The Benefits of Learning Data Analytics From a Business School

Companies in almost every industry now collect vast amounts of data about their customers, competition and supply chains. But gathering information is relatively simple. Discovering the full value of data analytics in business is a constant challenge.

That’s where the efforts of business analytics professionals become critical. Back in 2012, the Harvard Business Review heralded the importance of these roles by declaring that data scientists had “the sexiest job of the 21st century.” Many organizations have since realized that the big data professionals who really turn heads are the ones who take the next steps, going beyond data analysis and adding the “what’s next” factor. These professionals play an essential role in developing and implementing business strategies.

While there are plenty of graduate schools that offer master’s degrees in analytics, choosing the right educational path could make a big difference in your career. A business school big data analytics curriculum teaches the concepts, tools and techniques to guide an organization’s growth and transformation — going well beyond basic data analysis and statistics. If you’re ready to take the lead in making quantitative information really count, a Master of Science in Business Analytics from an internationally renowned school of business provides advantages that you won’t find in other programs.

How Does Data Analytics Play a Vital Role in Today’s Business World?

Data is raw material that can be forged into powerful solutions for furthering an organization’s objectives. Analytics professionals develop the systems to organize and structure quantitative information, identify valuable insights and create reports and visualizations to convey their findings. These steps lay the foundation for actionable business intelligence, helping leaders to understand their organization’s position in the marketplace and make informed decisions about how to stay ahead of their competition.

Most organizations today have already built some of that foundation—they’ve begun collecting data and running descriptive analytics tools like dashboards. What many companies still need, however, are the supporting elements to conduct predictive and prescriptive analytics processes and successfully take action.

Gartner predicted that through 2022, only 20% of analytics initiatives will deliver on business objectives. What’s happening to the other 80%?

It’s easy to fall into a technology-first approach when thinking about analytics, but the most common causes of failed analytics projects are not the wrong tools or a lack of technical proficiency. In fact, many of these issues are business problems:

• Asking the wrong questions
• Failing to define a clear purpose for collecting data
• Selecting the wrong uses for analytical methods
• Lack of supporting business culture

It takes technical expertise and business acumen to establish the conditions for analytics to thrive. Leaders must know which technologies to use, when to deploy them and how to optimize the outcomes. According to Bryan Routledge, an associate professor of finance at Carnegie Mellon University’s Tepper School of Business, quantitative thinking has become an indispensable aspect of leadership.

“You need to see the big picture of how this data might be connected to this problem and able to drill down a bit deeper and see what the sub-problems are that you have to solve,” Routledge explained. “You might not have to write every line of code yourself, but you have to be able to see how these pieces fit together.”

7 Reasons to Learn Data Analytics from a Business School

What’s the difference between a company that has some interesting data at its disposal and a truly analytics-driven business? One important variable is the work of professionals who not only know how to write descriptive and predictive models, but how to achieve results. A graduate program in business analytics helps students build the expertise to deliver practical analysis and leadership based in the next generation of analytical methods.

These are just a few ways that an analytics education from a business department could prepare you to make a greater impact on your organization:

1. Find Connections that Matter

Quantitative methods answer pressing questions for stakeholders, but first you have to understand how to make the best use of data. When it comes to making the connections between analytics and decision-making, graduate programs are not all the same. For example, the data science or analytics degrees in computer science departments may not focus on the problems that are the highest priorities in today’s enterprises. By contrast, a multidisciplinary analytics degree from a business department equips professionals to confront urgent and intriguing issues at leading companies around the world.

In a business school environment, professionals find the resources to synthesize knowledge of data mining, programming and machine learning with strategic planning and communication, making a real impact on the organization. Insights into all these areas come from business analytics faculty who engage in cutting-edge research with real-world applications. Renowned experts who study the uses of data for management, finance, marketing and operations present students with unique perspectives on the challenges that will affect their careers and the future of business.

2. Communicate Persuasively

Organizations only reap the full benefits of an analytics strategy when everyone involved in planning and executing their strategies—including managers and employees on both technical and non-technical teams—understand the implications of their data. Analytics professionals with a business background can create compelling visualizations and reports but also have the overall communication skills to spur teams into action.

Carnegie Bosch Professor of Operations Research Willem van Hoeve described the ways a business analytics education can be especially valuable for engaging teams that cross multiple departments and functions.

“When managing an interdisciplinary team, being able to speak the language of the machine learning experts as well as the business users gives you not only credibility but also the opportunity to build bridges in an organization and truly leverage the power of analytics,” he said.

3. Predict What’s Next

Data professionals aren’t fortune-tellers, and analytics tools aren’t crystal balls. Nonetheless, predictive analytics enables an organization’s stakeholders to think ahead with algorithms that extrapolate from past data to determine what changes are likely over the months and years to come. These findings may reveal what products existing customers will probably buy next, warn cybersecurity teams about potential incidents of fraud or project the performance of financial assets.

