What is business analytics?

Data is the foundation upon which well-rounded decisions are built. Individuals make choices every day, but for business owners in particular — as well as professionals in general — the mission-critical actions they take can be highly consequential to their desired outcomes.

Leveraging accurate business data may not guarantee a successful outcome, but when it is truly reflective of a certain topic or subject matter — such as purchasing trends, as an example — data allows for them to make more informed decisions. Because there are so many ways to collect and parse data, thanks to advancements in data science and data visualization, organizations are in a better position to solve problems — perhaps more than ever before.

If data is your passion, or you enjoy identifying answers to specific questions, business analytics may be the industry for you. What is business analytics? What is its purpose? What are its key benefits and applications? We’ll answer these questions and more.

Learning more about business analytics could lead you to a new and exciting career as a business analyst, a field that is ripe with opportunity. You can prepare to join this field with the online Master of Science in Management Information Systems program. This comprehensive curriculum, available through the University of Alabama at Birmingham’s Collat School of Business, can supply you with the knowledge and skills to achieve your professional aspirations, all while maintaining your current job.

Understanding Business Analytics

Business analytics are the processes and procedures that organizations use to make more informed decisions. These processes and procedures may include statistics methods, predictive analytics, programming languages as well as modeling and machine learning. All of these methodologies are state-of-the-art and made possible by the ongoing advancements in technology.

Data is truly ubiquitous. Massive amounts are produced daily through the utilization of consumer electronics, smart devices, and other technologies. Much of this data is accessible. Business analytics focuses on obtaining this raw data, dissecting it through mathematical and statistical analysis, and then applying the results to help solve problems or identify solutions.

Douglas Laney, innovation fellow for data analytics strategy for the consulting firm West Monroe, tells U.S. News & World Report that this is the golden age of data science. Business owners would be wise to take advantage of it.

“The world of data is pretty extreme, and to not leverage it effectively puts a company in a competitive hole,” Monroe cautions. “[Business analytics] is simply about using data to generate insights.”

Just as data comes in different forms, so too does analytics, which is the computational analysis of data, otherwise known as statistics. Analytics can be grouped into three broad categories:

  • Descriptive analytics
  • Predictive analytics
  • Prescriptive analytics


Their descriptor defines their type. Descriptive analytics is just that — statistics that seek to understand events or actions as they are. Key performance indicators serve as a classic example of descriptive analytics. Business analysts might use descriptive analytics to draw conclusions about why an organization may be struggling financially, since descriptive analytics draws from historical data.


Predictive analytics is leveraged when decision-makers want to gain insight into what may happen. This is accomplished by examining where there may be similarities or trends in data. Here, historical data may also be used, but it’s parsed and input into predictive algorithms to get a sense of what may be to come. If a retailer or salesperson wants to advertise a product, but isn’t sure what method or medium will work best — a television advertisement versus an online banner, for example — they may use predictive analytics to assess which channel has historically resonated with buyers. Machine learning is also a product of predictive analytics.


Prescriptive analytics is a combination of predictive analytics and descriptive analytics. Here, historical data is used to determine the likelihood of previous outcomes recurring.

For example, if a restaurateur or franchisee is going food shopping and doesn’t know how much produce to purchase for the weekend rush, they may look at receipts or review inventory from previous weekends. If they recognize patterns, they may play out again. Capacity planning and product allocation are all forms of prescriptive analytics.

These processes allow business owners to effectively analyze data so decisions are rooted in gathered facts or intelligence.

What Are Business Analytics Tools?

Business analytics is a tool unto itself: It serves as a resource that organizations can leverage on an as-needed basis. But at the same time, businesses need certain tools, or equipment, to go about gathering data so they can interpret it and make practical use of it. Software is a type of business analytics tool. One of the more basic kinds is spreadsheets. Spreadsheets typically include statistical methods and functions that users can apply to their datasets so it can be more easily understood and extrapolated. Business intelligence tools can not only aggregate data, but they can perform the functions that make data readily usable and applied to business decisions.

