About this Course
This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment to create dashboards and Visual Analytics. We will cover the use of MicroStrategy, a leading BI tool, OLAP (online analytical processing) and Visual Insights capabilities for creating dashboards and Visual Analytics.
The course gives an overview of how computer technologies can support decision making across any number of business sectors. These technologies have had a profound impact on corporate strategy, performance, and competitiveness and broadly encompass decision support systems, business intelligence systems, and business analytics. Modules are organized around the business intelligence concepts, tools, and applications, and the use of data warehouse for business reporting, creating dashboards and visualizations, and for descriptive analytics.
商业智能的概念、工具与应用 is course 4 of 5 in the Data Warehousing for Business Intelligence Specialization.
This Specialization covers data architecture skills that are increasingly critical across a broad range of technology fields. You’ll learn the basics of structured data modeling, gain practical SQL coding experience, and develop an in-depth understanding of data warehouse design and data manipulation. You’ll have the opportunity to work with large data sets in a data warehouse environment to create dashboards and Visual Analytics. You will use of MicroStrategy, a leading BI tool, OLAP (online analytical processing) and Visual Insights capabilities to create dashboards and Visual Analytics. In the final Capstone Project, you’ll apply your skills to build a small, basic data warehouse, populate it with data, and create dashboards and other visualizations to analyze and communicate the data to a broad audience.