How to Get a Data Analyst Degree

Most roles that deal with data and information are in high demand, but fewer are as sought-after as data analyst. One big reason for that is that the job title of data analyst is quite broad, and these professionals can be found in virtually every industry.

Organizations large and small, both for profit and not, all require the assistance of data analysts to help inform smart decision-making. Getting a data analyst job means continuing your education after high school and usually means getting a graduate-level degree.

Let’s explore the path you’ll need to take to get a data analyst degree that can propel you to a next-level career.

What Do Data Analysts Do?

While their specific day-to-day job duties will vary depending on the organization and the industry in which they work, in a broad sense, data analysts gather, process and analyze large-scale sets of data.

According to a report by the World Economic Forum (WEF), data analysts are becoming increasingly mission-critical for employers across all industries, as organizations of every stripe will need to hire qualified professionals who can tackle the accumulating data we’re all generating and consuming every day.

Not only are data analyst jobs in high demand today, but for those with a desire to ensure their careers won’t vanish as the global economy continues to modernize, a degree that provides a solid foundation in data science and analysis should be a wise investment. In fact, the WEF report further indicated that about one-third of the core skills of the average worker need to change as technology continues to disrupt economies all over the world.

But that also means that the everyday tasks of the average data analyst are likely to change at a rapid clip. Today, most data analysts use a combination of hard skills like database programming and soft skills like communication to achieve the goals to which they are assigned. Here’s a look at some common tasks data analysts have to deal with on a daily basis:

  • Generating reports
  • Collaborating with coworkers and supervisors
  • Analyzing data to spot trends
  • Collecting and cleaning data
  • Establishing and maintaining data infrastructure
  • Writing and executing database queries
  • Conceptualizing and creating data visualizations
  • Using data to recommend organizational decisions

Skills & Qualifications

A successful data analyst will possess a combination of mathematical prowess, technological skill and problem-solving abilities. While these jobs do tend to have significant programming and other technical requirements, unlike a job like data scientist, a key function for data analysts is being able to effectively communicate their findings to others. In short, they can’t just be about the numbers.

Here’s a look at some of the hard and soft skills needed to excel in a data analyst role:

  • Programming and database languages: Data analysts will need to be familiar with at least one programming language, and usually more, as being able to harness data successfully means drawing from whatever source is available. The most common languages you’ll encounter are R, SQL and Python.
  • Microsoft Excel: For data analysts, Excel will need to become a second language, and they should be able to perform advanced techniques to clean, sort and model data.
  • Data visualization: Getting your arms around data often means translating it from a number to an image, and that means understanding the science behind data visualization and the technical requirements to create effective visualizations of your data. This is also a helpful tool in successfully communicating your findings and recommendations to others within the organization. While you may use tools like Excel or SQL to gather your data, you’ll need to master one or more programs to create visualizations, such as Tableau or Adobe Illustrator.
  • Analytical thinking: Given the job title, it shouldn’t be a surprise that a data analyst needs to be an analytical thinker. This goes beyond being able to understand the technical aspects of querying a database because you also need to know what questions to ask and why a given set of data will help answer those questions.
  • Interpersonal communication: Using your vast technical and analytical skill to find a piece of data that solves a business problem is only the first step in your task. That’s because you also need to be able to effectively communicate what you’ve learned and, if applicable, what steps you recommend be taken by the organization. Communicating clearly and effectively will help ensure your message is received.

Choosing a Degree Path

Not all data analyst degrees are created equal, and figuring out which one is right for you means understanding yourself and your goals before jumping in. Degrees for data analysts exist at every level and with just about any specialization you can imagine, which means that narrowing down why you want a particular degree is important to your educational success.

Ideal Job Title

Data Analyst is just one of a vast array of possible job titles that would fit under this umbrella. Having a sense of your ultimate career goals is important, especially when going about getting a degree because some job titles may require specialized training in one or more areas.

SEE ALSO: Data Analyst Degree Salary

Some differences are obvious: A healthcare data analyst’s job likely would require knowledge in areas like consumer healthcare or public health policy, while an individual who hopes for a career in business data analytics should consider programs that include business, finance or management training.