Enterprise resource planning software is one of the more powerful business analysis tools available, which many organizations use today to increase visibility into their various work processes. They’re poised to continue leveraging these and other similar systems. According to Mordor Intelligence, the business intelligence sector is a multibillion-dollar industry, and it is expected to reach a valuation of $40 billion by 2026, up from $20 billion in 2020.

From predictive models to programming languages to data mining, business intelligence systems and methods are redefining how people go about managing their business to improve, grow, and prosper. And they are making regular use of them. According to a poll by Logi Analytics, the typical knowledge worker (e.g. physicians, programmers, engineers, scientists, etc.) devotes an average of five hours per day to analytics. Nearly all of those surveyed — 99% — said they found analytics to be “very” or “extremely” valuable toward making better decisions.

Given the rapid pace at which this industry is expanding — thanks in part to technological innovation — new ways to collect and scrutinize data may be just around the corner. As Laney points out, what is state of the art today may be obsolete before long.

“I really would not encourage anyone to get fixated on any kind of technology because it will be secondary in two to three years,” Laney tells U.S News & World Report.

This is a topic that is discussed more in depth in the three-credit course Emerging IT Trends & Tech, which is part of the Management Information Systems core in the online Master of Science in Management Information Systems program at UAB.

Where Can Business Analytics Be Applied?

The applicability of business analytics may be the single best aspect of this realm of data science. In short, it is universally applicable. You name the sector, business analytics is being leveraged. If business owners aren’t utilizing the solutions, they’re hiring someone to do it for them. Here are a few examples:

Social Media

Be it Facebook, Twitter, TikTok, or several other outlets, social media likely wouldn’t be what it is today — nor as popular — were it not for analytics. While many people log on to their accounts to connect with friends or relatives, they also utilize social media for news-gathering purposes. As a recent poll from Gallup shows, nearly three-quarters of respondents in 2020 say they used social media during the pandemic to help them stay connected. More specifically, 68% of users said they considered it helpful for getting up-to-the-minute updates on events of the day from news organizations, and 70% said it enabled them to receive guidance from public officials.

The information and posts that users see on their news feeds is largely determined by data analytics. The activities and engagements that users participate in while on the site play a role in what stories appear on screen. Here, social media operators utilize prescriptive and predictive analytics to make educated guesses as to what their users will be most likely to click on based on what they’ve selected in the past.

Businesses that seek to advertise on social media may also draw from such analytics to find out their target audience.


In a similar vein, marketing firms leverage business analytics. Whether they have a specialist who handles it for them or hire an outside consultant to deal with such tasks, a business analyst may deploy a variety of analytics tools to identify what campaigns resonated with users or to guide their forthcoming advertising strategies.


From the gas motorists use to fuel their car, to the kerosene used to heat their homes, massive amounts of energy are consumed daily to power everyday processes. Gas and oil producers have to make regular decisions about how much they need on hand at any given moment to avoid shortages or surpluses. Producers may deploy prescriptive analytics methods to form judgments about prices and extraction activities.


Supply chain management is a major ongoing task for manufacturers, regardless of what they produce. While professionals who work in this industry have long understood this fact, consumers at large became more aware of this reality during the height of the COVID-19 pandemic, when household name products that are typically easy to find — such as paper products and sanitizing equipment — were suddenly difficult to come by.

Given the unprecedented nature of the coronavirus crisis, it led to breakdowns and disruptions in the supply chain. Downtime, maintenance, inventory, and several other variables all factor into manufacturing decisions. Business analysts employ forecasting methods and metrics so manufacturers can have a more predictable supply chain.

You name the sector, business analytics has a seat at the table. This may explain why business analyst is a rapidly growing occupation. According to the U.S. Bureau of Labor Statistics, between 2019 and 2029, the number of jobs is expected to increase by 11%. The average growth rate among all occupations is 4%.

What Are Some of the Challenges in Business Analytics?

