What is Business Analytics?

Today’s world involves an enormous amount of digital data. By the end of 2021, internet users were creating 2.5 billion gigabytes of data daily. It’s estimated that by 2025, more than 200 zettabytes of data (a billion terabytes) will live in the cloud.¹ Using data analytics, this vast quantity of data can be organized and examined to glean insights and make forecasts. Business analytics (or business data analytics) relates specifically to business, allowing companies to use insights, identify trends and embrace data-driven decision making.²

The data scientists and business leaders who understand the language of data, and who can render its fundamental patterns into actionable insights, have a unique power to redefine corporate strategies, enhance agility and improve profitability.

Keep reading to learn about business analytics—what it is, the four analytical models, and how organizations use analytics for various purposes, such as assessing strategies and predicting future trends, to make companies more profitable.

What is business analytics, exactly? Business analytics uses various methods to gather, process and analyze large amounts of data, transforming it into actionable information to make more informed business decisions. Business analysts use a wide range of tools and techniques, such as data aggregation, text and data mining, Big Data analytics, forecasting and predictive analytics, data visualization and storytelling and what-if data analysis using simulations.^3,4

There are four types of business analytics, which are used for different purposes. They can be combined to gain a deeper understanding of business performance, to solve problems and to help leaders make data driven business decisions to gain a competitive advantage. For example, a company might look at customers’ actions over time, examine their motivations, forecast what they might want in the future and determine how to address those needs.⁵

This is the most basic and common form of business analytics.⁵ It consists of traditional business intelligence as well as visualization tools such as tables, graphs, charts and narratives.⁶ Information such as metrics, key performance indicators (KPIs) and historical business reports are examined to track patterns and trends in past and current data, to better understand what has happened within the business.

This advanced type of analytics is used to examine why things happened and identify causes of trends and events.⁵ It relies more heavily on data science methods—such as data discovery, data mining, drill-down and correlations—than descriptive analytics does.

This approach uses various data science methods, such as predictive modeling, pattern matching, advanced statistics and forecasting, to anticipate what will likely occur in the future and how it might impact the business. Predictive analysis helps an organization analyze how events, emerging trends and challenges will make an impact on business.⁵

The most advanced business analytics model, prescriptive analytics informs a company regarding what it should do to achieve a specific goal or outcome. This may require advanced data science methods such as machine learning.⁵

According to a report by business intelligence company MicroStrategy, 94% of business leaders say that data and analytics are essential to their organizations’ growth and digital transformation.⁷ Businesses use data analytics techniques to track performance, make fast and accurate decisions, identify current trends and predict outcomes, learn how to foresee and respond to unexpected events, and gain insights that lead to growth and innovation.⁸

Embracing a business analytics strategy can help strengthen your company by:

Discover which strategies are working and which aren’t. Analytics provides a clear picture of what’s moving the company forward so that you can invest more in that area for further growth. For example, by tracking employee hours, behavior and performance, a company might see that certain departments are understaffed and, as a result, are less productive. A solution may be to hire additional team members.⁹

The ideal company mission is to improve operational efficiency and customer service while lowering costs. With business analytics, you can use certain metrics to compare the level of productivity with expenditures.

A business intelligence solution is far superior to manual data entry since it brings different data sources into the system in real time, letting you regularly monitor important indicators. This allows for more nimble responses, which might include improvements or even company restructuring. Automating manual reporting can greatly reduce your company’s operational costs.⁹

By analyzing consumer behavior, market trends and business performance, you can make smarter decisions that keep your business clear of difficulties. You can automate various data processes, freeing up employees so that they can spend more time on higher-level responsibilities. For example, in the insurance industry, analytics can be used to inspect claims carefully, in the service of preventing fraud.⁹

Understanding customer preferences and behavior is the first step toward building a more responsive business and increasing customer satisfaction. Business analytics observes this essential data in real time so that companies can more successfully cater to their customers’ needs and desires. This may involve changing company policies or setting up an in-house customer service team.⁹ The goal is to reduce churn—that is, when customers stop associating with a company due to dissatisfaction.

By using business analytics to assess leads and analyze customer behavior patterns, you can ensure that you focus on the leads that seem most promising. A business intelligence application would be able to examine many variables to compute which past customers are likely to make future purchases. This enables your organization to be more efficient in its marketing campaigns.⁹

According to an Accenture report, 91% of consumers are more likely to do business with brands they’re familiar with and that provide recommendations and offers that are relevant to them.¹⁰ To create personalized marketing effectively, your company can use business analytics and segmentation to know what your customers want and provide them with a more personalized experience.⁹

Business analytics is a fast-moving industry that’s changing all the time, which is why it’s essential to keep your knowledge and skill set up to date. With the right training, you’ll be prepared with the latest analytics skills to be highly competitive and advance your career. Many organizations have lucrative opportunities for qualified analytics professionals.¹¹

Earning a master’s degree in business analytics opens you up to a growing field. Data scientists are included in the list below, but it's worth calling out that the 36% projected growth through 2031 is much faster than average for all professions.¹² Additionally, data scientist was ranked #3 in Glassdoor’s list of Best Jobs in America for 2022.¹³

Consider these analytics-centered careers as you look to join the ranks of business analytics professionals. The positions below are shown with their current median salaries and projected job growth for the decade of 2021-2031:

Designed for working professionals who want to embrace the power of data analytics and evolve their expertise in business, William & Mary's Online Master of Science in Business Analytics (MSBA) program empowers you to join a field of high-performing business analytics professionals by instilling the knowledge and skills that are in highest demand.

William & Mary’s Online MSBA program is designed to maximize your computing and modeling skills while honing your ability to apply data science to strategic business planning and business decision making. The program curriculum revolves around four dynamic pillars, and mastery of these pillars helps ensure that you graduate with a tangible advantage in a high-demand field, where opportunities are growing across industries and around the globe.

The rigorous curriculum covers probability and statistics with R and business modeling with python, both heavily used in data analysis.²⁰ You’ll graduate with the business analytics tools you need to succeed by going in depth on topics like business analytics, decision modeling, machine learning and predictive analytics, optimization and prescriptive analytics, Big Data and cloud computing, data warehousing for business intelligence and artificial intelligence applications for business.

Speak to an Admissions Advisor today to discuss how an Online MSBA from the Raymond A. Mason School of Business can impart the business analytics skills to make you a powerhouse.