Big Data Terms Glossary: Big Data Terms in 2024
B
Big Data
Big Data refers to large and complex datasets that cannot be easily handled using traditional data processing tools.
Business Intelligence
Business Intelligence (BI) refers to the technologies, applications, and practices used for analyzing data to provide actionable insights for informed decision-making.
C
Cloud Computing
Cloud Computing is the delivery of computing services, including storage, processing power, and applications, over the internet.
D
Data Access Control
Data Access Control refers to the mechanisms and policies used to regulate and control access to data, ensuring only authorized users can view or use the data.
Data Analyst
A Data Analyst is a professional who collects, analyzes, and interprets large datasets, using statistical techniques and tools to identify trends, patterns, and insights.
Data Analytics
Data Analytics is the process of examining, transforming, and organizing data to discover useful insights and draw conclusions.
Data Anonymization
Data Anonymization involves modifying or removing personally identifiable information from datasets to ensure the protection of privacy and compliance with data protection regulations.
Data Architecture
Data Architecture refers to the design, structure, and organization of data within an information system, including the data models, schemas, and storage strategies.
Data Archiving
Data Archiving is the process of moving data from the active storage systems to separate long-term storage for retention and compliance purposes.
Data Backup
Data Backup is the process of creating copies or replicas of data to protect against data loss, corruption, or system failures.
Data Bias
Data Bias refers to the presence of systematic errors or prejudices in data that can influence the results or outcomes of data analysis or machine learning models.
Data Breach
A Data Breach is an incident where sensitive, confidential, or protected data is accessed or disclosed without authorization.
Data Breach Response
Data Breach Response refers to the actions and processes followed to address and mitigate the impact of a data breach, including investigation, notification, and recovery.
Data Catalog
A Data Catalog is a centralized inventory or index of data assets within an organization, providing metadata and information on available datasets.
Data Center
A Data Center is a facility used to house computer systems, servers, networking, storage, and other IT resources for the purpose of storing, processing, and managing large amounts of data.
Data Classification
Data Classification is the process of categorizing data based on its sensitivity, value, and criticality to enable appropriate data protection and access controls.
Data Cleansing
Data Cleansing, also known as data scrubbing or data cleaning, is the process of identifying and fixing or removing errors, inconsistencies, and inaccuracies from datasets.
Data Cleansing Tools
Data Cleansing Tools are software applications or platforms used to automate and streamline the process of identifying and fixing errors or inconsistencies in datasets.
Data Compression
Data Compression is the process of reducing the size of data to save space or bandwidth while maintaining its essential information.
Data De-Identification
Data De-identification is the process of removing or modifying personally identifiable information from datasets to ensure the protection of privacy and compliance with data protection regulations.
Data Deduplication
Data Deduplication is the process of identifying and removing duplicate or redundant data entries or records within a dataset.
Data Encryption
Data Encryption is the process of transforming data into a format that is unreadable without the decryption keys, ensuring the confidentiality of data.
Data Engineer
A Data Engineer is a professional responsible for designing, building, and managing the infrastructure and systems used for storing, processing, and analyzing Big Data.
Data Federation
Data Federation is the process of integrating and combining data from multiple sources in real-time or near-real-time to create a virtual view for analysis and reporting purposes.
Data Fusion
Data Fusion is the process of combining data from multiple sources and integrating it into a unified dataset to enable comprehensive analysis and decision-making.
Data Governance
Data Governance refers to the overall management and control of data within an organization, including policies, procedures, and standards for data management.
Data Governance Council
A Data Governance Council is a group of individuals within an organization responsible for defining and implementing data governance policies, procedures, and standards.
Data Governance Framework
A Data Governance Framework is a structured and organized approach for establishing and maintaining data governance within an organization, defining roles, responsibilities, and processes.
Data Governance Officer
A Data Governance Officer is a role responsible for overseeing the implementation and adherence to data governance policies and practices within an organization.
Data Governance Policy
A Data Governance Policy is a document that outlines the rules, principles, and guidelines for managing and using data within an organization.
Data Ingestion
Data Ingestion refers to the process of importing, collecting, and loading data from various sources into a storage or processing system.
Data Integration
Data Integration is the process of combining data from different sources or systems into a unified and coherent view.
Data Lake
A Data Lake is a storage repository that holds a vast amount of raw and unstructured data in its native format until it is needed.
Data Lake Analytics
Data Lake Analytics refers to the techniques and tools used to process, analyze, and derive insights from the data stored in a Data Lake.
Data Lake Architecture
Data Lake Architecture refers to the design and organization of a Data Lake, including the storage, processing, and access methods for the data.
Data Lake Governance
Data Lake Governance is the process of establishing policies, controls, and standards for the management and usage of data within a Data Lake.
