MBA in Data Analytics

MBA in Data Analytics is a two-year postgraduate MBA programme that provides training and knowledge of critical managerial abilities needed to streamline the data process. The MBA in Data Analytics programme prepares students for positions in consumer goods and services functions, as well as a grasp of the industry's special difficulties, enabling a speedier ascent up the career ladder. Students will also gain a thorough understanding of data science and data analytics principles through the MBA in Data Analytics curriculum. The programme includes themes such as business communication, business skills development, applied operations research, and others.

Admission to this MBA programme, like any other, is based on the candidates' previous academic record and performance, as well as qualifying scores from university-accepted entrance tests such as the CAT, XAT, MAT, NMAT, SNAP, and others. IIMs, IITs, Great Lakes in Chennai, Madras University, Narsee Monjee Institute of Management Studies, and others are among the top MBA in Data Analytics colleges in India. Candidates often spend anything between INR 3 lakhs and INR 27 lakhs for the programme.

Graduates can work as Data Analysts, Business Analysts, Information Architects, Product Managers, Data Scientists, Data Engineers, Data Analytics Managers, Research Analysts, System Analysts, and other professionals. Graduates can expect to start with an annual salary of INR 5-15 lakhs, which will definitely rise and potentially reach INR 40 lakhs as their experience grows. Here is everything to know more about the MBA in Data Analytics programme and what it comprises.

Here is a quick rundown of some of the most important features and facts about MBA in Data Analytics courses.

Data Analytics has become an essential tool for business in this age where relying on trends and patterns has become a necessity for taking major business decisions. Researching trends is the most effective way to succeed in this digital age that is driving the business world and transforming it into a data-centric industry. From multinational corporations (MNCs) to start-ups, everyone relies on data to develop better strategies for their business's future.

That being said, being an individual in this data-driven business world can prove to be highly beneficial in terms of career opportunities. Thus, pursuing an MBA in Data Analytics is an ideal choice for individuals who are interested in building a career in data research and Big Data Analytics. Here are some compelling reasons to study and pursue an MBA in Data Analytics.

• Data Analytics is Important for Top Organisations: The flood of data is reshaping enterprises. Companies of all sizes are now expecting data-driven insight to inform their business decisions. Data specialists have a significant impact on business strategies and marketing approaches.
• Job Prospects are Increasing: The Science and Technology Committee produced this research, noting that 58,000 jobs might be generated and £216 billion contributed to the global economy (2.3% of GDP) by 2022. The need for data specialists is increasing while the supply remains limited, generating excellent work prospects for those in this industry. Today, it is nearly hard to find a brand that does not have a social media presence; eventually, every firm will require data analytics people.
• Helps in Informed and Improved Decision Making: Companies are better positioned to produce accurate forecasts when big data is combined with artificial intelligence, machine learning, and data mining. Predictive analytics, for example, can forecast what might happen in reaction to changes in the business, whereas prescriptive analytics might recommend how the organization should respond to these changes. Furthermore, organizations can utilize data analytics tools to measure the success of changes and visualize the results, allowing decision-makers to select whether to implement the changes across the organization.
• More Successful Marketing: What distinguishes firms is the distinct strategy they take to marketing their products. Companies can use data analytics to pinpoint exactly what their customers want. Data allows organizations to do in-depth analyses of customer trends, which they can then use to produce profitable, focused, and targeted marketing.
• Better and More Personalised Customer Experience: Customers expect firms to know them, form relevant conversations, and give a seamless experience across all touchpoints after giving their data. Only modern analytics makes it feasible to respond in real-time and make the customer feel appreciated. Data enables interactions to be adjusted to the customer's personality, assisting in the understanding of their sentiments and delivering personalization in a multi-channel service environment.
• Streamline Operations: MBA in Data Analytics graduates can help businesses uncover potential methods to streamline procedures and increase revenue. It aids in recognizing possible problems and preventing them from occurring. This enables businesses to determine which operations delivered the best overall results under various conditions.
• Become Rock Stars of the Digital World: Since the job of a data analyst is unlike any other in the business world. As a result, the status of a data analyst is comparable to that of a rock star. Competent training in data analytics will transform you into an organizational magician, and you will be spinning insights by toying with large data. Thus, it is all about living up to and remaining true to the expectations that others have placed on you. Data does not lie, but it takes top data analysts' abilities to uncover the harsh facts and set a business on the royal route to success.

