ADDENDUM to the Rasmussen College Catalog 2016-2017 May 18, 2017 QMB 3200 Introduction to Scripting 4 credits, 60 hours This course serves as an introduction to the scripting process as it relates to data extraction and transformation processes. Prerequisite: None QMB 3300 Introduction to Data Visualization 4 credits, 60 hours This course explores data visualization tools and techniques. It emphasizes the best ways to communicate data to the intended audience. Students learn about tools that aid in visualizing data and how to develop objective depiction of data using an editorial thinking approach. This course will prepare students for the challenges of having to analyze data and communicate results to audiences with various skill levels and preferences. Prerequisite: None QMB 4000 Data Elements 4 credits, 60 hours This course reviews the concepts, standards, and functions used to identify data elements necessary for an efficient data preparation process. Prerequisite: QMB 3200 Introduction to Scripting QMB 4100 Applied Business Intelligence 4 credits, 60 hours This course allows students to apply skills and techniques for analyzing existing business performance data to provide support for business planning. It places focus on planning an end-to-end business intelligence process, platform, database, and analytical tool usage. Students will learn about processing and analyzing data, quality assurance and regulatory adherence, and preparing data for consumption. Students will create visualizations to help guide business decision-making. Prerequisite: CTS 3265C Introduction to Business Intelligence QMB 4200 Advanced Analytics Platforms, Environments, and Software 4 credits, 60 hours This course is the student for advanced analytics. It places focus on developing and deployed Extract Transform Load (ETL) jobs for large data sets. Topics will include how to configure the environment to run the advanced analytic job. It places focus on real-time analytics as well. This course will prepare students for developing advanced analytics and ETL job. It also prepares students about how to deploy the advanced analytics in the enterprise environment. Prerequisite: QMB 3100 Foundations of Analytics Platforms, Environments, and Software QMB 4300 Data Quality in Analytics 4 credits, 60 hours Quality data allows for quality analysis. In this course, students will learn how to identify common types of data quality issues including missing data, incorrect data, outliers, normalization, and duplication. This course will prepare students to prepare data for analytics projects. Prerequisite: None QMB 4400 Data Analysis and Optimization 4 credits, 60 hours This course will allow students to run data extracts and scripts to demonstrate a complete data analysis process, while requiring the identification and application of data element requirements, scripting modifications, and preparation techniques that could improve analysis results. Prerequisites: QMB 4000 Data Elements; QMB 4300 Data Quality in Analytics QMB 4500 Data Visualization Implementation and Communication 4 credits, 60 hours This course focuses on the study of data sets which relate to meeting client needs. It includes methods used to evaluate data such as benchmarking, scoring, and ranking. Students learn the difference between correlation and causation. Students will explore techniques for visualizing both quantitative and qualitative data. This course will prepare students with the skills to derive business insights and make meaningful inferences from data sets. Prerequisite: QMB 3300 Introduction to Data Visualization QMB 4900 Data Analytics Capstone 3 credits, 60 hours This course allows students to demonstrate their skills and techniques for analyzing generalized business data to provide support for business planning. It places focus on planning an end-to-end business analytics process; platform, database, and analytical tool usage; processing and analyzing data; quality assurance and regulatory adherence; preparing data for consumption; and visualization creation to help guide business decision- making. Prerequisite: Expected to be the final upper-level core course completed Delete the existing course descriptions and replace with the following: CIS 1175C Fundamentals of Hardware and Software II This course is a continuation of Fundamentals of Hardware and Software I and helps prepare students to take the CompTIA A+ certification exams. This course will focus on operating systems, security, mobile devices, and troubleshooting. Using the Windows operating system, students will learn how to set up networking, printers, tablets, file sharing, and troubleshoot problems related to This addendum replaces all previously issued versions. Page 9 / 53
