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What is Business Analytics?

With the era of big data well-underway, businesses continue to harness the vast troves of data produced every day by human activity to improve decision-making and drive growth. According to NewVantage Partners, nearly 100% of 70 Fortune 1000 and industry leading companies surveyed in 2020 reported investing in big data and artificial intelligence and machine learning operations. More than 60% of these reported investing more than $50MM, up from around 40% just two years prior.

Of course, merely collecting data isn’t sufficient: the data must undergo expert analysis. No surprise, then, that in recent years the field of business analytics has been booming. A multidisciplinary field combining statistical analysis, machine learning, data management, and business acumen, business analytics comprises the tools, techniques, and knowledge needed to extract the kinds of insights that can provide value for a business. Business analytics can be deployed to help lower costs, increase revenues, streamline operations, enter a new market, or support any number of other key business initiatives.

In this article, we’ll dive deeper into how the core types of business analytics drive business decision-making, how business analytics differs from adjacent fields like business intelligence and data analytics, and, for someone interested in breaking into the field, the key skills, career opportunities, and educational pathways out there.

How can the core types of business analytics drive business decision-making?

According to Harvard Business School, there are four primary types of business analytics: descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.

Descriptive analytics: what happened?

Descriptive analytics entails analyzing data to understand what has happened in the past. The most fundamental type of business analytics, descriptive analytics often only requires software like Excel or a database-querying language like Structured Query Language (SQL) to wrangle larger data sets and identify important trends.

How’s it being used: Every business uses descriptive analytics at some point in time — it would be impossible to measure growth otherwise. While the analytics behind Goldman Sachs’ decision to lay off over 3000 employees at the beginning of 2023 were no doubt complicated, much of the impetus arose from an insight arrived at by descriptive analytics: a recent downturn in investment banking compared to previous performance. 

Diagnostic analytics: why did something happen?

Diagnostic analytics entails analyzing data to understand why something occurred: its root cause. For this reason, diagnostic analytics is sometimes called root cause analysis. Diagnostic analytics generally requires a business analyst to dive deeper into a data set — or even reference external data sets — to develop and test hypotheses about what is driving a certain pattern or trend. Often, techniques like regression will be used to determine whether a relationship exists between two variables, which can point to a potential causal relationship.

How it’s being used: Diagnostic analytics is employed whenever a company wants to ascertain or demonstrate causation of a phenomenon. One area this can be particularly useful is in understanding the motivations behind customer behavior. When Spotify seeks to characterize listening history within larger listening habits to make their product more attractive to advertisers, they are employing diagnostic analytics to do so.

Predictive analytics: what will happen in the future?

Predictive analytics entails analyzing historical data in order to predict future events, either through more rudimentary methods like regression or advanced statistical modeling and machine learning . Looking into the future can be particularly useful for businesses wanting to make decisions about entering new markets, initiate a merger or acquisition, manage their supply-chain or production schedule, or forecast earnings for investors.

How it’s being used: Predictive analytics are a crucial way for businesses to mitigate risk when embarking on new initiatives, like entering a new market or launching a new product. Skullcandy, a headphones manufacturer, utilizes predictive analytics to estimate return rates of new headphone units, which gives them insight into potential future costs.

Prescriptive analytics: what actions should be taken?

Prescriptive analytics entail analyzing data to determine the best future course of action. As with predictive analytics, in many cases machine learning algorithms are employed to analyze big data sets and output — or even automate — optimal actions.

How it’s being used: Prescriptive analytics are used in industries as varied as manufacturing, finance, retail, and media. Venture capital firm Hone Capital has recently gained notoriety for using a prescriptive machine learning model that outputs an investment recommendation for each deal the firm is considering, with positive results so far.

How does business analytics differ from business intelligence?

When researching business analytics, there’s a good chance you’ll run into the term business intelligence. At their core, both utilize analytics to produce information that can support businesses, but beyond that there can be disagreement as to how exactly they differ. Some draw a distinction between the work products of each. Business analytics produces insights that more directly support decision-making, they argue, while business intelligence focuses on producing informational resources like reports and dashboards.

Others consider business intelligence to be focused on past events — the domain of descriptive and diagnostic analytics — with business analytics instead focused on the future through predictive and prescriptive analytics. Finally, others find no difference between the two, considering them simply synonyms referring to the analysis of data to produce business insight. Ultimately, you’ll have to use context and content to determine how each term is being used in a particular situation.

How does business analytics differ from data analytics?

Business analytics is also frequently confused with data analytics, and for good reason: in many cases it’s difficult to distinguish between the work a business analyst or a business intelligence analyst does and the work a data analyst does, especially at a smaller company where employees have greater range of responsibility.

At larger companies, the distinction between business analytics and data analytics is usually one of emphasis rather than essence. At their core, both are concerned with employing data analytics to support a business, but business analytics will more often emphasize bigger-picture business concerns while data analytics will emphasize more siloed or operational concerns.

What skills are necessary for business analytics?

To extract actionable business insights from big data sets, business analytics professionals must be proficient in computer science, statistical analysis, data management, data visualization, and business fundamentals, in addition to assorted soft skills.

Computer science

Business analytics professionals must at least be able to run Excel formulas and script in SQL. For more advanced analytics, however, they will need to be able to write machine learning algorithms and train machine learning models using a programming language like Python or R. They’ll also need to be versed in machine learning and deep learning libraries like Pandas or Tensorflow.

