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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-analytics-business
课程评论：没有评论
课程名称：商业数据分析入门 课程概述：本课程将使您了解商业领域中执行的数据分析实践。我们将探讨关键领域，如分析过程、数据的创建、存储、访问，以及组织如何与数据合作并创造一个有利于分析的环境。您在本课程中所学的内容将为您在支持分析的各个领域打下坚实的基础，帮助您更好地在组织中定位自己的成功。您将发展出一种技能和视角，使您更快地提升生产力，并成为组织中的重要资产。 此课程还为深入研究高级调查和计算方法提供基础，您将有机会在未来的商业数据分析专业课程中进行探索。 课程大纲： 1. 数据与现实世界中的分析 - 介绍分析问题的思考方式，分析数据如何促进决策过程。介绍信息-行动价值链框架。 - 学习信息生命周期以及如何在这一背景下思考分析问题。 - 掌握传统与新兴技术的数据捕获和存储方式，了解关系数据库和SQL的基本使用。 - 理解数据生命周期中的各类角色，概述数据质量、数据治理和数据隐私的关键理念。 2. 分析工具 - 学习支持分析工作的技术，包括数据存储和数据库、关系数据库、大数据和云技术等。 - 了解常用工具类别及其在分析任务中的支持作用。 3. 使用SQL进行数据提取 - 学习如何使用结构化查询语言（SQL）从关系数据库中提取数据。 - 掌握基本的SQL命令，数据结合与堆叠，以及如何使用运算符和子查询处理更复杂的查询。 4. 现实世界的分析组织 - 关注与数据工作和分析执行相关的人员和组织。 - 探讨不同角色的职能、组织结构如何影响效率与效果，以及支持分析组织顺利运行的规则与流程，如数据治理、数据隐私和数据质量。
Name:Data and Analysis in the Real World
Description:Welcome to week 1! In this module we’ll learn how to think about analytical problems and examine the process by which data enables analysis & decision making. We’ll introduce a framework called the Information-Action Value chain which describes the path from events in the world to business action, and we’ll look at some of the source systems that are used to capture data. At the end of this course you will be able to: Explain the information lifecycle from events in the real world to business actions, and how to think about analytical problems in that context , Recognize the types of events and characteristics that are often used in business analytics, and explain how the data is captured by source systems and stored using both traditional and emergent technologies, Gain a high-level familiarity with relational databases and learn how to use a simple but powerful language called SQL to extract analytical data sets of interest, Appreciate the spectrum of roles involved in the data lifecycle, and gain exposure to the various ways that organizations structure analytical functions, Summarize some of the key ideas around data quality, data governance, and data privacy
Name:Analytical Tools
Description:In this module we’ll learn about the technologies that enable analytical work. We’ll examine data storage and databases, including the relational database. We’ll talk about Big Data and Cloud technologies and ideas like federation, virtualization, and in-memory computing. We’ll also walk through a landscape of some of the more common tool classes and learn how these tools support common analytical tasks.
Name:Data Extraction Using SQL
Description:In this module we’ll learn how to extract data from a relational database using Structured Query Language, or SQL. We’ll cover all the basic SQL commands and learn how to combine and stack data from different tables. We’ll also learn how to expand the power of our queries using operators and handle additional complexity using subqueries.
Name:Real World Analytical Organizations
Description:In this module we focus on the people and organizations that work with data and actually execute analytics. We’ll discuss who does what and see how organizational structures can influence efficiency and effectiveness. We’ll also look at the supporting rules & processes that help an analytical organization run smoothly, like Data Governance, Data Privacy, and Data Quality.
This course will expose you to the data analytics practices executed in the business world. We will explore such key areas as the analytical process, how data is created, stored, accessed, and how the organization works with data and creates the environment in which analytics can flourish. What you learn in this course will give you a strong foundation in all the areas that support analytics and will help you to better position yourself for success within your organization. You’ll develop skills and a perspective that will make you more productive faster and allow you to become a valuable asset to your organization. This course also provides a basis for going deeper into advanced investigative and computational methods, which you have an opportunity to explore in future courses of the Data Analytics for Business specialization.
