B.C.A. in Data Analytics is a 3-year undergraduate course in computer applications. The program has been designed to offer to eligible candidates a combination of technical and managerial coursework needed for dealing with future challenges in the technology and data-driven global environment.
Data Analytics finds application across a range of areas, such as taking care of complex business issues, expanding efficiencies in hospital and medical centers, and recreating sporting challenges.
The coursework includes components like optimization, computer simulation, decision analysis, statistics, predictive modelling, data mining and visualization, applied probabilistic modelling, artificial intelligence, applications in finance, marketing, supply chain, information systems and economics using these tools.
The basic eligibility criterion for pursuing the course is a 10+2 or equivalent qualification in any stream from a recognized educational Board, with a minimum aggregate score of 50%.
Such graduates are hired in capacities such as:
Some of the top entrance tests conducted in India for admission to the course are:
The course is offered at leading Indian institutes such as:
The average tuition fee charged for the course in India ranges between INR 5,000 and 5 Lacs for a span of 3 years.
Successful graduates of the course can expect anything between INR 3 to 20 lacs as annual salary in the industry, increasing with experience and skillset.
Listed below are some of the major highlights of the course:
|Examination Type||Semester System/Year wise|
|Eligibility||10+2, preferably with Commerce subjects, with a minimum aggregate score of 50%.|
|Admission Process||Merit-based/ Based on counselling after qualification of entrance test.|
|Course Fee||INR 5,000 to 5 Lacs|
|Average Starting Salary||INR 3 to 20 lacs per annum|
|Top Recruiting Companies||HDFC Bank, Google, ICICI Bank, LinkedIn, Yes Bank, Oracle, IBM, McKinsey and Company, Boston Consulting Group, Morgan Stanley, Microsoft, KPMG, Deloitte, Accenture, Reliance, HCL, Wipro, Infosys, Adani Group, Larsen and Toubro (L&T), Tata Group, Google, Facebook, American Express, Capital IQ, Amazon, Infosys, Airtel, Idea, Reliance, BSNL, Tata Consultancy, Tata Motors, Bajaj, Hyundai, etc.|
|Top Recruiting Areas||Academics Institutions, Colleges and Universities, Finance, Marketing, Information Technology, Banking, management, Sales, Operations, Supply Chain Management, MNCs, Product Development, Human Recourses, and such.|
|Job Positions||Data Scientist, Health Care Analyst, Statistician, Business Analyst, Data Analyst, Data Scientist, Market Research Analyst, Technical Team Leader, Big Data Analyst, Predictive Modeler, Quantitative Analyst, Project Manager, Market Research Analyst, Computer Systems Analyst, Technical Team Leader, among others.|
The program aims to impart to eligible candidates a combined study of business with data analytics and quantitative systems. The curriculum is further supplemented by a progression of analytical modules, giving a solid range of abilities in data analysis and statistics.
In present-day business, key leaders consistently utilize the deductions of information investigation to advise strategic decisions. The program has been designed to equip aspiring managers and entrepreneurs with a crucial understanding of statistical principles, in order to grasp the implications and limitations of the results presented to them.
Such candidates would ideally possess vital analytical skills to operate in the discipline of Data Analytics, and strong theoretical foundations and practical skills of data science sector.
The subject covers specialized, technical and business areas. The curriculum is oriented towards:
Listed below are the minimum criteria which candidates interested in pursuing the course are required to fulfil, in order to be eligible to apply for the course:
Most institutes offering the course admit students based on performance in a relevant entrance test, often followed by a round of personal interview, wherein their general aptitude for the course is tested. Admission process generally varies across colleges.
A few institutes also provide direct admission based on the candidate’s performance at the 10+2 level of education.
Listed below are some of the top entrance exams conducted in the country for admission to the course:
A semester-wise breakup of the course’s syllabus is tabulated here:
|Semester I||Semester II|
|English for Professionals||Mathematics for Data Scientists -- II|
|Mathematics for Data Scientists - I||Object Oriented Programming using Java|
|Communication skills||Data Structures and Algorithms|
|Computer Architecture & Organization||Probability & Statistics - I|
|Programming in C||Excel for Data Scientists (Tool Based)|
|Operating System||Introduction to Data Science|
|Programming in C Lab||Object Oriented Programming using Java Lab|
|Operating System Lab||Data Structures and Algorithms Lab|
|Semester III||Semester IV|
|Reasoning and Thinking||Inferential Statistics|
|Software Engineering||Data Manipulation Using PL / SQL Programming|
|Database Management Systems||Big Data Analytics (Tool Based)|
|Probability & Statistics - II||Machine Learning Algorithms - I (Tool Based)|
|Computer Networks||Exploratory Data Analysis (Tool Based)|
|Scientific Programming Using R (Tool Based)||Business Communication and Presentation Skills / Professional Ethics|
|Database Management Systems Lab||Inferential Statistics Lab|
|Software Engineering Lab||Data Manipulation Using PL / SQL Programming Lab|
|Semester V||Semester VI|
|Times Series Analysis||Elective - III|
|Cloud Computing||Project and Viva-Voce|
|Machine Learning Algorithms - II (Tool Based)||List of Electives:|
|Data Visualization (Tool Based)||Elective – I (Any One)|
|Elective – I||Internet of Things|
|Elective – II||Artificial Intelligence|
|Times Series Analysis Lab||Neural Networks|
|Cloud Computing Lab||-|
|Elective – III (Any One)||Elective – II (Any One)|
|Data Science Project Management||Natural Language Processing|
|Data Science Industry Use Cases||Reinforcement Learning|
|Advance in Data Science||Real Time Data Processing|
B.C.A. in Data Analytics: Career Prospects
Data Analytics lies at the intersection of business intelligence, statistics, sociology, communication, and computer science.
Such professionals are needed to be number wizards, and also strong communicators who can think abstractly. Such analyses need to work closely with the Project Manager and help with project planning.
After gaining certain expertise, a Business Analyst is promoted to supervisory positions like Senior Business Analyst, etc.