Data Lake Governance Tools
Data Lake Governance Tools are software applications or platforms used to enforce and implement data governance policies, processes, and controls within a Data Lake.
Data Lake Management
Data Lake Management involves the administration, optimization, and maintenance of a Data Lake, including data ingestion, organization, and access control.
Data Lake Security
Data Lake Security involves implementing safeguards, controls, and measures to protect the data stored within a Data Lake against unauthorized access, misuse, or breaches.
Data Lineage
Data Lineage is the record or history of the movement and transformation of data, showing its origins, transformations, and where it is used or consumed.
Data Loss
Data Loss refers to the accidental or intentional destruction, corruption, or deletion of data, resulting in its permanent or partial unavailability or irretrievability.
Data Loss Prevention
Data Loss Prevention refers to the strategies, technologies, and practices employed to prevent the accidental or intentional loss, theft, or exposure of sensitive data.
Data Mart
A Data Mart is a subset of a data warehouse that is focused on a specific department, function, or business area, providing tailored data and analytics capabilities.
Data Mart Architecture
Data Mart Architecture refers to the design and structure of a data mart, including the source data, data models, and storage methods for the mart.
Data Masking
Data Masking is the process of replacing sensitive or confidential data with realistic but fictional or scrambled data to protect sensitive information from unauthorized access or exposure.
Data Migration
Data Migration is the process of transferring data from one system or storage location to another.
Data Mining
Data Mining is the process of discovering patterns, trends, and insights from large datasets using statistical methods and machine learning techniques.
Data Mining Algorithms
Data Mining Algorithms are mathematical or computational methods used to identify, classify, and analyze patterns, relationships, and clusters within large datasets.
Data Mining Techniques
Data Mining Techniques refer to the algorithms, methods, and approaches used to discover patterns, relationships, and insights from large datasets.
Data Modeling
Data Modeling is the process of creating a conceptual, logical, or physical representation of data, using diagrams, schemas, or other modeling techniques.
Data Owner
A Data Owner is an individual or entity responsible for the overall management and accountability of specific datasets within an organization.
Data Pipeline
A Data Pipeline is a set of processes, tools, and technologies used to collect, transform, and move data from multiple sources to a target destination for analysis or storage.
Data Privacy
Data Privacy refers to the protection of sensitive and personal data, ensuring that it is collected, stored, and used in a secure and confidential manner.
Data Privacy Impact Assessment
A Data Privacy Impact Assessment is a systematic evaluation of the potential risks and impacts that data processing activities may have on individuals' privacy rights and freedoms.
Data Privacy Regulations
Data Privacy Regulations are legal frameworks and guidelines that govern the collection, storage, processing, and sharing of personal and sensitive data.
Data Profiling
Data Profiling is the process of analyzing and evaluating the quality, completeness, accuracy, and consistency of data, often in preparation for data integration or migration.
Data Profiling Tools
Data Profiling Tools are software applications or platforms used to automate the process of analyzing and evaluating the quality and characteristics of data.
Data Quality
Data Quality refers to the accuracy, completeness, consistency, and reliability of data, ensuring it is fit for its intended use.
Data Replication
Data Replication is the process of creating and maintaining multiple copies of data in different locations or systems, ensuring redundancy and data availability.
Data Retention
Data Retention refers to the policies and practices governing the storage, archiving, and deletion of data based on legal, regulatory, and business requirements.
Data Scalability
Data Scalability refers to the ability of a system or architecture to handle increasing amounts of data without sacrificing performance.
Data Science
Data Science is an interdisciplinary field that combines scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Data Scientist
A Data Scientist is a professional who uses scientific methods, algorithms, and data analysis tools to extract insights and knowledge from data, and to solve complex problems.
Data Security
Data Security refers to the protection of data against unauthorized access, use, disclosure, disruption, modification, or destruction.
Data Silo
A Data Silo refers to a situation where data is stored and managed in isolated systems or departments, hindering data sharing, integration, and collaboration.
Data Silos
Data Silos refer to isolated and separate data repositories or systems within an organization that hinder data sharing, integration, and collaboration.
Data Sovereignty
Data Sovereignty refers to the concept that data is subject to the laws, regulations, and jurisdiction of the country where it resides or is stored.
Data Steward
A Data Steward is an individual or team responsible for ensuring the quality, integrity, and compliance of data assets within an organization.
Data Stewardship
Data Stewardship involves the planning, implementation, and monitoring of policies and processes for the optimal use, security, and integrity of data.
Data Storage
Data Storage is the process of storing data in various forms, such as databases, data warehouses, or cloud storage systems.
