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MBA in Business Analytics 2 at Siksha 'O' Anusandhan
Khordha, Odisha
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About the Specialization
What is Business Analytics [2] at Siksha 'O' Anusandhan Khordha?
This Business Analytics program at Siksha ''''O'''' Anusandhan focuses on equipping students with advanced analytical skills to interpret complex business data. It addresses the growing demand for data-driven decision-making across Indian industries, providing a comprehensive understanding of tools and techniques. The curriculum integrates management principles with cutting-edge analytical methodologies, preparing graduates for diverse roles in the evolving data economy.
Who Should Apply?
This program is ideal for fresh graduates from quantitative or business backgrounds seeking entry into data-centric roles. It also suits working professionals aiming to upskill in analytics or career changers transitioning into the dynamic field of business intelligence. Individuals with a strong aptitude for numbers and problem-solving, possessing a bachelor''''s degree and valid entrance test scores, will find this specialization highly rewarding.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative career paths in India as Data Analysts, Business Intelligence Developers, Analytics Consultants, or Machine Learning Specialists. Entry-level salaries typically range from INR 4-7 LPA, with experienced professionals earning significantly more. The program aligns with industry demand for analytics expertise, facilitating growth trajectories in various sectors including IT, finance, e-commerce, and healthcare across leading Indian companies.
Student Success Practices
Foundation Stage
Strengthen Core Business Fundamentals- (Semester 1-2)
Dedicate time to thoroughly understand core MBA subjects like Management Process, Economics, Accounting, and Marketing. These foundational concepts are crucial for applying analytics effectively to business problems later on. Utilize textbooks, case studies, and faculty office hours to build a strong theoretical base.
Tools & Resources
Core MBA textbooks, Harvard Business Review case studies, Faculty mentorship
Career Connection
A solid grasp of business fundamentals ensures you can connect analytical insights directly to strategic business outcomes, making you a more valuable asset in any data-driven role.
Master Business Statistics and Computer Applications- (Semester 1-2)
Focus intensely on Business Statistics and Computer Applications Lab courses. Develop strong proficiency in statistical software (e.g., Excel, R, Python basics) and data handling. Participate in extra practice sessions and online tutorials to solidify these essential technical skills.
Tools & Resources
Microsoft Excel, Python (Anaconda, Jupyter Notebook), R Studio, Coursera/edX introductory courses
Career Connection
Proficiency in statistical methods and computer applications forms the bedrock for all advanced analytics, crucial for roles like Data Analyst and BI Developer.
Develop Effective Business Communication- (Semester 1-2)
Actively participate in Business Communication classes and the Communication Lab. Focus on improving presentation skills, report writing, and professional networking. Join student clubs that offer opportunities for public speaking and team projects to practice conveying complex ideas clearly.
Tools & Resources
Toastmasters International (local chapters), Grammarly, LinkedIn for networking
Career Connection
Strong communication skills are vital for translating analytical findings into actionable business insights for non-technical stakeholders, enhancing career progression in leadership roles.
Intermediate Stage
Deep Dive into Core Business Analytics Tools- (Semester 3)
Beyond classroom learning, invest time in mastering tools introduced in ''''Introduction to Business Analytics'''' and ''''Data Visualization''''. Practice with real-world datasets, build dashboards, and engage in online challenges. Consider pursuing introductory certifications in these tools.
Tools & Resources
Tableau Public, Power BI, SQL (online platforms like HackerRank, LeetCode), Kaggle datasets
Career Connection
Hands-on expertise with industry-standard analytics tools makes you highly employable for roles requiring immediate practical application of skills.
Engage in Analytics Projects and Internships- (Semester 3)
Actively seek and participate in industry-related analytics projects, whether through academic assignments or external internships (like the Internship Project). Apply theoretical knowledge to solve real business problems, building a strong portfolio of practical work. Network with industry professionals during this period.
Tools & Resources
University''''s placement cell, LinkedIn, Industry conferences/workshops
Career Connection
Practical experience through projects and internships is critical for demonstrating problem-solving abilities and securing full-time positions post-graduation, especially in analytics consulting.
Specialize through Elective Choices- (Semester 3)
Carefully select elective specialization courses in Semester 3 and 4 that align with your career interests, such as Predictive Analytics, Marketing Analytics, or Supply Chain Analytics. Deepen your knowledge in these niche areas to develop specialized expertise demanded by specific industries. Supplement with relevant online courses.
Tools & Resources
Niche industry reports, Online learning platforms for specialized analytics, Domain-specific forums
Career Connection
Specialized knowledge in a particular domain of analytics (e.g., marketing, finance) enhances your candidacy for targeted roles and faster career advancement in that sector.
