Module 04 · Data literacy for Data Science (Optional)
Glossary: Data Literacy for Data Science术语表：数据科学中的数据素养
Welcome! This alphabetized glossary contains many of the terms in this course. These terms are important for you to recognize when working in the industry, participating in user groups, and participating in other certificate programs.
欢迎！本按字母顺序排列的术语表包含了本课程中的许多术语。这些术语对于您在行业内工作、参与用户组以及参与其他证书项目时识别非常重要。
| Term 术语 | Definition 定义 | Video where the term is introduced 介绍该术语的视频 |
|---|---|---|
| ACID-compliance | Ensuring data accuracy and consistency through Atomicity, Consistency, Isolation, and Durability (ACID) in database transactions. 通过数据库事务中的原子性（Atomicity）、一致性（Consistency）、隔离性（Isolation）和持久性（Durability）（ACID）确保数据准确性和一致性。 |
Relational Database Management System 关系型数据库管理系统 |
| Cloud-based Integration Platform as a Service (iPaaS) 基于云的集成平台即服务(iPaaS) |
Cloud-hosted integration platforms that offer integration services through virtual private clouds or hybrid cloud models, providing scalability and flexibility. 基于云的集成平台，通过虚拟私有云或混合云模型提供集成服务，具有可扩展性和灵活性。 |
Data Integration Platforms 数据集成平台 |
| Column-based Database 列式数据库 | A type of NoSQL database that organizes data in cells grouped as columns, often used for systems requiring high write request volume and storage of time-series or IoT data. 一种 NoSQL 数据库，将数据组织为列组中的单元格，常用于需要高写入请求量以及存储时间序列或物联网数据的系统。 |
NoSQL |
| Data at rest 静态数据 | Data that is stored and not actively in motion, typically residing in a database or storage system for various purposes, including backup. 指已存储且未处于活跃状态的数据，通常存在于数据库或存储系统中，用于各种目的，包括备份。 |
Considerations for Choice of Data Repository 数据存储库选择考量因素 |
| Data integration 数据集成 | A discipline involving practices, architectural techniques, and tools that enable organizations to ingest, transform, combine, and provision data across various data types, used for purposes such as data consistency, master data management, data sharing, and data migration. 一个涉及实践、架构技术和工具的学科，使组织能够摄取、转换、组合和提供跨各种数据类型的数据，用于数据一致性、主数据管理、数据共享和数据迁移等目的。 |
Data Integration Platforms 数据集成平台 |
| Data Lake 数据湖 | A data repository for storing large volumes of structured, semi-structured, and unstructured data in its native format, facilitating agile data exploration and analysis. 一个用于存储大量结构化、半结构化和非结构化数据的数据存储库，以原生格式保存，促进敏捷数据探索和分析。 |
Data Marts, Data Lakes, ETL, and Data Pipelines 数据集市、数据湖、ETL 和数据管道 |
| Data mart 数据集市 | A subset of a data warehouse designed for specific business functions or user communities, providing isolated security and performance for focused analytics. 一个为特定业务功能或用户群体设计的仓库子集，提供隔离的安全性和性能，以支持专注的分析。 |
Data Marts, Data Lakes, ETL, and Data Pipelines 数据集市、数据湖、ETL 和数据管道 |
| Data pipeline 数据管道 | A comprehensive data movement process that covers the entire journey of data from source systems to destination systems, which includes data integration as a key component. 一个全面的数据移动过程，涵盖了数据从源系统到目标系统的整个旅程，其中包括数据集成作为关键组成部分。 |
Data Integration Platforms 数据集成平台 |
| Data repository 数据存储库 | A general term referring to data that has been collected, organized, and isolated for business operations or data analysis. It can include databases, data warehouses, and big data stores. 一个通用术语，指为业务运营或数据分析而收集、组织和隔离的数据。它可以包括数据库、数据仓库和大数据存储。 |
Data Collection and Organization Data Collection 和组织 |
| Data warehouse 数据仓库 | A central repository that consolidates data from various sources through the Extract, Transform, and Load (ETL) process, making it accessible for analytics and business intelligence. 一个中央存储库，通过提取、转换和加载（ETL）流程整合来自各种来源的数据，使其可用于分析和商业智能。 |
