Business Analytics Programs 17 Nov 2013 The The core f core for r - - PDF document

business analytics programs 17 nov 2013
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Business Analytics Programs 17 Nov 2013 The The core f core for r - - PDF document

Business Analytics Programs 17 Nov 2013 The The core f core for r MBA MBA / / MS MS Course Key Ideas Skills/Software Business Intelligence Bridge between IS and Databases, SQL, Business Analytics Programs Quantitative Methods


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Business Analytics Programs 17 Nov 2013 2013‐Nargundkar‐DSI‐MSMESB‐Slides.pdf 1

Satish Nargundkar Georgia State University Presented at the Decision Sciences Institute Annual Meeting, Baltimore, Nov. 16-19, 2013.

Business Analytics Programs

The The core f core for r MBA MBA / / MS MS

Course Key Ideas Skills/Software Business Intelligence Bridge between IS and Quantitative Methods Databases, SQL, Dashboards Business Modeling Financial, Forecasting, Optimization Spreadsheet based analysis – Excel – Regression, LP (Solver) Data Mining Model Life Cycle Classification/Prediction, Segmentation, Association Data Cleaning DiscriminantAnalyis, Logistic Regression, ANN, Classification Trees, Clustering Project Management Soft skills, quantitative

  • aspects. Critical activities.

PERT/CPM

Elec Electives f for r MS MS

Quantitative Qualitative Statistical Modeling Applied Regression Risk Management Marketing Intelligence Negotiation IS Management Strategy

Ne New (Pr w (Propo posed) MS MS Pr Progr

  • gram

Research focus Across departments Information Systems, Marketing, Management Science, Risk Management Internship component Industry partnership for data, projects

Succe Success wit ss with current current pr prog

  • gram

ram

 Fairly strong anecdotal data  Increased enrollment  Challenges

 Software, data  Mathematical ability  Staffing/Hiring – research vs. teaching

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Satish Nargundkar Georgia State University Presented at the Decision Sciences Institute Annual Meeting, Baltimore, Nov. 16-19, 2013.

Business Analytics Programs

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SLIDE 3

The core f The core for MBA / MS r MBA / MS

Course Key Ideas Skills/Software Business Intelligence Bridge between IS and Quantitative Methods Databases, SQL, Dashboards Business Modeling Financial, Forecasting, Optimization Spreadsheet based analysis – Excel – Regression, LP (Solver) Data Mining Model Life Cycle Classification/Prediction, Segmentation, Association Data Cleaning Discriminant Analyis, Logistic Regression, ANN, Classification Trees, Clustering Project Management Soft skills, quantitative

  • aspects. Critical activities.

PERT/CPM

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SLIDE 4

Electiv Electives f s for MS r MS

Quantitative Qualitative Statistical Modeling Applied Regression Risk Management Marketing Intelligence Negotiation IS Management Strategy

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SLIDE 5

Ne New (Pr w (Proposed) MS posed) MS Pr Program

  • gram

Research focus Across departments Information Systems, Marketing, Management Science, Risk Management Internship component Industry partnership for data, projects

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SLIDE 6

Success with current pr Success with current program

  • gram

 Fairly strong anecdotal data  Increased enrollment  Challenges

 Software, data  Mathematical ability  Staffing/Hiring – research vs. teaching