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• AACSB-accredited and STEM-designated
• Completion time: One year expedited or 2-year standard duration to satisfy degree requirements. Full-time and part-time tracks available.
• Credit units needed for degree: 34 credits
• Number of courses: 12 courses – 11 core and one culminating experience
• Class time: Evening classes, Monday – Thursday, and Saturday classes
• Class mode: In-person lectures with hybrid content

The M.S. Business Analytics is open to students who hold a baccalaureate degree with certain quantitative and programming background from a regionally accredited college or university. The admission to this program is based on the holistic view of the following criteria: 

• Demonstrated mastery of college algebra, statistics, and programming with a grade of “C” or better in relevant coursework
• Undergraduate degree with at least 2.5 Grade Point Average (or equivalent).
• For International students, please visit the following link for English Proficiency Requirements. 
• Two letters of recommendation
• Other supporting documents such as resume, certificates, etc.
• Æðµã´«Ã½ English Language Institute (CPELI) offers English learning programs. CPELI level 6 is acceptable for satisfying CPP English proficiency requirement of SGSB graduate program admission purpose. Details can be found at /cpeli/.

• CPP’s STEM designated program for a graduate degree in business analytics consists of 34 units across four models – Business, Data, Analytics, and Experiential tracks, enabling students to focus on the implication of business analytics on various functional business areas.
• For more info, visit the Curriculum page

To provide in-depth and rigorous training in business analytics, this program emphasizes both the technical and the application perspectives of data analytics. Graduates from this program are anticipated to be able to:

• Develop business initiatives with strong story-telling ability
• Lead organizational changes with data driven decision making
• Proficiently use programming and database tools for descriptive, discovery, predictive, and prescriptive analytics

• Students will be able to effectively impart business analytics problems, methods, and solutions orally.
• Students will be able to effectively describe business analytics problems, methods, and solutions in writing.
• Students will be able to use different business analytics methodologies and tools to evaluate business problems.
• Students will be able to select the appropriate business analytics methodologies and tools for the problem at hand.
• Students will be able to evaluate business analytics solutions for various business functional areas' needs.
• Students will be able to develop change management strategies.
• Students will be able to demonstrate leadership knowledge and skills in business analytics projects.

Data Engineer
A Data Engineer designs, builds, and maintains data pipelines and infrastructure, enabling efficient data collection, storage, and analysis for organizational decision-making.

Predictive Modeling Analyst
A Predictive Modeling Analyst uses statistical techniques and machine leaming to create models that forecast future trends, behaviors, or outcomes, aiding in strategic decision-making.

Business Intelligence Engineer
A Business Intelligence Engineer designs and develops systems to collect, analyze, and visualize data, providing actionable insights to support informed business decisions.

Customer Analytics Director
A Customer Analytics Director leads the analysis of customer data to uncover insights, guide strategy, and improve customer experiences, driving loyalty and business growth

Statistician
A Statistician collects, analyzes, and interprets data using statistical methods to provide insights, solve problems, and support decision-making across various fields.

Big Data Consultant
A Big Data Consultant advises organizations on leveraging large datasets, implementing analytics tools, and developing strategies to extract insights and drive data-driven decisions.

Technology Consultant
A Technology Consultant advises organizations on leveraging technology to improve operations, solve problems, and achieve business objectives through strategic planning and implementation.

Chief Data Offcer
A Chief Data Officer (CDO) oversees an organization's data strategy, governance, and analytics, ensuring data is effectively used as a strategic asset to drive decision-making and innovation.

Senior Quantitative Developer
A Senior Quantitative Developer designs and develops advanced mathematical models and algorithms to analyze financial data, optimize strategies, and support decision-making in financial institutions.

Chief Technology Officer
A Chief Technology Officer (CTO) leads an organization's technological vision, strategy, and development, ensuring technology aligns with business goals and drives innovation.

Data Architect
A Data Architect designs and structures data systems and frameworks, ensuring efficient data management, accessibility, security, and scalability to support organizational goals.