Frequently Asked Questions On Data Science And Business Analytics

Data science and business analytics are integral disciplines in modern business operations. The two are closely related fields that involve analyzing data to derive insights and make informed decisions. Data science involves a combination of statistics, computer science, machine learning, and domain expertise to uncover patterns, trends, and relationships within data. Business analytics involves applying statistical methods, predictive modeling, and optimization techniques to interpret data and guide strategic decision-making and solve real world problems within organizations. Both the fields compliment each other.

Wondering if you’re cut out for a PGDM in Data Science and Analytics at Narayana Business School? Here’s a straightforward checklist to gauge your eligibility: 

1. Educational Background: A bachelor’s degree from a recognized university is a must. Make sure you’ve scored at least 60% or equivalent in your 10th, 12th, and graduation.
2. On the Verge of Graduation? Those in their final year or awaiting graduation results aren’t left out! You’re welcome to apply.
3. Field Specificity: If your bachelor’s degree is in IT, Engineering, or Statistics, you’re on the right track. This ensures you’re already familiar with some foundational concepts crucial for data science and analytics.
4. Narayana’s Own Test – NBSAT: You should have taken the NBSAT, a bespoke management entrance exam by Narayana Business School. It’s designed to gauge aspects like mathematical prowess, general awareness, verbal skills, and abstract reasoning.
5. Work Chronicles: While not mandatory, if you’ve dabbled in the professional world, especially in a relevant field, it could give you an edge. It’s not about the duration but the quality of your experience, showcasing your understanding of practical business scenarios.

Curious about the admissions process or need more details? Dive deep by visiting our admissions page. 

Yes, it can be said that data science and business analytics is the best career option keeping in mind the current and future market trends. The world operates on data and business decisions and its dependency is drastically expected to grow in the coming decades. There is an upsurge in the demands of data scientists and business analysts. Good news for you, At NBS, you are given the title of both.

In comparison data scientist are expected to earn between $50k to $150k per year. But at NBS, you learn masters in data science and master in business analytics, under one program, making you 10x more employable than just data scientists.

Yes, a data scientist can be a business analyst with Narayana Business School. While both of these fields require a special skill set, vision, caliber and focus, NBS Ahmedabad dedicated masters in data science and business analytics equips you with the knowledge of both. You learn management via data.

In general, yes! Big data course can be termed as a difficult course as it requires technical awareness of using and managing big data tools and techniques, ability to understand numbers, and other statistical and programming skills. Go to big data page.

The final decision on if MS in data science or MS in business analytics, which is better, would depend on your innate skills and future career goals. However, at NBS, we free you from this decision as our master in data science and business analytics nurtures you to be the masters in both fields.

Narayana Business School’s PGDM in Data Science offers an expansive curriculum, with more than 50 courses to enrich your understanding. You will learn Data Science Fundamentals, Statistical Analysis, Machine Learning, Big Data Analytics, Business Intelligence, Data Visualization, Predictive Modelling, and Data Mining. For More Details, Go To Course Curriculum

No coding background required for data science course. A prior coding pedigree, while beneficial, is not mandatory. Narayana Business School’s masters in Data Science and Analytics is tailored to imbue you with essential coding skills, all from a management perspective. The course is designed to ensure that even if you’re starting from scratch, you’ll emerge with a holistic understanding of both data science and its managerial applications.

In Data Science and Analytics, you dive deep into a plethora of specialized subjects, each designed to equip you with cutting-edge skills and a holistic understanding of the vast data landscape. At Narayana Business School’s PGDM program, here’s what you’ll unravel: 

1. Big Data Analytics: Delve into the world of vast data with tools specifically crafted for its navigation. This subject revolves around managing, processing, and analyzing large datasets to glean valuable insights.

    

2. Machine Learning Techniques & Application: Embrace the power of algorithms. Understand various machine learning models and harness them to make precise predictions and data-centric decisions.

    

3. Python / R for Future Managers: Script your success. Get acquainted with the titans of data science languages – Python and R. Learn how to wield them to weave data magic.

    

4. Business Analytics, Intelligence & Forecasting: Decode the past to foretell the future. Use statistical techniques and predictive models to understand business trajectories and steer them towards success.

    

5. Enterprise Data Visualization: A picture speaks a thousand data points. Master tools like Tableau and Power BI to turn complex data into compelling visuals that narrate clear stories.

    

6. Data Warehousing & Data Mining: Unearth the hidden treasures in data. Learn how to store vast amounts of data efficiently and mine it for patterns and insights.

    

7. Deep Learning & Reinforcement Learning: Dive deeper into the neural realms. Understand the intricacies of multi-layered neural networks and leverage reinforcement learning to make adaptive decisions in dynamic scenarios.

    

8. Social Media & Social Networks Analytics: Navigate the digital social labyrinth. Extract and analyze information from the buzzing world of social media, and study the intricate web of social networks.

