This is the second course in the Data Warehousing for Business Intelligence specialization. Ideally, the courses should be taken in sequence.
In this course, you will learn exciting concepts and skills for designing data warehouses and
Extraction, Transformation And Loading (ETL)
完成时间为 4 小时
Data Warehouse Concepts and Architectures
Module 1 introduces the course and covers concepts that provide a context for the remainder of this course. In the first two lessons, you’ll understand the objectives for the course and know what topics and assignments to expect. In the remaining lessons, you will learn about historical reasons for development of data warehouse technology, learning effects, business architectures, maturity models, project management issues, market trends, and employment opportunities. This informational module will ensure that you have the background for success in later modules that emphasize details and hands-on skills.You should also read about the software requirements in the lesson at the end of module 1. I recommend that you try to install the software this week before assignments begin in week 2.
8 个视频 （总计 53 分钟）, 15 个阅读材料, 1 个测验
完成时间为 7 小时
Multidimensional Data Representation and Manipulation
Now that you have the informational context for data warehouse development, you’ll start using data warehouse tools! In module 2, you will learn about the multidimensional representation of a data warehouse used by business analysts. You’ll apply what you’ve learned in practice and graded problems using WebPivotTable or Pivot4J, open source tools for manipulating pivot tables. At the end of this module, you will have solid background to communicate and assist business analysts who use a multidimensional representation of a data warehouse.
7 个视频 （总计 45 分钟）, 9 个阅读材料, 2 个测验
完成时间为 4 小时
Data Warehouse Design Practices and Methodologies
This module emphasizes data warehouse design skills. Now that you understand the multidimensional representation used by business analysts, you are ready to learn about data warehouse design using a relational database. In practice, the multidimensional representation used by business analysts must be derived from a data warehouse design using a relational DBMS.You will learn about design patterns, summarizability problems, and design methodologies. You will apply these concepts to mini case studies about data warehouse design. At the end of the module, you will have created data warehouse designs based on data sources and business needs of hypothetical organizations.
6 个视频 （总计 47 分钟）, 8 个阅读材料, 2 个测验
完成时间为 2 小时
Data Integration Concepts, Processes,and Techniques
Module 4 extends your background about data warehouse development. After learning about schema design concepts and practices, you are ready to learn about data integration processing to populate and refresh a data warehouse. The informational background in module 4 covers concepts about data sources, data integration processes, and techniques for pattern matching and inexact matching of text. Module 4 provides a context for the software skills that you will learn in module 5.