Data science is undoubtedly a technical field, but data science applications are concrete, tangible, transformative and rooted in strategically solving real-world business problems.
This arena is the focus of the online Master of Business Administration (MBA) with a concentration in Data Science program at Henderson State University. Intensive coursework helps students develop the technical knowledge and skills needed to excel. Yet programmatic studies further explore data science in the context of strategic decision-making, problem-solving, ethical reasoning, effective communication and managerial leadership.
This comprehensive, holistic approach to modern data science prepares graduates to utilize their expertise in many impactful ways. Here are three areas in which data science MBA grads can help address real-world problems in business and beyond:
1. Tackling Global Problems
As an exciting place to start, data scientists are instrumental in solving the most pressing challenges the modern world faces. A Forbes article highlights the impact that modern technologies, especially data analysis tools, can have on addressing social, environmental and health issues on a global scale.
Essentially, the authors maintain that the data and expertise needed to address global issues already exist. The key is leveraging and integrating collective skills and knowledge drawn from the private sector, nonprofits, nongovernmental organizations (NGOs) and governmental agencies worldwide.
Businesses recognize the impact they can have through partnering in such global initiatives. The private sector acts as the world’s engine for innovation and an incubator for ideas and strategies that challenge the status quo. As noted by Forbes, data science tools are central to applying such business innovations to solve global problems.
Data scientists uniquely understand the nuanced information and analysis needed to create solutions. Analytics technologies driven by artificial intelligence (AI) can aggregate and synthesize big data from vastly disparate sources. This process is necessary for making sense of siloed datasets from multiple repositories, countries, regions, organizations, disciplines of study and more.
Data science experts know how to drill into this data and get results. They work with AI technologies like machine learning (ML) and natural language processing (NLP) to distill accurate insight through predictive and prescriptive analysis. Data science professionals use data visualization and storytelling tools to translate such advanced research into actionable information that experts in other fields can understand and use.
This application is vital for the interdisciplinary, cross-sector collaboration needed to face the complexity of today’s global challenges. Data science leaders form the information and communication bridges among data, technology, analysis, decision-makers and effective strategy.
2. Providing Business Insights and Intelligence
Typical, business-oriented data science applications rely on the same practices, technologies and strategies described above. Data scientists help businesses organize, understand and explore their data assets to gain insight into business operations, problems and opportunities. This insight informs strategic, evidence-based decision-making to improve business outcomes.
In a post for KDnuggets, ReHack editor-in-chief Devin Partida explains that data science is also “instrumental in predicting events and preventing unwanted consequences.” The predictive and prescriptive capabilities of AI-driven analytics help business users predict trends or likely outcomes more accurately than antiquated predictive models or gut intuition. This insight supports improved strategy, planning and risk management while preventing the harmful results of inaccurate predictions.
Advanced analytics software can also detect outliers, anomalies and troubling patterns in fluid datasets. This ability is essential for solving complex business problems like identifying and addressing inefficiencies in supply chains or fraud in the financial sector. It is also central to cybersecurity practices as it can predictively prevent threats, test for vulnerabilities and address incidents in real-time with mitigation strategies.
3. Supporting Customer-Facing Business
Data science has completely reshaped modern customer-facing business practices. Mass marketing strategies of the past were highly impersonal and inefficient, lacking the ability to target audiences effectively and genuinely connect with prospective customers.
With a wealth of customer data, analytics capabilities and multichannel connection opportunities, businesses can now customize and personalize the customer experience, at scale, as never before. But, as pointed out in a Data Science Central article, “Personalization is exclusively concentrated on the improvement of customers` experience.”
Applications of data science to improving the customer experience can be seen across industries and customer-facing departments. Streaming services and eCommerce platforms use analytics to make personalized recommendations to consumers. Analytics informs the creation of targeted, customized marketing and entertainment content. AI-driven chatbots provide customers with quality, on-demand customer service.
All this requires incorporating data science into marketing, sales, brand reputation management, customer service and customer relationship management practices. The magnitude of personalization and information consistency facilitated by data science has, to a degree, broken down problematic boundaries between these customer-facing departments.
These are merely a few examples of the ways data scientists are impacting problem-solving and continuous improvement at every operational level of business. By earning an MBA in data science, data-driven professionals can develop the technical and leadership skills needed to tackle these problems and create innovative opportunities for modern businesses.