MSIT Specialization in Data Analytics and Big Data

Empowering Minds Towards Technological Excellence

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.

  1. 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.
  2. 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.
  3. Students will have intermediate proficiency in the acquisition and organization of data.
  4. Students will demonstrate intermediate proficiency in the visualization of data to communicate information and patterns that exist in the data.
  5. 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.
  6. 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
Data Analytics and Big Data Specialization MSIT

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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Please fill the form below, we will mail you the details of Tuition Fees and Scholarships of our Data Analytics and Big Data Degree program.


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