…
Read definition →Data Virtualization (Data Virtualisation)
Data virtualization is a data integration approach that provides a unified view of information stored across multiple data sources without requiring all the underlying data to be physically moved into…
Read definition →Data Wrangling
Data wrangling is the process of collecting, cleaning, structuring, and enriching raw data to make it suitable for analysis, reporting, and machine learning. Also known as data munging, it involves…
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ELT
ELT (Extract, Load, Transform) is a data integration process that extracts data from source systems, loads it into a target platform, and transforms it there for analysis and reporting. It…
Read definition →ETL
ETL (Extract, Transform, Load) is a data integration process that extracts data from one or more sources, transforms it into a suitable format, and loads it into a target system…
Read definition →R
Reverse ETL
Reverse ETL is the process of transferring cleaned, transformed, and modeled data from a data warehouse or lakehouse into operational applications such as CRM systems, marketing platforms, customer support tools,…
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