-
-
- Sciences, Mathematics
and Biotechnology - Biology
- Chemistry and Physics
- Clinical Laboratory Science
- Health Advising
- Life Science Business and Biotechnology
- Mathematics and Statistics
- Online Sciences Courses
- See the full list
- Technology and
Information Management - Writing, Editing and
Technical Communication
- Online Learning
- Custom Programs
- Events
- Sciences, Mathematics
-
-
-
- Academic Services
- Student Aid
-
-
-
Berkeley Global
Business intelligence (BI) is revealed by combining operational information from various sources into a data mart and then providing insightful queries and reports to decision makers. BI has become an essential tool for strategic management, finance, customer service, marketing, sales and other business activities. Learn to analyze and develop a BI system, including programming examples using Microsoft SQL Server. You also learn to design insightful inquiries and reports, and gain an understanding of BI applications, data mart features, data mining algorithms and BI industry trends.
Prerequisites:
Required
- Familiarity with databases and spreadsheets
- Knowledge of management, marketing and finance
- Ability to program in at least one high-level programming language such as Python, Java, Ruby, JavaScript, C or C++. Need to fulfill this prereq? Take a course in:
- Introduction to Computers and Programming COMPSCI X444.4
- Programming Python COMPSCI X434
- First Course in Java EL ENG X429.9
- JavaScript and jQuery: An Introduction COMPSCI X452.1
- Introduction to C Language Programming EL ENG X24
Course Outline
Expand or collapse section
Course Objectives
- Understand business intelligence concepts and processes.
- Use SQL server relational databases to design and populate data marts.
- Create specific data mart applications based on business and marketing needs and goals.
What You Learn
- BI applications
- Data mart features in Microsoft SQL Server
- Data preparation for data mining
- Operational systems
- ETL (extract, transform and load)
- Relational databases with star schema
- How to create a data cube
- Aggregation and slowly changing dimensions
- Data mining algorithms including Association, Decision trees, Naïve Bayes, Neural Network, Regression, Sequence Clustering and Time Series.
- BI industry, tools and trends
How You Learn
- In-class presentations by instructor and BI industry professionals
- In-class exams
- Team programming assignments
- Analysis and design papers
Is This Course Right for You?
If you want to learn how to perform analytics in a business environment, then you should enroll.
Loading...
Sections
Spring enrollment opens on October 17!