Summary and Highlights总结与要点

In this lesson, you have learned:
在本课程中，您学习了：

Modern data ecosystem includes a network of interconnected and continually evolving entities that include:
现代数据生态系统包括一个由相互连接且不断演变的实体组成的网络，其中包括：

• Data, that is available in a host of different formats, structures, and sources.
  数据，以多种不同的格式、结构和来源而存在。
• Enterprise Data Environment, in which raw data is staged so it can be organized, cleaned, and optimized for use by end-users.
  企业数据环境，其中原始数据被暂存，以便对其进行组织、清理和优化，以供最终用户使用。
• End-users, such as business stakeholders, analysts, and programmers who consume data for various purposes.
  最终用户，例如商业利益相关者、分析师和程序员，他们出于各种目的消费数据。

Emerging technologies such as Cloud Computing, Machine Learning, and Big Data, are continually reshaping the data ecosystem and the possibilities it offers.
云计算、机器学习和大数据等新兴技术正在不断重塑数据生态系统及其提供的可能性。

Data Engineers, Data Analysts, Data Scientists, Business Analysts, and Business Intelligence Analysts, all play a vital role in the ecosystem for deriving insights and business results from data.
数据工程师、数据分析师、数据科学家、商业分析师和商业智能分析师都在生态系统中扮演着至关重要的角色，他们从数据中提取洞察并实现商业成果。

The goal of Data Engineering is to make quality data available for analytics and decision-making. And it does this by collecting raw source data, processing data so it becomes usable, storing data, and making quality data available to users securely.
数据工程的目标是为分析和决策提供高质量的数据。它通过收集原始源数据、处理数据使其变得可用、存储数据以及安全地向用户提供高质量数据来实现这一目标。