MBA programmes are often meant to improve your workplace experience by providing advanced topic knowledge and skill development. The type of MBA in Data Analytics programme you eventually choose is determined by your job goals, the amount of experience you have, and the amount of time you have to devote to your degree. Let us go over the many MBA degrees available to you:

• Full-Time MBA in Data Analytics: Full-time MBA programmes are divided into two categories: one-year and two-year programmes. Whatever path you pick, you will be expected to attend classes full-time and not work while obtaining your degree. A two-year MBA in Data Analytics programme gives a more thorough education that is ideal if you want to expand your business knowledge, choose an area to specialise in, and potentially complete an internship near the end of your studies. A one-year MBA in Data Analytics programme, on the other hand, provides an accelerated timeline that allows you to graduate in less time. They are typically suitable for those with greater professional experience, a bachelor's degree in business, and the completion of specified prerequisite courses.
• Part-Time MBA in Data Analytics: A part-time MBA is a traditional MBA degree that does not necessitate taking time away from work. It is typically a more flexible curriculum intended for professionals with other responsibilities who want to further their business knowledge. Part-time MBAs are classified into two types: lockstep and self-paced. Lockstep is enrolling with a specific group of students (a cohort), whereas self-paced entails completing classes on a more flexible schedule.
• Online MBA in Data Analytics: An online MBA, like a part-time MBA, provides additional flexibility. There is no need to relocate, and you may finish classes on your computer. Both of these criteria frequently imply that you can continue working while pursuing your degree. Furthermore, you do not have to forego engagement with an online MBA. Many programmes are designed to promote virtual networking, peer-to-peer involvement, and other activities. Online MBAs can also be less expensive than on-campus MBAs.
• Executive MBA in Data Analytics: An Executive MBA (EMBA) programme is designed for professionals with 10 to 15 years of experience. They are intended to assist you to advance your professional career, often to the executive level, by expanding on your existing knowledge. EMBAs also allow you to work while pursuing your degree. EMBA programmes typically operate on part-time schedules, such as weekend classes, and allow you to complete your degree faster than regular part-time MBA programmes. Unlike full-time MBA students, who have summers off, you will most likely continue your education all year.
• Global MBA in Data Analytics: Business is becoming increasingly global. Enrolling in a global MBA programme can provide you with more networking possibilities and opportunities to discuss and exchange knowledge with people all over the world, which can help you create professional relationships and broaden your potential reach as a global business professional.

Semester-wise break up of the MBA in Data Analytics Syllabus is provided below.

Following are the subjects primarily studied in an MBA in Data Analytics course.

Enrollment or admission into an MBA in Data Analytics programme in India has varying prerequisites based on the eligibility criteria of various universities. Individuals with a bachelor's degree who wish to pursue their higher education can enrol in MBA in Data Analytics programmes at a variety of management schools. The generic eligibility criteria that aspirants have to fulfil are mentioned below:

• MBA in Data Analytics requires a bachelor's degree in a relevant field of study with some mandatory subjects too. This course is designed for students with a bachelor's degree in business administration who want to pursue an MBA in Data Analytics.
• To be admitted to the MBA Data Analytics degree programme, candidates must pass any one of the entrance exams like CAT, XAT, MAT, etc, which is accepted by the chosen university.
• Candidates must also have to pursue and pass personal interviews and group discussions to prove their candidature for an MBA in Data Analytics programme.

All the colleges providing admission into the MBA in Data Analytics will sort candidates on the basis of their scores in the entrance exam. There are many entrance tests conducted for MBA/ PGDM Admission in the country. Applicants can check out the type of colleges that accept the scores of these entrance tests provided below.

The majority of the questions on the MBA in Data Analytics entrance exams are of the MCQ type, therefore applicants must have a solid understanding of the exam pattern in order to perform effectively. Additionally, applicants need to acquire some innovative strategies in order to answer the questions accurately within the allotted time. On incorrect responses, there are occasionally negative markings. As a result, the applicant must take care to consider this fact and should only attempt to respond to a question when they are certain of the answer.

Before taking the entrance exam, applicants should solve sample question sheets, mock test papers, or previous year's question papers. Taking at least 25 to 30 practise examinations will help the applicant feel more confident.
Success on the MBA admission test depends on time management. The time allotted for each component must be divided among aspirants, who must strive to finish the full syllabus in the allotted time while also setting aside time for a speedy revision of challenging topics.
For better preparation, candidates may also enroll in online tutoring sessions or read the top reference books for entrance exams.

