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    Quick Facts

    Total Fees
    11.92 L
    Exam
    UGAT

    Fees Details

    General

    11.92 L

    Disclaimer: Data for total fees has been calculated based on all years/semesters as provided by the college. The actual fees may vary.

    Course Details

    MODE

    Full time

    DURATION

    36 Months

    The BBA (Analytics and Big Data) - Big Data Analytics and Mining program at UPES is a specialized undergraduate degree program that focuses on equipping students with the skills and knowledge necessary to work with data and perform analytics tasks. The program combines principles of business administration with technical skills required for data analysis and interpretation. Students will learn various analytical techniques and tools to extract meaningful insights from large volumes of data.

    The specialization in Big Data Analytics and Mining within the program offers advanced courses that delve into specific topics related to big data analytics. These topics may include Text Mining and Natural Language Processing, Web Mining and Social Network Analysis, Data Visualization and Storytelling, and Big Data Analytics Platforms. This specialization prepares students for a wide range of career paths in the field of data analytics, including roles such as data analyst, data scientist, business intelligence analyst, data engineer, data consultant, and data strategist. Graduates can find employment opportunities in industries such as finance, marketing, healthcare, e-commerce, consulting, and more.

    The BBA (Analytics and Big Data) - Big Data Analytics and Mining program at UPES provides students with a comprehensive learning experience. It is a full-time course designed to support fast-track career progression by developing leadership and strategic management skills. The three-year program includes summer internships, live projects with companies, industrial tours, a dissertation (major project), and talks from industry experts. This hands-on approach allows students to apply their knowledge in real-world scenarios and gain practical industry experience.


    Important dates

    Exams and EventsDates
    UGAT
    Application Date - Last date to apply (Mode - Online)
    5 Jun'26 - 6 Jun'26
    UGAT
    Admit Card Date (Mode - Online)
    8 Jun'26 - 13 Jun'26
    UGAT
    Exam Date (Mode - Online)
    13 Jun'26 - 13 Jun'26
    UGAT
    Result Date (Mode - Online)
    23 Jun'26 - 23 Jun'26
    UPESMET-UG
    Slot Booking Date - Phase 2 (Mode - Online)
    19 Apr'26 - 2 May'26
    UPESMET-UG
    Application Date - Phase 2 (Mode - Online)
    24 Feb'26 - 29 Apr'26
    UPESMET-UG
    Exam Date - Phase 2 (Mode - Online)
    30 Apr'26 - 2 May'26
    CUET UG
    Others - Photo verification window (Mode - Online)
    6 Apr'26 - 9 Apr'26
    CUET UG
    Exam Date (Mode - Online)
    10 May'26 - 30 May'26

    Eligibility Criteria

    The minimum eligibility criteria for BBA (Analytics and Big Data) - Big Data Analytics and Mining to be fulfilled by interested students is as follows: Minimum 50% marks in Classes X and XII.

    Admission Details

    The process of selection criteria for students interested in pursuing BBA (Analytics and Big Data) - Big Data Analytics and Mining offered by UPES is based on the individual's performance in Entrance Exam (UPESMET-UG) / UGAT/ CUET

    Top Exams Accepted by School of Business, UPES Dehradun

    Student Reviews for BBA Analytics and Big Data Big Data Analytics and Mining

    College Infrastructure: 2/5
    Academics: 3/5
    Placements: 3/5
    Value for Money: 3/5
    Campus Life: 3/5

    MY overall experience is good . in upes we can explore thing

    College Infrastructure

    infrastructure is good in our both the campus . i like the infrastructure of library and school of libral arts building but i did not like much classroom infrastructure . wifi is also working good but in upes the wifi is same for faculty and students so this made problem sometimes . but other its well and good . faculty staff is also very helpful in nature they guide us very properly .we can reach to our faculty with any kind of help . the classroom infrastructure is not good .

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