    

9. Time Series & Forecasting Techniques & Analysis: Time-travel with data. Learn to predict future trends based on historical patterns, a skill invaluable in sectors like finance.

    

10. Natural Language Processing: Speak the language of machines. Delve into techniques that help machines understand and respond to human language, opening doors to tasks like sentiment analysis and chatbot development.

     

11. With such a rich and diverse curriculum, you’ll emerge from the program equipped to tackle the challenges of the modern data-driven world. 

Data Science and Analytics have become an indispensable tool for numerous industries as they strive to harness the power of data to make informed decisions, enhance customer experience, and gain a competitive edge. Here’s a closer look at the top industries and their utilization of Data Science and Analytics: 

1. E-commerce: In the digital marketplace, data reigns supreme. E-commerce giants rely on Data Science for understanding customer preferences, predicting buying patterns, personalizing shopping experiences, optimizing prices, and forecasting demand.
2. Finance and Banking: With vast amounts of transactional data, financial institutions harness analytics for tasks like credit risk assessment, fraud detection, customer segmentation, and algorithmic trading.
3. Healthcare: Data analytics in healthcare focuses on improving patient outcomes, enabling precision medicine, optimizing treatment plans, and aiding in cutting-edge drug discovery.
4. Retail: Bricks and mortar or online, retailers leverage data for inventory optimization, customer insights, market basket analysis, and tailoring marketing strategies to consumer behaviors.
5. Manufacturing: In the era of Industry 4.0, manufacturers are turning to data analytics for process optimization, quality assurance, predictive maintenance, and supply chain efficiency.
6. Telecommunications: Telecom companies harness the power of data to improve network efficiency, forecast infrastructure needs, reduce customer churn, and tailor marketing strategies.
7. Transportation and Logistics: Efficiency is key in this sector. Analytics aids in route optimization, demand forecasting, managing fleet operations, and ensuring smooth supply chains.
8. Energy and Utilities: Companies in this sector use data analytics for forecasting demand, optimizing grid operations, improving energy conservation measures, and predicting equipment failures.
9. Government and Public Sector: Governments around the world employ data analytics for better policy-making, detecting fraud, optimizing public health strategies, and enhancing public safety measures.
10. Media and Entertainment: In the age of streaming and digital media, companies utilize data analytics for content recommendations, understanding viewer preferences, optimizing advertising strategies, and predicting content trends. 

In summary, while the application of Data Science and Analytics may differ, its significance is universally recognized across sectors, driving innovation and ensuring growth. 

The Post Graduate Diploma in Management (PGDM) with a specialization in Data Science and Analytics offers a comprehensive gateway to numerous promising career avenues. Given the increasing reliance on data in today’s digital age, professionals with expertise in data science are highly sought after in various sectors. Here’s a deeper dive into the scope of PGDM in Data Science: 

1. Data Scientist: Often dubbed ‘the sexiest job of the 21st century,’ data scientists decipher complex datasets to derive actionable business insights, developing models that predict future trends.
2. Data Analyst: These professionals dive deep into data to discern patterns, ensuring that businesses have the actionable insights they need to make informed decisions.
3. Business Analyst: Bridging the gap between data and decision-making, business analysts utilize data-driven insights to optimize operations and improve overall business strategy.
4. Machine Learning Engineer: With the ability to create algorithms that can learn from and make decisions based on data, they’re at the forefront of technological advancements.
5. Data Engineer: Tasked with ensuring that vast amounts of data are accessible and usable, data engineers play a pivotal role in any data-driven organization.
6. Data Architect: Designing robust data systems and structures, they ensure data accuracy, availability, and security.
7. Data Visualization Specialist: Through the creation of intuitive graphs, charts, and other visual tools, they present complex data in a digestible format.
8. Data Consultant: Acting as the bridge between businesses and data, these consultants ensure companies harness the power of their data to its fullest potential.
9. Risk Analyst: By analyzing potential risks and trends, they help businesses navigate uncertain terrains.
10. Research Scientist: Delving deep into research, they advance the field by developing new techniques and methodologies in data science.
11. Quantitative Analyst: Key players in the financial sector, ‘quants’ harness mathematical models to predict market movements.
12. Healthcare Data Analyst: In the rapidly evolving healthcare sector, these analysts optimize patient outcomes through the analysis of vast amounts of medical data.
13. Supply Chain Analyst: They streamline and optimize every step of the supply chain process, ensuring products move efficiently from manufacturer to consumer.
14. Social Media Analyst: Tapping into the digital pulse, they gauge public sentiment and analyze online trends to shape social media strategies.
15. Fraud Analyst: Safeguarding businesses, they detect anomalies and potential fraudulent activities, ensuring the organization’s security.
16. Data Journalist: Blending the art of storytelling with data analytics, they unravel compelling stories buried in numbers.

