Fundamentals of Managing and using Data for Business Intelligence

In course, you will be introduced to the concept of business intelligence (BI), data mining and all you need to know about making business decisions. Have you ever wondered about the reasons behind the shutdown of a business? This course takes you through how to analyze circumstances surrounding a business to enable you to make useful business decisions. You will learn about the types of systems business intelligence applications use to analyze data. You will acquire basic knowledge about data visualization and dashboards. This course will bring to light the capabilities of a good performance dashboard, what it can help you achieve, and the common mistakes made when designing one. It discusses the characteristics and categories of data warehouses. Also, learn about concepts like key performance indicators (KPI), ETL (extract, transform and load), and data management.

This course also delves into data management. Do you know what data warehouse architecture is? Do you know the importance of data management, or care to find out the mechanism behind the transformation of data from input to output? Learn about data management, the arrangement of data in the data warehouse, and how data is being transformed from input to output. Specifically, you will learn about the different types of data warehouse development approaches. Some key concepts you study are N-tier architecture, data marts, operative/datastore/ODS (operational data store), and analytics/visualization and applications. Finally, you will be introduced to data mining.

The need for business intelligence cannot be overemphasized because for a company to remain viable it needs to be able to analyze the circumstances or data in its surroundings appropriately. Understanding the underlying mechanism of analyzing data surrounding a business environment is just as important as the analysis itself and should not also be overlooked. You will get an understanding of the mechanism of data mining, as well as the steps involved. The material highlights the various areas in which data mining can be applied. This course will be of significant interest to investors, shareholders, managers, and entrepreneurs.