Data Collection and Organization Data Collection 和组织 |
| Document-based Database 基于文档的数据库 | A type of NoSQL database that stores each record and its associated data within a single document, allowing flexible indexing, ad hoc queries, and analytics over collections of documents. 一种 NoSQL 数据库，将每条记录及其相关数据存储在单个文档中，允许灵活的索引、临时查询和跨文档集合的分析。 |
NoSQL |
| ETL process ETL 过程 | The Extract, Transform, and Load process for data integration involves extracting data from various sources, transforming it into a usable format, and loading it into a repository. 数据集成中的提取、转换和加载（ETL）过程涉及从各种来源提取数据，将其转换为可用格式，并将其加载到存储库中。 |
Data Marts, Data Lakes, ETL, and Data Pipelines 数据集市、数据湖、ETL 和数据管道 |
| Graph-based Database 基于图的数据库 | A type of NoSQL database that uses a graphical model to represent and store data, ideal for visualizing, analyzing, and discovering connections between interconnected data points. 一种使用图形模型来表示和存储数据的 NoSQL 数据库，适用于可视化、分析和发现相互连接的数据点之间的联系。 |
NoSQL |
| Key-value store 键值存储 | A type of NoSQL database where data is stored as key-value pairs, with the key serving as a unique identifier and the value containing data, which can be simple or complex. 一种将数据存储为键值对的非关系型数据库，其中键作为唯一标识符，值包含数据，可以是简单的也可以是复杂的。 |
NoSQL 非关系型数据库 |
| Portability 可移植性 | The capability of data integration tools to be used in various environments, including single-cloud, multi-cloud, or hybrid-cloud scenarios, provides flexibility in deployment options. 数据集成工具在各种环境中（包括单云、多云或混合云场景）的使用能力，为部署选项提供了灵活性。 |
Data Integration Platforms 数据集成平台 |
| Pre-built connectors 预构建的连接器 | Cataloged connectors and adapters that simplify connecting and building integration flows with diverse data sources like databases, flat files, social media, APIs, CRM, and ERP applications. 已编目连接器和适配器，可简化与数据库、平面文件、社交媒体、API、CRM 和ERP 应用程序等多样化数据源连接和构建集成流程。 |
Data Integration Platforms 数据集成平台 |
| Relational databases (RDBMSes) 关系数据库（RDBMS） |
Databases that organize data into a tabular format with rows and columns, following a well-defined structure and schema. 将数据组织成具有行和列的表格格式，遵循明确定义的结构和模式的数据库。 |
Data Collection and Organization Data Collection 和组织 |
| Scalability 可扩展性 | The ability of a data repository to grow and expand its capacity to handle increasing data volumes and workload demands over time. 一个数据存储库随着时间的推移增长和扩展其处理不断增长的数据量和工作负载需求的能力。 |
Considerations for Choice of Data Repository 数据存储库选择考虑因素 |
| Schema 模式 | The predefined structure that describes the organization and format of data within a database, indicating the types of data allowed and their relationships. 预定义的结构，描述数据库中数据的组织格式，指示允许的数据类型及其关系。 |
Considerations for Choice of Data Repository 选择数据存储库的考虑因素 |
| Streaming data 流式数据 | Data that is continuously generated and transmitted in real-time requires specialized handling and processing to capture and analyze. 连续实时生成和传输的数据需要专门的处理和加工才能捕获和分析。 |
Considerations for Choice of Data Repository 选择数据存储库的考虑因素 |
| Use cases for relational databases 关系型数据库的应用场景 |
Applications such as Online Transaction Processing (OLTP), Data Warehouses (OLAP), and IoT solutions where relational databases excel. 在线事务处理 (OLTP)、数据仓库 (OLAP) 和物联网解决方案等关系型数据库表现优异的应用。 |
Relational Database Management System 关系型数据库管理系统 |
| Vendor lock-in 供应商锁定 | A situation where a user becomes dependent on a specific vendor's technologies and solutions, making it challenging to switch to other platforms. 用户对特定供应商的技术和解决方案产生依赖，导致难以切换到其他平台的情况。 |
Data Integration Platforms 数据集成平台 |