5 courses with the subject BIDA, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
BIDA 630Data Analytics3
Lecture Hours: 3 Lab Hours: 0 Data analytics help decision makers perform quicker analysis and use the valuable information to make better decisions. This course introduces several commonly used modeling tools to develop and improve students' analytical skills through a variety of realistic situations. The skills learned in this course will help students to recognize a decision situation, understand the business problem, and deal with uncertainty and complex interactions to solve the problem. This course is cross listed with and equivalent to ISBA 630.
Lecture Hours: 3 Lab Hours: 0 This course focuses on building `web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms. The past decade has witnessed the development of big data platforms and associated technologies such as distributed file systems, no-SQL databases and stream computing engines. Online advertising, machine translation, natural language understanding, sentiment mining, personalized medicine, and national security are some examples of web- intelligence applications that are already wide-spread in different business areas. In this course we explore some such applications and related techniques such as text analytics, social media analysis, cloud and distributed systems, big data visualization using Tableau and GIS along with parallel implementations using map-reduce and related platforms. 182
Lecture Hours: 3 Lab Hours: 0 Data analytics focuses on improving existing operations and supports the enterprise resource planning by streamlining or optimizing business processes. Business analytics help decision makers perform quicker analysis and use the valuable information to make better decisions. This course introduces several commonly used modeling tools to develop and improve students' analytical skills through a variety of realistic situations. The skills learned in this course will help students to recognize a decision situation, understand the business problem, and deal with uncertainty and complex interactions to solve the problem. In order to equip students with these skills, this course is divided into four parts: (I) Descriptive and Predictive Analysis, (II) Prescriptive Analytics with low uncertainty, (III) Prescriptive Analytics with high uncertainty and (IV) Complex Predictive Analytics. Part I will cover forecasting and time series analysis, Part II will cover modeling, optimization, and solvers. Part III will cover decision trees for structuring decision problems under uncertainty, waiting line models, simulation and Part IV will cover multi-criteria decision making, heuristics, and simulation-optimization. Throughout the course, we will use SAS software as a modeling and analysis environment. This course is cross listed with and equivalent to MGMT 610 and HINF 640.
BIDA 660Executive Analytics and Business Intelligence3
Lecture Hours: 3 Lab Hours: 0 This course focuses on the integration of business processes and real time data analysis on a specific business intelligence platform. Using variety of globally used, user friendly technologies students will have hands-on experience and develop powerful analytical capabilities to end users. Major components of business intelligence platforms will be introduced and fundamentals of analytics (reporting, visualization and prediction) will be taught using SAP Business Intelligence Business Objects. This course uses the latest in technology to show the practice of data analytics in the real world. Students will experience practical applications of analytics through guided exercises and case studies.
Lecture Hours: 3 Lab Hours: 0 The prerequisite business analytics course presented predictive and prescriptive analytics tools at the introductory level. This course goes beyond by covering the tools and theory at a deeper level with an emphasis on the challenges that can arise in implementing analytical approaches within an actual organization. With the objective of helping students make better business decisions using advanced analytics, the course emphasizes that business analytics is a practical discipline which requires mastery of 183