Many students look for the best MBA in Data Analytics admission process to advance their MBA application. This degree provides students with a competitive advantage in their careers. MBA education is essential for practically all employers since it allows them to learn about running their businesses. India is on a path of continual advancement, and with it, there will be great growth in the future for MBA in Data Analytics specialists. As a result, students should be aware that top-tier business schools in India employ a tough screening process to choose the best applicants. A basic admission procedure is provided below to assist students interested in pursuing an MBA in Data Analytics degree in India:

Step 1: Register and Apply for MBA Entrance Exams

MBA in Data Analytics admission at top MBA schools in India begins in the first week of August/September and finishes in the last week of November. During the registration window, candidates seeking admission to top MBA programmes should register and apply for the relevant MBA entrance exams, such as CAT/XAT/NMAT/MAT/SNAP/GMAT. The registration period for most national-level MBA entrance exams, such as the CAT and XAT, closes in September and November, respectively.

Step 2: Take the MBA Entrance Exams and Wait for the Results

Those who want to study a management course PGDM/MBA programme specialized in Data Analytics from top MBA institutions in India must take the CAT, XAT, NMAT, or any appropriate entrance test accepted by their target colleges and business schools offering MBA in Data Analytics.

Step 3: The Selection Procedure

Following the announcement of MBA exam results in January, most top business schools will shortlist qualified candidates for the final admission round based on exam scores, academics, diversity, work experience, and other parameters as determined by the respective B-school admission policy and weightage. The process is completed independently by each business school or institution.

Step 4: Complete the Final Admissions Round - GD-PI-WAT

All candidates who have been shortlisted will be asked to take part in a Group Discussion (GD), Written Ability Test (WAT), and Personal Interview (PI). Some B-schools also conduct GD and Extempore before the PI round, whereas others do GD-PI. Psychometric examinations are also given to students at several colleges. The final merit list will be created, and admission offers for the MBA FinTech programme will be issued based on their performance in the final selection round, the weightage given to entrance scores, academic profile and diversity, work experience, and gender diversity.

Here is a list of some of the most well-known and prestigious universities in India that provide MBA in Data Analytics course to aspirants:

The cost of an MBA in Data Analytics course in India is determined by a variety of criteria, including the type of university (whether public or private), the duration of the programme, location, course content, rating, reputation/goodwill, and more. The following graph represents the estimated yearly average fees for MBA in Data Analytics programmes at some of India's most prestigious institutes: 

With the incorporation of Data Analytics in the business world, numerous career opportunities have sprung up in the past couple of years. So, getting an MBA in Data Analytics abroad is worth considering if you are looking for a successful career in the field. The MBA in Data Analytics degree will help international students achieve professional status and expand their career prospects by advancing understanding, knowledge, and experience.

As per a report by the Bureau of Labor Statistics, it is estimated that about 96,500 new MBA in Data Analytics jobs will be created in the next 10 years, which is an average of 12% of growth in the industry. Lucrative job opportunities in the field are not the only reason one should go for MBA in Data Analytics abroad, but there are many other convincing reasons too which have been mentioned below.

• Excellent Networking: Pursuing MBA in Data Analytics will allow candidates to build a strong network of professionals around the world. Creating an excellent network will allow the graduates to seek better career opportunities and give them a chance to share their knowledge and skills which will be useful for their professional career in the long term.
• Diverse Job Opportunities: Studying MBA in Data Analytics degree from one of the top colleges in the world will help students get the best jobs in renowned organizations. If a student decides to come back to India after being graduated with MBA in Data Analytics abroad, then he can expect a plethora of high-paying career opportunities.
• Up-to-date with the Latest Trends: The top MBA in Data Analytics colleges in developed nations like the US or UK provide the best quality education to candidates and prepare them to stay updated with the latest trends in the market. By utilizing this knowledge in their jobs, they will help their companies serve their customers better.
• No Shortage of Jobs: An MBA in Data Analytics degree from a top college abroad will make sure that candidates will always be in demand and never feel a shortage of work. In times of recession or any other circumstance, companies will face challenges and they will need qualified Data Analysts to get an edge over their competitors.

