Business Analysis & Analytics   

This course introduces statistical techniques to evaluate quality and analyze processes and products. The course covers fundamentals of statistics, descriptive statistics, probability, binomial probability distribution, normal probability distribution, inferential statistics, and linear regression analysis. Students will be able to practice mathematical formulae as they relate to statistical methods as well as apply Excel to solve statistical problems. The course will develop skills of statistical analysis and decision-making. No Textbook Required.

Software Required: MS Excel

Students examine the fundamental processes, roles and responsibilities of the business analyst. The course curriculum is consistent with version 3 of the Business Analysis Body of Knowledge (BABOK) from the IIBA International Institute of Business Analysis. Students explore the use of tools and techniques used by business analysts within the broader context of organizations and their projects. They review methodologies used to equip the business analyst to better perform as a communication link between all business stakeholders and help them deliver on their key role in project and organizational success. The role of the business analyst as an agent of change is also highlighted. Students learn to plan, structure, and control the requirements elicitation and communication process, in order to maximize success and optimize results. These techniques can be utilized on a wide variety of activities, initiatives and projects and are an important component for success. Additionally studies include the effective use of requirements and life cycle management techniques. Through the combination of lectures, discussions and exercises, the course provides insights into the interaction between the business analyst and his or her surrounding environment and presents methodologies to identify, analyze and resolve business problems. Textbook required. NOTE: This course has mandatory chats and mandatory group work.

Students are introduced to different scripting language tools such as SQL, NOSQL, Apache, Java and Python that support data analysis on large volumes of data. They also analyze the strengths and limitations of current tools used today. Students review and recommend which tools best support data analysis, data quality, problem solving, analysis, analytics and business decision-making for different functions and industries.

NOTE: This course has mandatory chats. No Textbook Required

Students are introduced to data sources, informatics, data models, data management and data ownership; all key components to the data-driven organization. They analyze the common practices, prioritization approaches, system workload and security challenges for systems that support high data volumes and analytics. Students assess the individual, legal and society impacts of collecting data, including social media data. They also assess the historic problems with data collection and data management and how the current tools are used to address these problems.

NOTE: This course has mandatory chats. No Textbook Required