Master of Science in Data Analytics
Overview
The discipline of data analytics comprises of the processes, technologies, and methodologies used to collect, store, process, analyze, and visualize data in a manner that enables decision-makers to make informed decisions. Data analytics involves the use of advanced analytics techniques, such as predictive modeling, machine learning, and data mining, to identify patterns and relationships in data. These techniques enable organizations to understand customer behavior, optimize supply chain management, improve product design, and enhance overall business performance.
The Master of Science in Data Analytics program offered at the School of Computing at Skyline University College can be distinguished from other similar programs by its focus and emphasis on Big data. Big data Analytics is a subset of Data Analytics discipline dealing with Massive sets of complex data that can be collected from hundreds of different sources with different forms and shapes (structured or unstructured). The complexity and sheer size of big data requires specialized infrastructure and different advanced tools and techniques with including both software and hardware such as Hadoop and Spark, which provide scalable and cost-effective solutions for storing and processing large datasets.
The Master of Science in Data Analytics program provides students with the necessary technical and analytical skills to collect, process, analyze, and interpret large and complex data sets. Additionally, students learn how to communicate their findings effectively to key stakeholders and decision-makers.
The curriculum is designed to cover a wide range of topics geared towards Big Data Analytics, including Statistical Analysis, Machine Learning, Data Visualization, and Big Data management. Students also learn about emerging technologies and tools used in big data analytics, such as Hadoop, Spark, and NoSQL databases.
Graduates of this program are well-equipped to work as data scientists, data analysts, or data engineers in various industries, including finance, healthcare, retail, and manufacturing, among others
Program Educational Objectives
The MSDA Program will enable its graduates to:
- Work collaboratively and communicate effectively to ensure a superior and productive experience for the user and all the organization’s functions. (Team work and Communication)
- Apply knowledge and Skills in Big Data Analytics to have a successful professional career. (Professional Career)
- Use expertise in implementing a wide range of innovative and sustainable Secured Computing solutions to support the community. (Community support)
- Recognize social responsibilities and perform duties professionally and ethically. (Social Responsibility and Ethics)
- Engage in professional and personal development through life-long learning and continuing education. (Life-Long Learning)
Students Outcomes (Program Learning Outcomes)
Data Analytics & Big Data Market Share
Curriculum
Industries
Technology
Finance, Banking, Marketing, and Advertising
Healthcare
Manufacturing and Supply Chain
Typical Job Titles
Data Scientist
Big Data Engineer
Data Analyst
Business Intelligence Analyst
Machine Learning Engineer
Database Administrator
Data and Analytics Manager
Financial Analyst
Customer Insights Analyst
Risk Analyst
Healthcare Data Analyst
Social Media Data Analyst
Data Architect
Data Engineer
Quantitative Analyst (Quant)
Analytics Consultant
Data Visualization Specialist
Statistician
AI Specialist
Marketing Analyst
Supply Chain Analyst
Fraud Analyst
Product Analyst
Admissions
Financial Support
In 2022, 56% graduate students received financial support towards their tuition fees.
Financial Support Options:
Undergraduate Merit Scholarships
Youth Empowerment Scholarships
Tuition Discount for Sponsored Undergraduates
