Data Analytics and Big Data Specialization
Program Aim
The Data Analytics and Big Data specialization curriculum will equip students with the necessary skill and ability to analyze, formulate and evaluate business data in the organisation and for career with analytical database knowledge, the ability to apply analytical database tools, techniques, and methods, and the ability to design, develop, implement, programme, and maintain data marts and data warehouses. It is a core subject in data science with the aim to develop methods to examine sizable and multivariate datasets. Thus, enabling you to develop goals that are abreast with the dynamics of the business world; consequently, giving you the means to gain a competitive edge and improve market share also helps in decision making by the top-level management.
Data Analytics and Big Data programme offers professionals a comprehensive foundation for applying statistical methods to solve real-world problems. One of the goals of this programme is to prepare students for careers in Data Analytics with a broad knowledge of the application of statistical tools, techniques, and methods, as well as the ability to conduct in-depth analysis, synthesis, and evaluation.
Data Analytics and Big Data is the study of the computational principles, methods, and systems for extracting and structuring knowledge from data, and the application and use of those principles. Large data sets are now generated by almost every activity in science, society, and commerce – ranging from molecular biology to social media, from sustainable energy to health care. Students will explore how to efficiently find patterns in these vast streams of data. Many research areas have tackled parts of this problem and separate research areas have grown around different types of unstructured data such as text, images, sensor data, video, and speech.
Program Objective
The student who graduates with a major in Data Analytics and Big Data will be able to:
- To apply statistical analysis and technologies on data to find trends and solve problems.
- Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.
- to make informed decisions using data and to communicate the results effectively.
- Provide expertise to plan, organize, direct, and lead full-scale data analytics projects and business ventures.
- Provide advice in all areas of the data analytics project cycle: business problem formation, data understanding, data warehousing, data preparation, and predictive model development, evaluation, interpretation, and deployment.
Program Learning Outcomes
The program learning outcomes (PLOs) set out the academic learning, skills, and achievements that the student must reliably demonstrate before graduation. Effectively develop and implement corporate strategies. Set up realistic business objectives. Perform daily tasks efficiently.
- Students will be able to articulate meaningful lines of inquiry that might be explored through the collection, organization, visualization, and analysis of data in a context associated with their primary field of study using (as appropriate) numerical, textual, spatial, and/or visual data.
- Students will understand what data are, how they are collected, the role of metadata in understanding a given set of data, and how to assess the quality/reliability of data.
- Students will have intermediate proficiency in the acquisition and organization of data.
- Students will demonstrate intermediate proficiency in the visualization of data to communicate information and patterns that exist in the data.
- Students will be able to use at beginning level of proficiency the tools of statistics and machine learning to ask questions of and explore patterns in data.
- For a given exploration of data, students will be able to communicate both in writing and verbally the limitations of data, the methods of acquisition, the interpretation of visualized data, and the results of statistical analysis.
Program Structure
| Year | Semester | Block | code | Subjects | Credits |
| Core Courses | |||||
| Year 1 | Semester 1 | Block 1 | IT4101 | Advance Computer Networks | 4 |
| Block 2 | IT4103 | Software Project Management | 4 | ||
| Block 3 | IT4102 | Advanced Database Management System | 4 | ||
| Semester 2 | Block 4 | MG4102 | Research Methodology | 4 | |
| Block 5 | IT4105 | Software Testing and Quality Assurance | 4 | ||
| Block 7 | IT4106 | Advanced Java Programming | 4 | ||
| Specialization Courses | |||||
| Year 2 | Semester 3 | Block 7 | DA4201 | Foundation of Data Sciences | 4 |
| Block 8 | DA4202 | Big Data Technology | 4 | ||
| Block 9 | DA4203 | Programming and Market Analytics | 4 | ||
| Semester 4 | Block 10-12 | IT4205 | Project Work | 9 | |
| Total Credits | 45 | ||||
Mr.Peter Nkhoma
Bachelor of Science in Information Technology
“My experience with Texila American University has been really great, it’s a wonderful experience and the lecturers are so friendly and interactive, they are always concerned about the studies of students. Texila American University has a standard education with very latest updated curriculums with concepts applicable to the current world. Latest technologies and wonderful libraries, it was always a wonderful feeling to be a student and to one day be called product of Texila American University.”
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FAQs
The Data Analytics and Big Data Specialization MSIT program at TAU Guyana is a master’s degree program designed to equip students with advanced knowledge and skills in data analytics, big data technologies, data mining, data visualization, and predictive modeling.
Admission requirements typically include a bachelor’s degree in computer science, information technology, mathematics, statistics, or a related field from an accredited institution, academic transcripts, letters of recommendation, a statement of purpose, and sometimes standardized test scores like the GRE. Proficiency in programming and data analysis concepts is also beneficial.
The curriculum includes core MSIT courses along with specialized courses focused on data analytics and big data, such as Data Mining Techniques, Big Data Technologies, Data Warehousing and Business Intelligence, Data Visualization, Predictive Analytics, Machine Learning for Data Science, and Advanced Data Analytics.
Yes, TAU Guyana provides opportunities for MSIT students specializing in data analytics and big data to gain practical experience through internships, data analytics projects, big data projects, workshops, and collaborations with IT companies or organizations, allowing students to apply concepts in real-world scenarios.
Graduates can pursue various career paths in data analytics, big data engineering, data science, business intelligence analysis, data visualization, machine learning, data-driven decision-making, and data consulting roles in industries such as IT, finance, healthcare, retail, marketing, and technology companies.
Yes, Big Data analytics offers promising career opportunities with high demand and competitive salaries. As organizations increasingly rely on data-driven insights for decision-making, skilled professionals in Big Data analytics are in high demand across various industries.
The best master’s degree for Data Analytics depends on individual career goals and interests. Common options include Master of Science in Data Analytics, Master of Science in Business Analytics, and Master of Information Systems with a focus on Data Analytics. Choosing a program that aligns with one’s career objectives and offers hands-on experience and industry connections is crucial.