Advanced Stage
Master Machine Learning and Big Data Techniques- (Semester 4)
Focus on developing advanced skills in Machine Learning for Business and Big Data Analytics. Understand the underlying algorithms and their business applications. Work on complex datasets, perhaps collaborating on research papers or advanced projects that demonstrate your ability to handle large-scale data and build sophisticated models.
Tools & Resources
Python libraries (Scikit-learn, TensorFlow, Keras), Apache Hadoop/Spark, Cloud platforms (AWS, Azure, GCP)
Career Connection
Mastery of ML and Big Data is essential for advanced roles like Data Scientist, AI Specialist, and Big Data Engineer, offering high growth potential and competitive salaries.
Undertake a Comprehensive Dissertation/Capstone Project- (Semester 4)
The Dissertation in Semester 4 is a critical opportunity to synthesize all learned skills. Choose a challenging business problem, collect and analyze relevant data, and propose innovative analytical solutions. This project should showcase your end-to-end analytical capability and problem-solving prowess.
Tools & Resources
Academic research databases, Industry mentors, Statistical software and ML tools
Career Connection
A well-executed dissertation serves as a powerful testament to your analytical expertise, significantly boosting your profile for job applications and demonstrating research aptitude.
Prepare for Placements and Professional Certifications- (Semester 4)
Engage actively with the placement cell for resume building, mock interviews, and company-specific preparation. Simultaneously, pursue relevant professional certifications (e.g., from IBM, Microsoft, Google) that validate your analytics skills and provide an edge in the competitive job market.
Tools & Resources
Placement Cell workshops, Online certification platforms (e.g., Google Data Analytics Certificate, Microsoft Certified: Azure Data Scientist Associate), Interview preparation guides
Career Connection
Proactive placement preparation combined with industry-recognized certifications ensures you are highly competitive for top roles and ready to launch a successful career in business analytics immediately after graduation.
Program Structure and Curriculum
Eligibility:
- Bachelor''''s Degree in any discipline with at least 50% marks (45% for SC/ST/OBC) from any recognized university. Must have a valid score in CAT/XAT/MAT/CMAT/GMAT/OJEE/SAAT.
Duration: 2 years / 4 semesters
Credits: 83.5 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA 101 | Management Process and Organisational Behaviour | Core | 3 | |
| MBA 102 | Managerial Economics | Core | 3 | |
| MBA 103 | Accounting for Managers | Core | 3 | |
| MBA 104 | Business Statistics | Core | 3 | |
| MBA 105 | Marketing Management | Core | 3 | |
| MBA 106 | Business Communication | Core | 3 | |
| MBA 107 | Communication Lab & Soft Skills | Lab | 1.5 | |
| MBA 108 | Computer Applications Lab | Lab | 1.5 |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA 201 | Human Resource Management | Core | 3 | |
| MBA 202 | Financial Management | Core | 3 | |
| MBA 203 | Operations Management | Core | 3 | |
| MBA 204 | Research Methodology | Core | 3 | |
| MBA 205 | Legal Aspects of Business | Core | 3 | |
| MBA 206 | Business Environment | Core | 3 | |
| MBA 207 | Managerial Skill Development | Lab | 1.5 |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA 301 | Strategic Management | Core | 3 | |
| MBA 302 | Entrepreneurship Development | Core | 3 | |
| MBA BA 303 | Introduction to Business Analytics | Compulsory Specialization | 3 | |
| MBA BA 304 | Data Visualization and Storytelling | Compulsory Specialization | 3 | |
| MBA BA 305 | Predictive Analytics | Elective Specialization | 3 | |
| MBA BA 306 | Business Intelligence Tools | Elective Specialization | 3 | |
| MBA BA 307 | Marketing Analytics | Elective Specialization | 3 | |
| MBA BA 308 | Supply Chain Analytics | Elective Specialization | 3 | |
| MBA 309 | Internship Project | Project | 4 |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA 401 | International Business | Core | 3 | |
| MBA BA 402 | Machine Learning for Business | Compulsory Specialization | 3 | |
| MBA BA 403 | Big Data Analytics | Compulsory Specialization | 3 | |
| MBA BA 404 | Financial Analytics | Elective Specialization | 3 | |
| MBA BA 405 | HR Analytics | Elective Specialization | 3 | |
| MBA BA 406 | Web and Social Media Analytics | Elective Specialization | 3 | |
| MBA BA 407 | AI and Deep Learning in Business | Elective Specialization | 3 | |
| MBA 408 | Dissertation | Project | 6 |
