Intro to Data Analytics for Business Students

By: Jada Jones , Class of 2026

Businesses rely on data analytics to make better decisions, improve efficiency, and gain a competitive advantage. For business students, developing analytical thinking and data skills is no longer optional, it is a critical career asset.  

What is Data Analytics? 

Data analytics can be described as “the process of collecting, transforming, and organizing data to draw conclusions, make predictions, and drive informed decision-making" (Coursera). Rather than relying on intuition, businesses use data to understand past performance, identify patterns, and anticipate future outcomes.  

What Tools Are Used For Data Analysis? 

Common tools used for data analytics are Excel (basic analysis), SQL (working with databases), Tableau or Power BI (visualization), and Python or R. 

Data Analytics Concepts Everyone Should Know 

Key concepts that every business student should understand include data quality, data visualization, correlation versus causation, and ethical data use. High-quality data is essential because poor data leads to unreliable predictions, which can lead to poor decisions. Data visualization helps make complex information easier to understand, especially for non-technical audiences, such as co-workers from other departments or stakeholders. Understanding the difference between correlation and causation is critical, since related variables do not always imply a cause-and-effect relationship. Ethical data ensures data is handled responsibly, helping prevent bias and discrimination. Together, these concepts support accurate, meaningful, and responsible analysis.  

Conclusion 

For business students, learning the basics of data analytics, and gaining analytical thinking skills, provides a powerful toolkit for understanding complex problems and making informed decisions. By mastering foundational concepts, gaining exposure to key data analysis tools, and exploring real-world applications, students can position themselves for success in an increasingly data-driven environment.  

Source 

Coursera Staff. (2025, October 13) Data analytics: Definition, uses, examples, and more. Coursera https://www.coursera.org/articles/data-analytics?msockid=2474491b3d9362e30ded5c743cf26359