Bachelor of Science in Business Administration with Specialization in Business Analytics

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(1)

November 2, 2013

Bachelor of Science in Business Administration

with Specialization in Business Analytics

(2)

Outline of Discussion

Outline of Discussion

•Rationale

Rationale

•Program Description

•Curriculum

•Implementation

•Current Efforts

•Current Efforts

(3)

Guaranteed Jobs in the Philippines

pp

“The United States alone faces a shortage of 140,000 to 190,000 people with

analytical and managerial expertise and 1.5 million managers and analysts with the kill t d t d d k d i i b d th t d f bi d t ( hibit) ” skills to understand and make decisions based on the study of big data (exhibit).”

Graduates with Business Analytics

Specialization can potentially fulfill this potentially fulfill this

global opportunity

New McKinsey

Gl b l I tit t R t Global Institute Report May 2011

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Broad Range of Skills Categories

Domain strategy skills to develop the right questions, determine which data is important Data experts to manipulate and integrate big

data

Mathematical and operations research to develop analytics algorithms

Executive and management skills to know when and how to use data for making decisions

Visualization skills to interpret data and present in meaningful ways Tool developers to mask the complexity of

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Analytics Course Roll-Out

y

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Analytics Course Roll-Out

y

(7)

Business Analytics Specialization Track

y

p

 Aims to present Business Analytics to Bachelor of Science in Business Administration students

 Aims to orient future managers of the benefits that can be offered by Business Analytics

 Aims to enable students to analyze data from multiple sources and present them in different methods and techniques that can be used for fact-based decision-makingg

 Highlights compliance to corporate code of ethics, policies, best practices, standards governing confidentiality and non disclosure agreement

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Business Analytics Specialization Track

y

p

 Fundamentals of Business Analytics

 Fundamentals of Data Warehousingu da e ta s o ata a e ous g

 Fundamentals of Descriptive Analytics

 Fundamentals of Predictive Analytics

 Fundamentals of Prescriptive Analytics

 Fundamentals of Prescriptive Analytics

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Learning Outcomes

g

 Define business requirements

 Tailor data architecture

 Describe where to look for data in an organization and create required reportsDescribe where to look for data in an organization and create required reports

 Analyses to support business optimization

 Understand data management concepts and criticality of data availability in order t k li bl b i d i i

to make reliable business decisions

 Demonstrate understanding of business intelligence including the importance of data gathering, data storage, data analysis and data access

 Apply different analytics modeling concepts on enterprise data

 Understand the functions and data access constraints of various departments within an organization and provide compliance reports

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Learning Outcomes

g

 Work on various analytics tools available in the market for various business functions

 Participate actively in business discussions with various departments and create common reports or specific/unique reports with regard to predictive and

prescriptive analytics

 Understand the business processes as they relate to data analysis and ti i ti

optimization

 Convey results of data analysis to organizational stakeholders at various levels

 Perform high-quality task required by the organization in particular, and the g q y q y g p , industry in general

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Bottomline…

Identify opportunities for the different types of analytics

 Descriptive Analyticsesc pt e a yt cs

 Predictive Analytics

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Fundamentals of Business Analytics

y

 Provides an overview of each type of analytics

 Enables students to identify opportunities for analytics given a scenario through multiple case studies

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Fundamentals of Data Warehousing

g

 Introduces students to the benefits of data warehousing

 Differentiates relational databases from multidimensional databases

 Provides a discussion on how to adapt data warehousing as an approach for managing data

 Highlights the needed resources to roll out a data warehouse

 Illustrates the relevance of data warehousing to analytics

 Emphasizes requirements gathering and the involvement of the business is made t b id th l b t b i d IT l

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Fundamentals of Data Warehousing

g

 Not technical

 Meant for managers who can charter changes in the future

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Fundamentals of Descriptive Analytics

p

y

 Teaches students to prepare reports using descriptive analytics tools

 Provides case studies from (Richards & Mindel, 2013) to enable students to learn report authoringg

 Teaches students to use IBM Cognos Report Studio

 Presents an opportunity to get an IBM Cognos Report Studio Advanced Report Authoring Certification

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Fundamentals of Predictive Analytics

y

 Introduces students to different techniques used to build predictive models

 Requires students to build and evaluate their own predictive models

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Fundamentals of Prescriptive Analytics

p

y

 Reviews operations research techniques previously discussed

 Presents operations research techniques not yet previously discussed

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Internship

p

 Aims to prepare students for their eventual jobs and careers in business analytics

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Implementation

p

 Commission on Higher Education (CHED)

 Technical Panel for Business and Management Education

 CHED Memorandum Order

 Orientation

 Training

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Commission on Higher Education and IBM

Commission on Higher Education and IBM

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Fundamentals of Analytics Training

y

g

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Business Analytics Society of Educators (BASE) -

y

y

(

)

Philippines

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IBM in the Philippines

Figure

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References

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