Because the possibilities are endless, it is impossible to provide a complete list of potential job titles, not including the obvious one (Data Analyst), that a person could pursue after a data analyst degree, but here’s an idea of the diversity inherent in this job role:

  • Economist
  • Forensic Accountant
  • Business Data Analyst
  • Supply Chain Manager
  • Risk Analyst
  • Management Consultant
  • Compensation and Benefits Analyst
  • Health Policy Analyst
  • Market Researcher
  • Operations Research Analyst
  • Budget Analyst
  • Machine Learning Analyst

It isn’t always necessary to decide on a job title before you begin a degree path, though. If you don’t have a strong sense of a specific industry you might want to work in, pursuing a generalist data analyst degree could help you figure that out. Or you might realize a few years into a particular type of data analyst job that a different industry is really the right one for you, and at that point, you can pursue jobs in that field or perhaps consider a further degree or certificate program to build any necessary skills you might lack.

Educational Level & Types of Degrees

Some entry-level jobs for data analysts require only a bachelor’s degree, but a master’s degree will be helpful for highly specialized roles. The higher up the educational ladder you go, the more difficult the degree will be to obtain but the more specific the education.

For example, an individual whose eventual career goal is to become a senior-level economist might first get a degree like Bachelor of Science in Statistics. This type of degree would provide them with foundational knowledge of statistics, mathematics and analysis as well as appropriate skills in a variety of basic tools used in statistical analysis.

SEE ALSO: 20+ Online Master’s in Business Analytics Degrees

But that degree alone would not be enough to get a senior-level economist job, so they likely would later need to pursue a graduate degree, such as Master of Science in Economic Analytics, which would provide the necessary education in economic theory as well as further training in the tools necessary to secure a higher-level job.

For many data analysts, a master’s degree ends up being a terminal degree in their educational journey. However, in many cases, further specialized training may be needed, which could consist of a graduate certificate or intensive in a subject or even a doctoral degree. Using our senior economist example, if our theoretical professional would need to conduct academic or laboratory-type research as one of their job functions, they likely would need a Ph.D. in Economics. On the other hand, if their dream job is managing a department or even running their own company, an MBA or Master of Management degree may be required.

The bottom line is that the type of degree (or degrees) you should plan to pursue will depend on both the type of job you want and the specificity of your daily job duties. The more general the job, the lower the required level of education.

Certifications & Licensure

Many data analyst jobs don’t require specific state licensure or professional certifications. But there are some notable exceptions to this, and those exceptions may also inform the degree you pursue and which institutions you consider.

For example, someone pursuing a Forensic Accountant job may need to qualify as a Certified Public Accountant. In every state, CPA certification requires a specific number of hours of professional experience, and in most cases, a bachelor’s degree from a program that’s earned accreditation from the Association to Advance Collegiate Schools of Business (AACSB). If the licensure or certification you need for your career means earning a degree, even an associate degree, be sure you investigate whether a specific accreditation is necessary.

Non-state-mandated certifications also can help boost your value on the job market. Data analytics certifications like Associate Certified Analytics Professional (aCAP), Certified Analytics Professional (CAP) and IBM Data Science Professional Certificate all are issued by private organizations, usually based on successful completion of a course and/or sitting for an exam.

There is no single license or certification that applies across the board to data analyst jobs, so be sure to do your due diligence in investigating what would be expected before you commit to an educational program.


There’s no doubt that the future success of organizations, business, even government agencies lies in their ability to harness data and make decisions based on analysis of that data. That’s why jobs for data analysts won’t be in short supply, but it also is the biggest possible sign that getting a data analyst degree could be a wise investment, regardless of your current career level.

States in America with the Most At Risk Populations for Coronavirus by Age

The coronavirus crisis has turned many Americans into amateur data scientists who are studying health data and statistics on a daily basis.

Are the rates of infections rising? Are they rising but accelerating or decelerating? Are the infections rising because of viral spread or because of more testing? How many people are dying each day? Does the data indicate that the virus is dangerous for only old people or young people as well? In many ways solving this crisis hinges on our mastery of data analytics, a subject we specialize in.

By now, the data is clear that coronavirus is dangerous for people of all ages, but it’s particularly lethal for older individuals.

In this article, the team at was compelled to review just how many Americans are over the age of 65 in various places across the country. While this data analysis doesn’t show us how to solve the problem, it can show us just how large the devastation could be.