As the Logi Analytics survey referenced earlier illustrates, data analytics is a highly effective tool in enabling decision-makers to make better business choices. But like any method, it’s imperfect. Here are a few of them, some of which are discussed in the master’s course curriculum.

Data Overload

The sheer volume of data that is recorded is virtually impossible to fully comprehend. According to the blog Tech Jury, humans alone produce 2.5 quintillion bytes of data every day. With so much data to choose from, it can result in information overload or potentially obtaining the wrong kind.

Automation may play a role in the future to ensure data systems collect the right type and the proper amount.


Data is for naught if there is no one present to make use of it or analyze it. In those instances where data must be communicated from one stakeholder to another, it may be misinterpreted or used to draw conclusions that aren’t in line with what it actually suggests.

Here as well, automation may help to guard against communication breakdowns so decisions aren’t based on flawed analysis or interpretation.

Poor Data Quality

Good decisions must be rooted in sound data and intelligence-gathering practices. Just as individuals can form errant conclusions from good data, bad data can also lead stakeholders to form judgments on faulty science. This may have resulted from simple manual errors that occurred during data entry, evaluating the wrong metric or collecting data from the wrong source. Ideally, real-time data is the best kind of data to evaluate, so outdated data may be another example of poor data quality.

Data That Is Difficult to Access

While data may be ubiquitous, it’s not always easily accessible or obtainable. This complication may be due to poor collection processes, outdated legacy software systems, or logistical complications.

Cloud computing, enterprise resource planning software, centralized databases and several other data collection methods are making data accessibility much more feasible and less labor-intensive. As technology continues to advance and develop, these practices will become even easier, but will need to be complemented with robust data security measures so sensitive or privileged information doesn’t fall into the wrong hands.

What Are the Biggest Successes of Data Analytics?

No data collection strategy or science is perfect, but for every challenge that analytics may have, it has logged just as many successes, if not more. From accurately predicting business outcomes to enabling organizations to make smarter decisions, analytics would be abandoned entirely if it was not providing businesses with more opportunities to grow and improve.

The National Hockey League is one such business that has successfully leveraged analytics by helping fans get closer to the game and the sport that they love. As the Associated Press reports, the NHL recently inked a deal with Amazon Web Services, which will enable hockey enthusiasts to more seamlessly access content that the NHL releases. This includes classic games from previous years, never-before-seen footage, and the ability to watch games from alternative camera angles.

Matt Garman, vice president of sales and marketing at Amazon Web Services, notes that coaches, players, and team staff will also be able to take advantage of these new features by allowing them to see the ice from a different perspective.

“There’s potentially a lot of ability for coaching staffs to actually help their teams get better by just learning where players may be efficient, where there are some opportunities to coordinate better,” Garman explained, as quoted by the AP.

The NHL is following in the footsteps of other professional sports leagues that have successfully leveraged analytics for their fanbases, personnel, and teams; these include Formula One motor racing, the National Football League, and Six Nations rugby, the AP reported.

Business analytics is all about helping businesses become better today than they were yesterday. Technology is making this possible. You too can become a better version of yourself through the online Master of Science in Management Information Systems program at UAB.  Whether you have a bachelor’s degree in IT already or are aiming to enter an entirely different industry, the curriculum will provide you with the foundation of skills that count and pay off — in more ways than one. For more information on the course descriptions and what transfer credits are accepted, please visit the program page and download the free brochure.


Recommended Reading

What Are the Different Types of Analytics for the Web and Their Uses?

Bachelor’s in Information Systems: Learning Outcomes and Career Paths

Comparing Business Intelligence vs. Data Science and Analytics

Mordor Intelligence – Business Intelligence Market



The Associated Press – NHL Takes Big Stride on Data and Analytics with AWS Deal

Tech Jury – How Much Data Is Created Every Day?

Gallup – Americans Use Social Media for COVID-19 Info, Connection

BLS – Management Analyst


U.S. News & World Report – What Is Business Analytics?

Logi Analytics – What Is Predictive Analytics?