Reasons to Learn 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.”

3 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.

1. 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.

2. 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.

3. 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.

Published by analyticsteppercmu

The Tepper School of Business, founded in 1949, pioneered the discipline of management science, challenging the academic orthodoxy of the time, which championed the case study method as the primary way to solve business problems.

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