Metadata and Metadata Management 元数据与元数据管理

Objectives 目标

After completing this reading, you will be able to:
完成本阅读后，您将能够：

• Define what metadata is  定义元数据是什么
• Describe what metadata management is
  描述元数据管理是什么
• Explain the importance of metadata management
  解释元数据管理的重要性
• List popular tools for metadata management
  列出流行的元数据管理工具

What is metadata? 什么是元数据？

Metadata is data that provides information about other data.
元数据是提供其他数据信息的那些数据。

This is a very broad definition. Here we will consider the concept of metadata within the context of databases, data warehousing, business intelligence systems, and all kinds of data repositories and platforms.
这是一个非常广泛的定义。在这里，我们将考虑数据库、数据仓库、商业智能系统以及各种数据存储库和平台中的元数据概念。

We'll consider the following three main types of metadata:
我们将考虑以下三种主要的元数据类型：

• Technical metadata  技术元数据
• Process metadata, and  流程元数据，和
• Business metadata  业务元数据

Technical metadata 技术元数据

Technical metadata is metadata which defines the data structures in data repositories or platforms, primarily from a technical perspective.
技术元数据是指定义数据仓库或平台中数据结构的元数据，主要从技术角度出发。

For example, technical metadata in a data warehouse includes assets such as:
例如，数据仓库中的技术元数据包括以下资产：

• Tables that record information about the tables stored in a database, like:
  记录数据库中存储的表信息的表，例如：
  • each table's name  每个表的名字
  • the number of columns and rows each table has
    每张表拥有的列数和行数
• A data catalog, which is an inventory of tables that contain information, like:
  一个数据目录，它是一份包含信息的表清单，例如：
  • the name of each database in the enterprise data warehouse
    企业数据仓库中每个数据库的名称
  • the name of each column present in each database
    每个数据库中每个列的名称
  • the names of every table that each column is contained in
    每个列包含的每个表的名称
  • the type of data that each column contains
    每列包含的数据类型

The technical metadata for relational databases is typically stored in specialized tables in the database called the System Catalog.
关系数据库的技术元数据通常存储在数据库中的专用表中，称为系统目录。

Process metadata 处理元数据

Process metadata describes the processes that operate behind business systems such as data warehouses, accounting systems, or customer relationship management tools.
流程元数据描述了在业务系统（如数据仓库、会计系统或客户关系管理工具）背后运行的流程。

Many important enterprise systems are responsible for collecting and processing data from various sources. Such critical systems need to be monitored for failures and any performance anomalies that arise. Process metadata for such systems includes tracking things like:
许多重要的企业系统负责从各种来源收集和处理数据。这些关键系统需要被监控以检测故障和任何性能异常。此类系统的流程元数据包括跟踪诸如以下内容：

• process start and end times
  流程开始和结束时间
• disk usage  磁盘使用情况
• where data was moved from and to, and
  数据从何地移动到何地，以及
• how many users access the system at any given time
  在任何给定时间有多少用户访问系统

This sort of data is invaluable for troubleshooting and optimizing workflows and ad hoc queries.
此类数据对于故障排除、优化工作流程和临时查询具有不可估量的价值。

Business metadata 业务元数据

Users who want to explore and analyze data within and outside the enterprise are typically interested in data discovery. They need to be able to find data which is meaningful and valuable to them and know where that data can be accessed from. These business-minded users are thus interested in business metadata, which is information about the data described in readily interpretable ways, such as:
想要探索和分析企业内外数据的用户通常对数据发现感兴趣。他们需要能够找到对他们有意义和有价值的数据，并知道这些数据可以从哪里访问。因此，这些具有商业意识的用户对业务元数据感兴趣，业务元数据是以易于理解的方式描述数据的信息，例如：

• how the data is acquired
  数据的获取方式
• what the data is measuring or describing
  数据所测量或描述的内容
• the connection between the data and other data sources
  数据与其他数据源之间的联系

Business metadata also serves as documentation for the entire data warehouse system.
业务元数据也作为整个数据仓库系统的文档。

Managing metadata 管理元数据

Managing metadata includes developing and administering policies and processes to ensure information can be accessed and integrated from various sources and appropriately shared across the entire enterprise.
管理元数据包括制定和管理政策与流程，以确保信息能够从各种来源获取和集成，并在整个企业中适当共享。