Routledge researches quantitative methods to understand and predict market behavior. He has pursued his interests through projects such as modeling the dynamics of oil prices and probing for patterns in insider trading. He discussed how developing algorithms that help analysts foresee likely outcomes for stocks involves both exceptional challenges and great rewards.

“The thing that is different about a finance setting is the variability,” Routledge explained. “Stock returns are just hugely volatile; the data is so noisy. But the returns to getting just a tiny grain of signal out of this data are really big.”

4. Elevate Your Career

All kinds of companies are looking to hire data experts, but quantitative methods alone can only take you so far. Zachary Lipton, an assistant professor of business technologies at CMU, suggested that professionals who expand their horizons are best positioned to reach their career goals.

“If you’re really great at mathematics or software development, but you don’t know how to apply those techniques to a business problem, or you can’t communicate to other stakeholders in your organization, you’re not going to be very good at an applied machine learning or applied data science job,” Lipton said. “The highest demand is for professionals who have all three skillsets.”

5. Develop Unique Strategic Insights

Analytics now guides everything from marketing campaigns to hiring, and further changes are on their way. Big data fuels machine learning, natural language processing and other forms of artificial intelligence used in an ever-broadening range of applications. But capturing this information’s strategic value takes specialized understanding of data management principles, advanced analytical methods and organizational objectives.

Analytics experts with a strong background in business fundamentals are able to boil down a complicated mass of input into valuable insights. As Routledge pointed out, learning to situate data within a specific context is a huge help in eliminating noise and structuring information.

“Data doesn’t arrive as a clean Excel spreadsheet,” he said. “So, when you teach data analytics now, it’s not just teaching people how to run a regression or push something through a statistical tool. The skill is being able to take a bunch of data, align it, and then represent it.”

By applying software tools to the information they’ve collected and organized, analysts can then answer complex questions. Thus, integrating data analysis skills and business knowledge is often the difference between solving a critical problem and wasting time on initiatives that lead nowhere.

In-depth analytics based on multiple data sources bring leaders a nuanced view of internal processes and the competitive landscape, informing both immediate improvements and long-term plans for growth.

6. Know the Right Tools for the Job

Analytics solutions are never one size fits all. Every company has its own needs for data sourcing, organization and analysis. A solid grounding in business-oriented data analytics skills makes it possible to customize tools and processes accordingly.

New platforms and technologies hit the market at a rapid pace, and it’s an enormous challenge to keep up, much less stay ahead of the curve. Leaders who can draw on both business and analytics knowledge are able to guide the evolution of their organization’s technological infrastructure, ensuring data and analytics serve the requirements of individual teams.

Business analytics education readies professionals to choose and implement tools that closely match their organization’s demands, such as determining what business intelligence features are most relevant to certain decision-makers and generating visualizations that make those discoveries easy to understand. By learning how major companies currently deploy their tools and resources, analysts can optimize performance, scale operations and continue developing innovative ideas.

7. Turn Ideas into Execution

There are countless ways for analytics initiatives to go disastrously awry. Projects may backfire if professionals miss a vital detail during implementation, don’t adapt to changing circumstances or fail to account for their audience’s privacy concerns and emotions.

To avoid these missteps, companies must employ specialists with the technical expertise and business sense to anticipate challenges and make adjustments. Decision-makers are better equipped to avoid analytics-driven disasters when they combine extensive knowledge of the technical side of analytics with thorough knowledge of best practices and regulations.

A business-oriented education readies professionals to operationalize analytics and address issues like when to purchase ads, how quickly to ramp up production and how high to set prices for a new product. Machine learning algorithms can even automate and streamline many of the processes involved, proactively addressing errors and other anomalies before they become crises.

How Tepper Gives You the Edge in Business Analytics

Organizations that keep data management and organizational decision-making siloed miss out on opportunities for growth. That’s why companies need individuals who connect robust quantitative methods with sophisticated business strategy. A graduate education in business analytics provides the specialized knowledge and hands-on skills that allow analytics professionals to advance their careers, excel in leadership roles and make a difference in their organizations.

The online Master of Science in Business Analytics (MSBA) from the Tepper School of Business at Carnegie Mellon University helps students to develop proficiency in the full range of state-of-the-art business analytics techniques. A comprehensive curriculum that encompasses data visualization, machine learning and optimization, and large-scale data management readies professionals to take on complex challenges in tomorrow’s analytics-driven organizations.

Online MSBA students benefit from a world-class education through the internationally renowned business school that pioneered the discipline of management science. Courses are taught by CMU’s faculty of top researchers and creators who make multidisciplinary leaps in areas like machine learning, accounting, communication, finance, organizational behavior, marketing and operations management. The online MSBA equips graduates with an unparalleled education and connects them with an international network of professionals.