ACCT 4307 - Business Modeling with SpreadsheetsCredits: 3
Introduces advanced quantitative modeling techniques for business decision-making. Covers a variety of modeling techniques, business analytics concepts, and data analysis tools. Students learn to implement these techniques in spreadsheet models that assist businesses in understanding and managing risk and improving decision-making. Applications cover a broad range of functional areas, including accounting, finance, marketing, and operations. Prerequisites: ACCT 2302 ; ITOM 2308 , ITOM 3306 ; FINA 3320 . Reserved for Cox majors.
The Business Analytics major is a unique major that integrates a functional area of business with computer expertise. It is a major that develops skills in the use of the computer as a decision-making tool and provides expertise in a business field in which these skills can be applied. The modern business employer is looking for graduates who have more than just a degree in a particular functional area. They are looking for students who have multiple skills which allow them to serve their company in many ways. Business Analytics provides the training needed to develop those skills.
Business Analytics: The Art Of Modeling With Spreadsheets, 5th Edition Book Pdf
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This course introduces students to the use of advanced data modeling in spreadsheets and self-service business intelligence tools to analyze data and make business decisions in Excel. Power Pivot and the DAX language are used to extract meaningful information from large data sets. Power Query is introduced as an ETL tool, and the Power BI Desktop is used for visualization purposes. These topics are then applied to analyze problems in predictive analytics. Examples include advanced multiple regression and classification techniques in data mining. Prerequisites: A grade of C or better in BNAL 301, BNAL 306, and a declared major in the University or permission of the Dean's Office.
Simulation modeling is an integral part of the analytics revolution, enabling the creation of models that can represent the variability that exists in many real business systems. This course covers the theory and application of simulation modeling, with an emphasis on how simulation provides predictive and prescriptive analytics to support business decision-making. Topics include simulation fundamentals, the project life-cycle, model development, input and output analysis, verification and validation, and the presentation of a simulation study. We utilize a major commercial simulation software package for assignments and class projects. Prerequisites: OPMT 303 with a grade of C or better and BNAL 306 with a grade of C or better, senior standing and a declared major in the University or permission of the Dean's Office.
Steve Powell is a Professor at the Tuck School of Business at Dartmouth College. His primary research interest lies in modeling production and service processes, but he has also been active in research in energy economics, marketing, and operations. At Tuck, he has developed a variety of courses in management science, including the core Decision Science course and electives in the Art of Modeling, Business Analytics, and Simulation. He originated the Teacher's Forum column in Interfaces, and he has written a number of articles on teaching modeling to practitioners. He was the Academic Director of the annual INFORMS Teaching of Management Science Workshops. In 2001, he was awarded the INFORMS Prize for the Teaching of Operations Research/Management Science Practice. Along with Ken Baker, he has directed the Spreadsheet Engineering Research Project. In 2008, he co-authored Modeling for Insight: A Master Class for Business Analysts with Robert J. Batt.
A leader in a data driven world requires the knowledge of both data-related (statistical) methods and of appropriate models to use that data. This Business Analytics class focuses on the latter: it introduces students to analytical frameworks used for decision making though Excel modeling. These include Linear and Integer Optimization, Decision Analysis, and Risk modeling. For each methodology students are first exposed to the basic mechanics, and then apply the methodology to real-world business problems using Excel.
Master business modeling and analysis techniques with Microsoft Excel and transform data into bottom-line results. Award-winning educator Wayne Winston's hands-on, scenario-focused guide helps you use today's Excel to ask the right questions and get accurate, actionable answers. More extensively updated than any previous edition, new coverage ranges from one-click data analysis to STOCKHISTORY, dynamic arrays to Power Query, and includes six new chapters. Practice with over 900 problems, many based on real challenges faced by working analysts.
This book fills a void for a balanced approach to spreadsheet-based decision modeling. In addition to using spreadsheets as a tool to quickly set up and solve decision models, the authors show how and why the methods work and combine the user's power to logically model and analyze diverse decision-making scenarios with software-based solutions. The book discusses the fundamental concepts, assumptions and limitations behind each decision modeling technique, shows how each decision model works, and illustrates the real-world usefulness of each technique with many applications from both profit and nonprofit organizations.
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Below is a break down of subject weightings in the FMVA financial analyst program. As you can see there is a heavy focus on financial modeling, finance, Excel, business valuation, budgeting/forecasting, PowerPoint presentations, accounting and business strategy.
In this course, you will explore spreadsheet modeling for applied decision making. You will work with data sets and navigate in an Excel 2016 Workbook. You will examine data cleaning and modeling concepts, practice core Excel skills, and explore ways to apply data management techniques to the spreadsheet system by using its math and logic capabilities to their full potential. By performing data management, you can improve the structure and usefulness of your data.
Donna L. Haeger is a Professor of Practice in the Charles H. Dyson School of Applied Economics and Management at Cornell University. She teaches introductory and advanced spreadsheet modeling courses for applied decision making. These courses leverage Microsoft Excel as a business analytics tool. Prior to teaching at Cornell, Dr. Haeger taught courses in management theory, organizational behavior, and marketing. With over 20 years in industry, her corporate experience includes work in investments, banking, and corporate finance.
Model complex hierarchies and business scenarios with a new, easy-to-understand Essbase user and administration interface. Deploy custom applications from multiple data sources to deliver consistent and sharable models across your organization.
The Business and Financial Modeling online program will feature a Capstone project that allows participants to apply their knowledge to the real world. Learners will work with datasets from Wharton Research Data Services, or WRDS, the leading data research platform and business intelligence tool for over 30,000 corporate, academic, government and nonprofit clients in 33 countries, and will receive feedback from Wharton data experts.
Updated and revised, Optimization Modeling with Spreadsheets, Third Edition emphasizes model building skills in optimization analysis. By emphasizing both spreadsheet modeling and optimization tools in the freely available Microsoft(R) Office Excel(R) Solver, the book illustrates how to find solutions to real-world optimization problems without needing additional specialized software.
Optimization Modeling with Spreadsheets, Third Edition is an excellent textbook for upper-undergraduate and graduate-level courses that include deterministic models, optimization, spreadsheet modeling, quantitative methods, engineering management, engineering modeling, operations research, and management science. The book is an ideal reference for readers wishing to advance their knowledge of Excel and modeling and is also a useful guide for MBA students and modeling practitioners in business and non-profit sectors interested in spreadsheet optimization.
An accessible introduction to optimization analysis using spreadsheets
Updated and revised, Optimization Modeling with Spreadsheets, Third Edition emphasizes model-building skills in optimization analysis. By emphasizing both spreadsheet modeling and optimization tools in the freely available Microsoft(R) Office Excel(R) Solver, the book illustrates how to find solutions to real-world optimization problems without needing additional specialized software.
The Third Edition includes many practical applications of optimization models as well as a systematic framework that illuminates the common structures found in many successful models. With focused coverage on linear programming, nonlinear programming, integer programming, and heuristic programming, Optimization Modeling with Spreadsheets, Third Edition features:
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