- PGDM Approved by AICTE, Accredited by NBA and Granted Equivalence to MBA by AIU
Data is the new Oil and the new Gold. Prime Minister Shri Narendra Modi, while addressing a crowd of more than 50,000 people at the grand ‘Howdy, Modi!’ event in Houston, USA in Sep 2019, used these words and reiterated that India was in a strong position to lead the world in the Industry 4.0 revolution, which relies on big data analytics and digital technology.
Data is growing faster than ever before and by the year 2020 about 1.7 megabytes of new information will be created every second for each human being on the planet. Research suggests that every second we perform 40,000 search queries on Google alone, which makes 1.2 trillion searches per year. The data is multiplying in every business and every aspect of life at a phenomenal rate. Our ability to analyze this data must keep pace with the speed of data generation. Businesses of all sizes, large and small, will soon have to use some or the other form of ‘data analytics’ to plan the sustainability and growth of their organizations.
McKinsey estimates that in the U.S. alone there will be a shortage of 140,000 to 190,000 people with deep analytical skills and 1.5 million more managers and analysts to analyze big data and make decisions thereon. Expertise in business analytics has emerged as the essential requirement of all future managers and business leaders.
Keeping in view the International industry trends, NDIM was one of the first to introduce Business Analytics as a full specialization. This course aims to prepare students for the competitive field of Business Analytics by giving them the ability to critically analyze business problems and devise data driven solutions. Some of the modules covered under this specialization include Machine Learning Using R and RapidMiner, Data Analytics using Python, Data Analysis Using SAS, Data Analytics using R, Programming skills with Python and Understanding DataBase Management Systems. The department is run by academically strong, result oriented faculty members with over 20 years of combined expertise and training in latest tools like R, Tableau, Python, SAS, RapidMiner, TensorFlow and Blockchain Technologies.
The programme is developed in consultation with senior Industry experts to ensure a high degree of relevance in accordance with the needs and demands of the industry. The department has a strong Industry linkage with professionals from McKinsey, Barclays, KPMG, Deloitte, etc coalescing with academia to bring greater value to the course offered. Illustrious alumni of the department continue to be connected to the faculty and their younger batches through an active forum for networking and mentoring.
The course highlights include an experiential and outcome based learning approach focusing on integrating the theoretical concepts with their real time applications, curriculum designed by industry leaders from various domains to ensure employment readiness and industry acceptability, incorporation of various Artificial Intelligence and Machine Learning tools across Finance/ HR/ Marketing/ SCM/ Manufacturing verticals, real world business use case studies, hands on sessions and exercises on application of databases, SQL, Python, R, RapidMiner in delivering business outcomes, further enhancing employability through mock interviews, special industry specific preparatory sessions, resume building and placement interviews in leading analytics firms, opportunity to interact with leading industry experts and exchange of ideas during guest lectures, workshops and industry led teaching sessions at NDIM to learn global best practices across business domains.
BRICS (Brazil, Russia, India, China, South Africa) CCI, through its School of Analysis, has partnered with NDIM to jointly offer ‘online’ and ‘offline’ programs in Data Science in India and other countries. NSDC Govt. of India has endorsed these programmes.
NDIM also regularly hosts Workshops/ MDPs/ Executive Programmes that aim to build strong foundation of data science concepts and machine learning algorithms for predictive modeling. This helps bridge the skill gap needs of organizations, while keeping the faculty in active touch with the recruiters and demands of the Industry.