Importance of Pursuing Management Degrees in Business Analytics and Data Science

Global Data Landscape

The rate of adoption of data and AI tools has been promising. McKinsey’s 2024 survey shows that 65 per cent of organisations are now using generative AI in at least one business function, which is a sharp increase from 33 per cent a year earlier. Industries such as banking, healthcare, retail and manufacturing are already using AI to cut costs, enhance customer experiences, and redesign business models.

This sudden boom in adoption shows the rising need for professionals who can manage, analyse, and strategically implement these technologies. Graduates in Business Analytics and Data Science are expected to bridge this demand.

Data Growth and Complexity

The main challenge lies in handling the complexity and scale of the data. McKinsey projects that data volumes will increase by 10 times by 2030, with 90 per cent of it being unstructured (text, images, audio, and video). Traditional business models are not capable of processing this kind of information at scale.

It can be a great opportunity for Business Analytics professionals as they learn to interpret large data sets for strategic decision-making, while Data Science graduates work more on the algorithmic aspect to process and extract value from the data. Both skill sets are essential in the upcoming era.

Why Business Analytics and Data Science Matter Today?

According to McKinsey’s report, businesses that lead in digital and AI adoption earn far higher returns than their competitors. For example, digital and AI leaders in retail and customer goods saw 9.4 per cent annual shareholder returns, compared to 3.2 per cent for others. While those in energy and materials gained 11.6 per cent vs 5 per cent for others.

In addition, McKinsey estimates that generative AI alone could deliver US$2.6 to 4.4 trillion in economic value annually across industries, when applied to about 63 use cases. This shows that both analytics and data science are not optional extras- they are central to how businesses succeed today.

Why Is It Important?

Bridging Business and Technology- Most businesses struggle not with the data but to derive insights from it. A Business Analytics graduate knows how to interpret insights and communicate them to decision-makers.

Leadership and Communication- Beyond technical skills, these degrees focus on teamwork, leadership, critical thinking, and presentation skills. All these are critical for management roles.

Impact on Growth- Companies use Business Analytics to personalise marketing campaigns, improve supply chains, and optimise their pricing strategies. These activities directly impact the profitability of a company.

Data Science

A Data Science degree is more technical. It focuses on programming, machine learning, artificial intelligence and statistical modelling. Students learn to work with large data sets, build algorithms, and develop AI tools that can predict or automate decisions.

A critical insight from McKinsey’s report is that many organisations struggle to move beyond pilot projects in AI- known as “pilot purgatory”. While companies often test innovative solutions, scaling them is difficult due to governance, infrastructure, and leadership gaps.

Why Is It Important?

Driving Innovation- Data Science is crucial for innovations such as recommendation engines (used by Netflix, Amazon), fraud detection in banking, and even medical diagnostics.

Core of Generative AI and Machine Learning- According to McKinsey, these fields could contribute 0.5 to 3.4 per cent annually to global productivity growth if adopted widely.

High Demand for Skills- Skilled data scientists are among the most sought-after professionals worldwide, and their technical expertise often commands higher salaries.

How Business Analytics and Data Science Complement Each Other

Business Analytics focuses on decision-making. Data Science focuses on problem-solving through models and algorithms. Business Analytics graduates often serve as the link between technical teams and management, ensuring that data is used effectively to inform strategy. Data Science graduates frequently build the systems and tools for advanced analytics.

Career Opportunities in Business Analytics and Data Science

Pursuing careers in either of the disciplines is promising. McKinsey reports that companies are actively investing in upskilling employees and hiring new positions for data and business analytics roles. 69 per cent of companies in India are focusing on recruiting data and analytics professionals.

Skill Gaps and Emerging Careers

McKinsey reports that only 50 per cent of Chief Data and Analytics Officers (CDAQs) feel confident in driving innovation at scale, and 70 per cent of organisations struggle with governance challenges in data and AI. McKinsey lists three essential areas where Data leaders should be skilled-

• Governance and Compliance

• Engineering and Architecture

• Business Value

Emerging Career Opportunities and Expanded Job Responsibilities

According to McKinsey’s report, managing new skills in generative AI will lead to expanded responsibilities of existing job roles, and some new career options will emerge-

Existing Roles With Enhanced Job Responsibilities-

• Data Architects- Ensure enablement of Generative AI capabilities for business needs and integration into the existing data ecosystem.

• Data Engineers- Collect, process, and store unstructured data

• Data Modellers- Build data models to incorporate both structured and unstructured data.

• Data Scientists- Design, Test, and Deploy Gen AI models.

Emerging Career Options-

• AI Ethics Stewards- Ensure that AI systems are developed and used ethically with proper risk management.

• Prompt Engineers- Develop and refine prompts for accurate responses.

• Unstructured Data Specialists- Define business requirements to prepare for unstructured data.

The Future of Data-Driven Enterprises

McKinsey envisions that by 2030, companies will operate in an environment where data and AI are embedded in “everything, everywhere, all at once”. From supply chains to HR to customer service, every business function will depend on AI-driven insights.

For students today, this means pursuing a future-oriented degree in disciplines such as Business Analytics, Data Science, and Artificial Intelligence.

Conclusion

The importance of pursuing management degrees in Business Analytics and Data Science cannot be overstated. With global data volumes expanding, AI adoption is increasing, and businesses are thinking of ways to overcome the scaling challenges; the demand for business analytics and data science professionals has increased significantly.