Data Strategy
Data Strategy is a comprehensive plan that outlines the organization's goals, objectives, principles, and processes related to the management, governance, and utilization of data.
Data Stream Processing
Data Stream Processing is the real-time processing of continuous data streams, allowing for immediate analysis and decision-making based on up-to-date information.
Data Transfer
Data Transfer refers to the movement or transmission of data from one location or system to another, often involving large datasets or network transfers.
Data Transformation
Data Transformation refers to the process of converting or mapping data from one format or structure to another, often for the purpose of integrating or loading into a target system.
Data Transformation Tools
Data Transformation Tools are software applications or platforms used to automate and streamline the process of converting data from one format or structure to another.
Data Virtualization
Data Virtualization is a technology that allows data from different sources and formats to be accessed and integrated in real-time, without the need for physical consolidation or replication.
Data Visualization
Data Visualization is the graphical representation of data and information, using visual elements such as charts, graphs, and maps to enable better understanding and analysis.
Data Warehouse
A Data Warehouse is a large and centralized repository that stores data from different sources for reporting and analysis purposes.
Data Warehouse Architecture
Data Warehouse Architecture refers to the design and structure of a data warehouse, including the organization, storage, and retrieval methods for the data.
Data Warehouse Governance
Data Warehouse Governance refers to the practices, policies, and processes used to ensure the quality, integrity, and security of data within a data warehouse.
Data Warehouse Modeling
Data Warehouse Modeling is the process of designing and creating the structure, schema, and relationships within a data warehouse to support effective data storage and retrieval.
Data Warehousing
Data Warehousing is the process of gathering, storing, and managing data from various sources to support business intelligence and reporting activities.
Data-Driven Decision Making
Data-driven Decision Making refers to the process of making informed decisions based on data analysis, rather than relying on intuition or personal judgment.
Deep Learning
Deep Learning is a subset of machine learning that uses artificial neural networks with multiple layers to extract high-level representations and patterns from complex data.
E
Etl
ETL stands for Extract, Transform, and Load. It refers to the process of extracting data from various sources, transforming it to fit the target system, and loading it into a data warehouse or other storage systems.
H
Hadoop
Hadoop is an open-source framework that enables distributed processing and storage of large datasets across clusters of commodity hardware.
I
Internet Of Things
The Internet of Things refers to the network of physical devices, vehicles, appliances, and other objects embedded with sensors, software, and connectivity, enabling them to collect, exchange, and analyze data.
Iot
Internet of Things (IoT) refers to the network of physical devices, vehicles, appliances, and other objects embedded with sensors, software, and connectivity, enabling them to collect and exchange data.
M
Machine Learning
Machine Learning is a field of study that focuses on using algorithms and statistical models to enable computers to learn from data and make predictions or decisions.
Mapreduce
MapReduce is a programming model and framework used to process and analyze large datasets in parallel across a distributed cluster of computers.
N
Natural Language Processing
Natural Language Processing (NLP) is a branch of AI that deals with the interaction between human language and computers, enabling machines to understand, interpret, and generate human language.
Nosql
NoSQL, or 'not only SQL,' is a type of database management system that provides a flexible and scalable approach to storing and retrieving unstructured and semi-structured data.
P
Performance Tuning
Performance Tuning involves optimizing the performance and efficiency of data processing systems or applications to enhance their speed, scalability, and responsiveness.
Predictive Analytics
Predictive Analytics is the practice of using historical and real-time data to make predictions and forecasts about future events or outcomes.
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Real-Time Analytics
Real-time Analytics refers to the analysis of data as soon as it becomes available, allowing for immediate insights and actions based on up-to-date information.
Real-Time Data
Real-time Data refers to data that is received, processed, and analyzed immediately or near-instantaneously upon its capture, enabling immediate action.
S
Scalability
Scalability is the ability of a system, application, or infrastructure to handle increasing amounts of data, users, and workload without compromising performance or responsiveness.
Semi-Structured Data
Semi-Structured Data refers to data that has some organizational structure but does not fit neatly into traditional relational databases or structured formats, often containing tags, labels, or attributes.
Spark
Spark is a fast and general-purpose cluster computing system that provides in-memory processing capabilities for big data analytics.
Sql
SQL, or Structured Query Language, is a standard language for managing relational databases, used for storing, manipulating, and retrieving data.
Streaming Data
Streaming Data refers to the continuous and real-time flow of data from various sources, allowing for immediate processing, analysis, and response.
Structured Data
Structured Data refers to data that is organized and stored in a fixed format, such as a table, with a predefined schema, allowing for easy storage, retrieval, and analysis.
U
Unstructured Data
Unstructured Data refers to data that does not have a predefined format or organization, such as text documents, images, videos, and social media posts, requiring special processing techniques for analysis.