Reading: Data Manager阅读：数据经理

Estimated Duration: 15 minutes
预计时长：15 分钟

Objectives 目标

• Explain typical data-related roles in enterprise organizations
  解释企业组织中典型的数据相关角色
• Map the level, placement, and relationships between roles within a typical company’s organizational structure
  描绘典型公司组织结构中各角色的级别、位置和关系
• Categorize the roles into technical, analysis and insight, governance, and leadership
  将角色分为技术、分析与洞察、治理和领导力
• Describe the expected impacts AI may have on these roles
  描述人工智能可能对这些角色产生的影响

Technical roles 技术角色

Data-related technical roles focus on infrastructure, architecture, and machine learning. They typically require programming skills, knowledge of databases, and adept handling of large datasets. These roles include data engineer, machine learning engineer, and database administrator (DBA).
数据相关的技术角色侧重于基础设施、架构和机器学习。它们通常需要编程技能、数据库知识以及熟练处理大型数据集的能力。这些角色包括数据工程师、机器学习工程师和数据库管理员 (DBA)。

To get started in these roles, you should consider an entry-level role in data engineering. This will familiarize you with the data ecosystem, where you work with data pipelines and maintain infrastructure under the direction of a more senior-level data engineer.
要胜任这些职位，您应该考虑从数据工程的入门级职位开始。这将使您熟悉数据生态系统，在其中您将在高级数据工程师的指导下处理数据管道并维护基础设施。

Machine learning engineers develop machine learning algorithms and models, assessing the most appropriate models for your data. A database administrator’s responsibilities include managing and maintaining a database to ensure performance and security.
机器学习工程师开发机器学习算法和模型，评估最适合您数据的模型。数据库管理员的职责包括管理和维护数据库，以确保性能和安全性。

AI impact on technical roles 人工智能对技术职位的影响

Regarding how AI may affect technical data roles, you can expect AI will automate routine tasks and AI tools will assist in optimizing code. AI will allow you to focus on higher-level tasks such as designing and integrating AI components into infrastructures to ensure components work as expected.
关于人工智能可能如何影响技术数据职位，您可以预期人工智能将自动化日常任务，人工智能工具将协助优化代码。人工智能将使您能够专注于更高级别的任务，例如设计人工智能组件并将其集成到基础设施中，以确保组件按预期工作。

Analytical roles 分析角色

Another category of data-related roles includes analyzing data and providing insights based on your analysis. In these roles, you will explore collected data to identify insights from your data.
另一类与数据相关的角色包括分析数据并根据分析提供见解。在这些角色中，您将探索收集到的数据，以从中发现见解。

Data analysts and data scientists play roles in analysis. Analysts usually report to a data scientist and create visualizations, dashboards, and reports under the scientist’s direction. As a data scientist, you will bear the responsibility of leading the team and its direction by applying statistical techniques and crafting the stories they find in the data. Data scientists bear the responsibility of effectively championing their recommendations of their team’s findings to others in the organization.
数据分析师和数据科学家在分析中扮演着重要角色。分析师通常向数据科学家汇报，并在数据科学家的指导下创建可视化、仪表板和报告。作为数据科学家，您将通过应用统计技术和讲述团队在数据中发现的故事，承担领导团队及其方向的责任。数据科学家有责任有效地向组织中的其他人推销其团队发现的建议。

AI impact on analytical roles 人工智能对分析角色的影响

You can expect AI will certainly automate many aspects, but the role will need to craft and tell coherent, compelling stories with that data and how to utilize these insights best.
您可以预见，人工智能必将实现许多方面的自动化，但该职位仍需利用这些数据以及如何最好地利用这些洞察力来撰写和讲述连贯、引人入胜的故事。

Governance and privacy roles 治理和隐私角色

Regarding data governance and privacy, these related roles ensure that data collection, storage, and comply with legal, ethical, and organizational standards. Roles include data governance associate, data steward, compliance specialist, governance manager, data ethics steward, and data privacy officer. For an entry-level role, you should target a data governance associate who supports governance by developing documentation and ensuring data quality.
关于数据治理和隐私，这些相关角色确保数据收集、存储和使用符合法律、道德和组织标准。这些角色包括数据治理助理、数据管理员、合规专员、治理经理、数据伦理管理员和数据隐私官。对于入门级职位，您应该瞄准数据治理助理，他们通过开发文档和确保数据质量来支持治理。

Data governance entails establishing and complying with the regulations and standards that direct how the business uses and manages its data, including legal issues. It ensures data integrity and security by developing and enforcing policies. Roles in data governance include the governance manager, data governance associate, and compliance specialist.
数据治理包括建立和遵守指导企业如何使用和管理其数据（包括法律问题）的法规和标准。它通过制定和执行政策来确保数据完整性和安全性。数据治理中的角色包括治理经理、数据治理助理和合规专员。

Data stewards ensure data quality, integrity, and proper management. They ensure their data is secure and handled in accordance with company policies related to data. Data stewards ensure AI models do not introduce bias or encourage misuse and promote responsible data use. Data ethics stewards ensure that the business handles its data ethically for transparency and accountability beyond compliance. Data stewardship tends toward more technical issues, whereas an ethics steward ensures that data practices align with societal values and ethical principles.
数据管理员确保数据质量、完整性和适当管理。他们确保数据安全并按照公司数据相关政策进行处理。数据管理员确保人工智能模型不会引入偏见或鼓励滥用，并促进负责任的数据使用。数据伦理管理员确保企业以符合道德的方式处理数据，以实现超越合规的透明度和问责制。数据管理倾向于处理更技术性的问题，而伦理管理员则确保数据实践符合社会价值观和伦理原则。

AI impact on governance and privacy roles 人工智能对治理和隐私角色的影响

As AI adoption and integration mature, the data governance field will likely grow rapidly as industries endeavor to understand the quickly changing laws, policies, and the data landscape. AI itself can likely help monitor established policies and flag issues, freeing humans to focus on strategy alignment with business objectives, ethics, and regulations.
随着人工智能的采用和整合日趋成熟，数据治理领域可能会迅速发展，因为各行业都在努力理解快速变化的法律、政策和数据格局。人工智能本身很可能有助于监控既定政策并标记问题，从而使人类能够专注于与业务目标、道德和法规保持一致的战略。

Leadership roles and AI impact on leadership roles 领导角色和人工智能对领导角色的影响

Data leadership roles include data architect, chief data officer, and data ethics officer. All of these roles help establish the vision and missions with respect to their particular area of expertise. These thought leaders set data policy for the business and ensure alignment with these directives throughout the organization. They will be the ones making decisions about how, where, and why AI should be used in their organizations. Ultimately, these leadership roles will determine the impact AI will have on their businesses.
数据领导角色包括数据架构师、首席数据官和数据伦理官。所有这些角色都有助于在各自的专业领域内确立愿景和使命。这些思想领袖为企业制定数据政策，并确保整个组织与这些指令保持一致。他们将是决定人工智能如何在他们的组织中、在何处以及为何被使用的人。最终，这些领导角色将决定人工智能对其业务的影响。

Data-related roles relationships 数据相关角色关系

Regarding the organizational structure of these roles within an organization, the exact positioning of them within the org chart may vary, but typically you will see something similar to the following diagram:
关于这些角色在组织中的组织结构，它们在组织结构图中的确切位置可能有所不同，但通常你会看到类似于以下图表的情况：