Statistical analysis

Statistical techniques essential for business analytics include regression analysis, factor analysis, optimization, cohort analysis, cluster analysis, and time-series analysis. You can find descriptions of each of these with examples in our data analytics explainer.

Data management

Business analytics professionals must be competent across the entire data pipeline, from data mining, to data wrangling and data cleansing, to data processing, to data storage.

Data visualization

Data visualization skills are crucial for business analytics professionals to be able to compellingly communicate insights to stakeholders. Tableau is a popular business analytics tool for creating graphs and other visualizations.

Business fundamentals

To be able to develop and implement useful analytics projects and communicate findings, business analysts must be conversant in business basics, including macro- and microeconomics, accounting, finance, M&A, and industry-specific fundamentals.

Soft skills

Crucial soft skills for a business analytics professional include critical thinking, communication, leadership, and data storytelling.

What career opportunities are out there for someone with business analytics skills?

While the most common role for someone interested in business analytics who has the requisite computer science, statistical analysis, data management, data visualization, business fundamental, and soft skills is business analyst, there are a variety of other common positions, including: data analyst, business intelligence analyst, and data scientist. Here’s how they differ and the average salary you can expect for each.

Business analyst

A business analyst typically collects, prepares, and analyzes data to extract business insights to inform future business actions, and then presents these findings to relevant stakeholders. According to data from, the average business analyst salary in the US is $79,770. 

For more on this career path, see our article on what it takes to become a business analyst.

Data analyst

A data analyst typically gathers and prepares data for analysis and analyzes it to yield insights related to operations, specific products, or other initiatives. As with a business analyst, a data analyst will need skills in data visualization and data storytelling in order to communicate their findings with various business stakeholders. According to data from, the average data analyst salary in the US is $81,719.

For more on this career path, see our article on what it takes to become a data analyst.

Business intelligence analyst

While understandings of the responsibilities of a business intelligence analyst can vary, generally they are responsible for designing and developing informational tools such as reports and dashboards on markets, industries, or business performance. According to data from, the average business intelligence analyst salary in the US is $85,278.

Data scientist

Utilizing advanced skills in machine learning and data engineering, a data scientist is responsible for designing, developing, and executing new approaches to extracting insights from big data sets. According to data from, the average data scientist salary in the US is $139,631.

For more on the data science career path, check out our deep dive and our guides to data science master’s programs and bootcamps.

How can you get started?

If learning more about business analytics — the core types and their applications, the basic skill set, and the typical career paths — has gotten you interested in pursuing a business analytics career of your own, the first step is to find an educational program that will work for your background and help you meet your goals. While historically in-person degree programs were the primary way to gain enough experience and expertise with analytics to land an entry-level job, there have never been more inexpensive, flexible options to gain a business analytics skill set if a traditional degree isn’t for you. Here are your options:

Business Analytics Bachelor’s Degree Programs

What are they?

In the US, bachelor’s degrees are typically four-year undergraduate degrees during which students declare a major that determines their academic focus. Students ultimately interested in business analytics typically major in computer science, applied mathematics, finance, business, or economics.

Who are they for?

Bachelor’s degrees are usually designed to be pursued right after high school, though students with nontraditional backgrounds are almost always welcome to apply. US bachelor’s degrees are also open to international students provided they can demonstrate English proficiency through a TOEFL or similar exam.

How much do they cost?

According to data from, an average bachelor’s degree at a public university costs $102,828 over four years, while a private university averages $218,004 to attend for four years.

Learn more about business analytics bachelor’s programs.

Business Analytics Master’s Degree Programs

What are they?

A business analytics master’s degree is a one- to two-year graduate degree that provides advanced training in business analytics skills and concepts, often while giving students more freedom to pursue individual interests and projects than they would have as undergraduates. Increasingly, business analytics master’s degrees are available online, following a broader trend in higher education.

Who are they for?

Data analytics master’s degree programs are for bachelor’s degree holders — in STEM, in the social sciences, or even in the humanities — who are looking to either advance their existing analytics careers or transition into analytics careers.

How much do they cost? pegs the cost of the typical master’s of science degree in the US at $61,200, though master’s degrees from public universities are significantly more affordable, averaging $29,150.

Learn more about business analytics master’s programs.

Business Analytics Bootcamps

What are they?

Bootcamps are months-long, intensive courses of study focused on helping learners land an entry-level data analytics job, with most including extensive career services. While some business analytics bootcamps exist, there are also many data analytics bootcamps that will provide the education necessary to land a business analyst job.

Who’re they for?

Bootcamps are for those who want to transition into business analytics quickly without paying for an expensive degree program. While some bootcamps will stipulate that students enter with existing experience in programming or statistical analysis, many allow complete beginners to enroll.

How much do they cost?

The average bootcamp cost $11,727 in 2020.

Learn more about business analytics bootcamps.

Business Analytics Certificate Programs

What are they?

Certificate programs can offer online training in one or several business analytics skills like SQL, data visualization, or statistical analysis. After completing the program, students are able to display their certificate on their resumes and LinkedIn. 

Who’re they for?

Certificate programs are great options for cost-conscious aspiring analytics professionals who want more flexibility in curriculum and modality than is possible in bootcamps, bachelor’s, or master’s programs.

How much do they cost?

Business analytics certificate programs range in cost from free to several thousands of dollars, depending on the educational provider’s reputation, the modality, and the extent of the curriculum.

Learn more about business analytics certificate programs.