Creation of a reliable, user-friendly data catalog is a primary objective of a metadata management model. The data catalog is a core component of a modern metadata management system, serving as the main asset around which metadata management is administered. It serves as the basis by which companies can inventory and efficiently organize their data systems. A modern metadata management model will include a web-based user interface that enables engineers and business users to easily search for and find information on key attributes such as CustomerName or ProductType. This kind of model is central to any Data Governance initiative.
创建一个可靠、用户友好的数据目录是元数据管理模型的主要目标。数据目录是现代元数据管理系统的一个核心组件，作为元数据管理的主要资产进行管理。它为公司提供了基础，以便他们能够清点和高效组织其数据系统。现代元数据管理模型将包括一个基于网络的用户界面，使工程师和业务用户能够轻松搜索和查找关于客户名称或产品类型等关键属性的信息。这种模型是任何数据治理计划的核心。

Why is metadata management important? 为什么元数据管理很重要？

Good metadata management has many valuable benefits. Having access to a well implemented data catalog greatly enhances data discovery, repeatability, governance, and can also facilitate access to data.
良好的元数据管理具有许多宝贵的优势。能够访问一个实施良好的数据目录可以极大地增强数据发现、可重复性、治理，并也能促进数据访问。

Well managed metadata helps you to understand both the business context associated with the enterprise data and the data lineage, which helps to improve data governance. Data lineage provides information about the origin of the data and how it gets transformed and moved, and thus it facilitates tracing of data errors back to their root cause. Data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data, and data controls are implemented that support business objectives.
良好的元数据管理有助于您理解与企业数据相关的业务背景和数据血缘关系，这有助于改进数据治理。数据血缘关系提供了关于数据来源以及数据如何被转换和移动的信息，因此它有助于将数据错误追溯到其根本原因。数据治理是一个数据管理概念，它涉及使组织能够确保在整个数据生命周期中存在高质量数据的能力，并实施支持业务目标的数据控制。

The key focus areas of data governance include availability, usability, consistency, data integrity and data security and includes establishing processes to ensure effective data management throughout the enterprise such as accountability for the adverse effects of poor data quality and ensuring that the data which an enterprise has can be used by the entire organization.
数据治理的关键关注领域包括可用性、可用性、一致性、数据完整性和数据安全，并包括建立流程以确保在整个企业中有效管理数据，例如对数据质量差产生的不利影响负责，并确保企业拥有的数据可以被整个组织使用。

Popular tools for metadata management 元数据管理的流行工具

Popular metadata management tools include:
流行的元数据管理工具包括：

• IBM InfoSphere Information Server
• CA Erwin Data Modeler  CA Erwin 数据模型器
• Oracle Warehouse Builder  Oracle 仓库构建器
• SAS Data Integration Server
  SAS 数据集成服务器
• Talend Data Fabric  Talend 数据构造平台
• Alation Data Catalog  Alation 数据目录
• SAP Information Steward  SAP 信息管理员
• Microsoft Azure Data Catalog
  Microsoft Azure 数据目录
• IBM Watson Knowledge Catalog
  IBM Watson 知识目录
• Oracle Enterprise Metadata Management (OEMM)
  甲骨文企业元数据管理 (OEMM)
• Adaptive Metadata Manager
  自适应元数据管理器
• Unifi Data Catalog  统一数据目录
• data.world
• Informatica Enterprise Data Catalog
  Informatica 企业数据目录

Summary 摘要

In this reading, you learned that:
在本阅读中，你学习了：

• Metadata is data that provides information about other data, and includes three main types: technical, process, and business metadata
  元数据是提供其他数据信息的那些数据，包括三种主要类型：技术元数据、流程元数据和业务元数据
• The technical metadata for relational databases is typically stored in specialized tables in the database called the system catalog
  关系型数据库的技术元数据通常存储在数据库中的专用表中，称为系统目录
• A primary objective of business metadata management modelling is the creation and maintenance of a reliable, user-friendly data catalog
  业务元数据管理建模的主要目标之一是创建和维护一个可靠、用户友好的数据目录
• Having access to a well-implemented data catalog greatly enhances data discovery, repeatability, governance, and can also facilitate access to data
  能够访问一个实施良好的数据目录可以极大地提升数据发现、可重复性、治理，并且还可以促进数据访问
• Metadata management tools from IBM include InfoSphere Information Server and Watson Knowledge Catalog
  IBM 的元数据管理工具包括 InfoSphere Information Server 和 Watson Knowledge Catalog