Data Analytics vs. Business Analytics

In today’s data-centric world, the terms “data analytics” and “business analytics” are often used interchangeably, creating a cloud of confusion around their unique roles and applications. Although a great deal of overlap exists between the two fields, they also differ from one another in important ways. Read on to learn how each field is distinct and which key aspects of data analytics apply to business analytics.

What Is Business Analytics?

Business analytics uses quantitative methods and various tools to turn data into meaningful insights that enable businesses to make informed decisions. In a data-driven world, they are essential for businesses to improve efficiency, productivity, decision-making, and financial performance, and they empower professionals to influence their organizations by supporting arguments and recommendations with data-backed evidence.

There are four primary methods of business analytics: descriptive analytics, which interprets historical data to learn what happened; diagnostic analytics, which determines why it happened; predictive analytics, which forecasts what will happen based on past and/or current data; and prescriptive analytics, which recommends what to do to optimize results in specific scenarios. Depending on the method used, the field encompasses elements such as data management, data visualization, predictive modeling, data mining, forecasting, simulation, and optimization.

Data Analytics Defined

Data analytics is the multidisciplinary science of deriving actionable insights from raw data. It generally follows a process involving data collection and storage, data processing and organization, and data analysis and visualization. It employs spreadsheets, programming languages, and visualization software to identify and display useful information from datasets. Conducting accurate data analysis draws on the disciplines of statistics, mathematics, and, in many cases, computer programming.

While data analytics is a key component of business, it also applies outside the business world. For example, educational institutions apply data analytics to student performance data, attendance records, and learning outcomes. This information can be used to identify areas for improving academics, allocating resources effectively, and enhancing the learning experience.

How to Mix Business Analytics and Data Analytics

A subset of data analytics, business analytics employs key steps from that analytical process within a business context. Whereas data analytics entails the full lifecycle of data collection and storage, data processing and organization, and data analysis and visualization, business analytics tends to focus on data processing and organization and data analysis and visualization to interpret data, obtain insights, and communicate those insights to motivate business decisions.

Since data collection and storage generally fall outside the scope of business analysts’ responsibilities, they do not use the specific programming skills required for these lifecycle stages.

Montclair State University’s MS in Business Analytics

Delivering a strong foundation in using data to solve business problems, Montclair State University’s Master of Science in Business Analytics (MSBA) prepares students to succeed in this exciting field.

Through their coursework, students acquire deep knowledge of data analytics and methods such as statistical and predictive modeling, analyzing structured and unstructured data, and analytical reporting. They then finish the program with an applied industry-based practicum that puts their new skills to work in real-world situations.