And more… As the digital transformation continues to evolve, new roles and specializations within data science and analytics are continually emerging. 

In essence, a PGDM in Data Science opens up a multitude of opportunities across sectors, equipping students with the tools to be at the forefront of the data revolution. 

The field of Data Science & Analytics has witnessed exponential growth, leading to substantial interest from global corporations and startups alike. Graduates of a PGDM in Data Science & Analytics are in high demand, and numerous top-tier companies actively recruit talent from this domain. Some of the prominent recruiters include: 

1. Accenture: A global professional services company, specializing in IT services and consulting.
2. Adani Gas: Part of the Adani Group, they focus on energy solutions and infrastructure.
3. ICICI: One of India’s leading private sector banks offering a wide range of banking and financial services.
4. Aptus Data Labs: An end-to-end data science solution provider.
5. Bombardier: A multinational aerospace and transportation company.
6. Capillary: A SaaS-based customer engagement and retention platform catering to retail businesses.
7. Crayon Data: A data analytics and AI company that provides business solutions.
8. Deloitte: A global consulting firm offering audit and assurance, consulting, risk and financial advisory, tax, and related services.
9. Ernst and Young (EY): Renowned for its commitment to building a better working world, EY offers services in assurance, advisory, tax, and transactions.
10. Global Analytics: An analytics solutions company.
11. IBM: An international tech company known for its contributions in IT services, cloud solutions, and hardware.
12. Infosys: A multinational corporation providing IT consulting and services.
13. KPMG: A global network of firms providing audit, tax, and advisory services.
14. LinkedIn: The world’s largest professional network and platform.
15. Panasonic Life Solutions: Known for their electrical construction products, they also delve into data solutions.
16. PwC (PricewaterhouseCoopers): A multinational professional services network, specializing in consulting and audit services.
17. Quantiphi: An AI-first digital engineering company.
18. Reliance Group: A conglomerate holding company involved in numerous sectors including telecommunications, petrochemicals, and retail.
19. Subex: A company specializing in analytics for telecom operators.
20. TCS (Tata Consultancy Services): An IT services, consulting and business solutions provider.
21. Tech Mahindra: A leading provider of IT, networking technology solutions, and BPO.
22. Tiger Analytics: A global analytics consulting firm.

For a comprehensive list of recruiters and more details, you can visit the [homepage](Insert link).

The intake for the PGDM in Data Science & Analytics program is 60 seats. 

The program follows a trimester pattern and the medium of instruction is English.

The fee for the PGDM in Data Science & Analytics program is Rs. 7,95,000/- for a duration of two years.

The assessment for each course under the PGDM in Data Science & Business Analytics program at Narayana Business School comprises two major components: Continuous Evaluation and Term End Examination. Each course carries a total of 100 marks. 

1. Continuous Evaluation (50 marks, 50% weightage): This component encompasses a range of evaluation techniques such as assignments, quizzes, projects, presentations, and class participation. Designed to consistently gauge a student’s grasp, development, and application of course content, these evaluations are spread throughout the course’s duration.
2. Term End Examination (50 marks, 50% weightage): Held at the culmination of the course, this examination aims to assess the student’s overall comprehension and retention of the material taught during the term. 

The final assessment score for each course is derived by amalgamating the scores from both Continuous Evaluation and the Term End Examination. 

The passing criteria for the PGDM in Data Science & Business Analytics program at Narayana Business School is grounded in the grading system. Here’s a breakdown: 

• The highest attainable Grade Point (GP) for any course is 10, which is equated to an “Outstanding” grade. 
• To successfully pass a course, students must achieve a minimum Grade Point of 4, synonymous with a “PASS” grade. 

• For a student to be deemed successful in a course, they must meet the passing criteria for both the Continuous Evaluation Components and the Term End Examination individually. 
• It’s crucial to emphasize that to be classified as “PASS” in a specific course, a student has to secure at least 40% absolute marks in every passing head. Failing to achieve this benchmark will result in the student being labeled as “FAIL” for that particular course. 

YES! Pursuing masters in data science and analytics is worth it as it is the #1 demanded industry right now, equips you with multiple industry knowledge, and the world is experiencing a crunch of skilled data scientists. On the other hand, data scientists are expected to be the highest earners in the corporate world in the future with an average $100k per year.

To qualify for the PG Data Science course at Narayana Business School, candidates must meet the following criteria: 

1. Secure a minimum of 60% marks or its equivalent grade in their 10th, 12th, and graduation levels.
2. Candidates should have completed their undergraduate studies in fields related to IT, Engineering, or Statistics. 

Those who satisfy these prerequisites are considered eligible for the program. To glean more insights about the course, prerequisites, or any other relevant information, continue exploring further details.