The following are some world-class universities where students and aspirants can pursue MBA in Data Analytics or relatable degree programmes abroad:

The amount of data available to us is continually expanding, and making sense of this data to derive useful insights and interpretations has become increasingly vital. This is where data analytics comes into play. Data analytics is the study of big data using analytics, statistics, predictive analytics, and other optimization tools and approaches to communicate insights to relevant stakeholders. Data analysts can assist a company in making critical decisions such as cost minimization, customer happiness, and profit growth.

Companies all around the world have finally realized that generating value from data is no longer a competitive advantage, but rather a need. Data Analytics and Science have developed as fresh ideas in technology-driven enterprises because data is vital to the running and growth of an organization. According to current trends, the field is predicted to increase dramatically in the future, which is why many hopefuls are betting on it and choosing it as a career path.

The future scope of the MBA in Data Analytics programme is highly promising:

• After finishing the MBA in Data Analytics course, students might pursue further study.
• MBA in Data Analytics graduates can pursue an M.Phil or a dual Master of Philosophy programme in relevant fields. It will help students get a better awareness of the numerous difficulties relating to their subject of interest, as well as improve career chances with a reasonable salary.
• A student may choose to pursue a Ph.D. in Data Analytics or a similar area after completing their MBA in Data Analytics. Taking this course will improve job research abilities and lead to better positions as well as research chances with higher income and experience.
• MBA in Data Analytics students may also apply for numerous civil service posts through the Union Public Service Commission (UPSC), state PSCs, and the Staff Selection Commission (SSC), as well as many other government competitive tests.

Most people do not associate the terms data analyst or data engineer with magicians, although that is exactly what a data analyst does. You may seriously develop a career of your choice within the subject of Data Analyst because it is a large domain with several specialties depending on your core talents and hobbies. The following are some of the most interesting data analyst fields that are attracting a lot of interest.

Graduates with an MBA in Data Analytics degree can expect to make INR 6 lakhs to INR 15 lakhs per year as a beginning income, with the potential to earn INR 16-31 lakhs per year. In general, different job classifications pay differently. Aspirants should be aware that this compensation is not fixed and may fluctuate depending on several factors. A graduate's pay is affected by criteria such as designation, education level, experience, and location. The table below shows the average starting salary for MBA graduates in Data Analytics in India:

The top recruiters for graduates with an MBA in Data Analytics degree are as follows:

• Deloitte
• PayPal
• Dell
• Infosys
• Wipro Technologies
• HCL Technologies
• Mahindra Satyam
• Cognizant Technology Solutions (CTS)

Candidates aspiring for an MBA in Data Analytics must possess the following skills.

• Analytical Ability: The most fundamental skill you must have is analytical ability. This implies you can work with massive volumes of data and comprehend the patterns, correlation, causality, linkages, and connections that exist inside those mountains of data. Aside from that, you must be able to communicate effectively with all stakeholders in the firm. 
• Communication Skills: You will be requested to convey your findings more frequently than not, therefore you must be able to make the other person comprehend what you want him to understand and have excellent communication skills. Another skill that a data analyst must develop is critical thinking. Ideally, there should be no doubt about what the data analyst recommends.
• Mathematical Knowledge: Since data is a data analyst's bread and butter, he must be adept at mathematics. Last but not least, you should have an eye for detail, which will help you solidify your place as a highly sought-after data analyst in the long run.
• Programming knowledge: R and Python are the two languages that must be learned by the candidates. Statistical and scripting languages can be divided into two groups according to whether compilation is required before execution.  
• Data: Basic arithmetic abilities, particularly in statistics, are necessary for data analyst professions. For large datasets, it's preferable to utilize a robust programming language like R, but Microsoft Excel's statistical features can manage smaller ones.
• Data Processing Platforms: Data analysts frequently employ big data processing systems like Hadoop and Apache Spark for massive data volumes. Data analysts may use these frameworks to search for data across many devices, clean, model, and analyze it to acquire a deeper understanding of correlations and patterns.
• Visualization: Tableau is one of the most used tools for data visualization. In order to create graphical representations of the results, data analysts might query data contained in relational and cloud databases, spreadsheets, and online analytical processing (OLAP) arrays.
• Machine learning: Any massive data analysis starts with automation. Computers may now automatically acquire new skills and complete tasks without explicit programming thanks to machine learning (ML). To solve particular issues, data analysts must understand how to develop, implement, and train the most relevant models and algorithms on datasets.

The main differences between Data Analytics and Big Data have been provided below.

The main differences between Data Analytics and Data Science have been provided below.