Across the country, there are over 51 million Americans that are over the age of 65, comprising 16% of the population. Maine and Florida lead the nation with the highest proportion of their population being over the age of 65. Alaska and Utah are the states with the lowest rates of elderly people. Among the largest hundred cities in America, Scottsdale, AZ and Honolulu, HI have the populations with the highest percentage of older Americans.


It’s important to note that coronavirus is serious for all individuals, not just the elderly. The disease can be debilitating and sometimes deadly, even if you’re healthy.  Even if you’re “asymptomatic” (meaning you have contracted coronavirus and might not know it because you show no symptoms) you could spread it to someone else who could experience very adverse consequences and possible death.

This is to say, it’s important to show the number of people across America that are above 65 years old because they are the most at risk, but that does not absolve younger people from the risks or responsibilities.

The chart below shows that states that have the highest percentage of their population aged 65 and above:

Across the country, Maine and Florida have the highest percentages of their populations that are over the age of 65 and the highest risk group for the virus. Alaska and Utah have the lowest rates of eldery population, with under 12% of their population being under the age of 65 years old.

But just how many older Americans are at risk in each state? While the prior chart looked at the percentage of the population that was over 65, the next chart shows the number of people in each state that are over 65 (in millions).

In California there are approximately 5.7 million people over the age of 65, followed by Florida with 4.4 million and Texas with 3.6 million. In New York, the state with currently the most known coronavirus infections, has the fourth highest population of people over the age of 65. All in all, 18 of the 50 states have more than a million people over the age of 65 that would be extremely high risk for complications due to coronavirus.

Next, let’s look at the cities with the highest percentage of inhabitants over the age of 65:

Scottsdale, AZ, an attractive retirement destination, has the highest percentage of people over the age of 65 by a significant margin. Scottsdale is followed by Honolulu, HI and Hialeah, FL, two warm locations favored by retirees.  Larger cities like Miami and San Francisco also make the top ten cities with a percentage of older Americans.

On the other hand, Irving, TX has the lowest percentage of people under the age of 65, with just 7.4% of the population being in this high risk group. Santa Ana, CA and Austin, TX round out the bottom three cities with the lowest percentage of people under 65 years of age.

Lastly, let’s look at which cities have the most people over the age of 65 living there:

New York City has the most inhabitants over 65+ years old by a huge margin. Almost 1.2 million New Yorkers are over the age of 65, more than twice as many as the second place city, Los Angeles. New York City currently has the highest know number of coronavirus infections in America by a large margin and may soon exceed the total in Wuhan, China.


In discussions about how to solve the coronavirus economics crisis, some people have suggested that high risk elderly people just need to avoid the virus or that only a small number of people are really at risk. While this sentiment is misguided on a number of different levels, it overlooks the sheer quantity of Americans that are at risk simply because of their age. In states like Florida and Maine and cities like Scottsdale, it would mean risking the health and lives of an enormous part of the population.

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Published on April 10th by Melissa Steele. Reviewed by Jennifer Gaskin, Jen Hood. 

Big Data Science & Analytics Scholarships

This field is booming!!

The business and data analytics field is definitely booming; it is estimated by IBM there will 364,000 more data analytics job openings in 2020, for a total of 2.720,000. ( To fill the gap, employers will look beyond data scientists and fill these jobs with various types of data analysts, engineers, and data and privacy security specialists.  IBM also reports demand for data analysts, data scientists, and data engineers will grow 39% in 2020.

Most of these jobs pay high salaries, with an average analytics manager earning $94,677 per year. (

That is why many students are interested in earning their bachelor’s, master’s in business and data analytics. The good news is there are many scholarships and fellowships available to ease the financial burden of attending college.

Our research has uncovered the following outstanding scholarships below. Review each award and click the link to review in more detail.

Amount: $2,000 | Type: Scholarship | Deadline: Feb 1st/Sept 1st

Big Data Science & Analytics Scholarship is offering a bi-annual $2,000 scholarship to students who plan to pursue or are currently working toward a bachelor’s degree in data analytics or master’s degree in data analytics or mba in data analytics related field. Individuals must be enrolled full-time or part-time, in the current year in a relevant U.S.-based campus or online degree program, such as computer information systems, business analytics, data science, data analytics, math/statistics, or computer science. A minimum GPA of 3.0 is required. Ideal for all students!

Amount: $10,000 | Type: Scholarship | Deadline: Varies

Bill Caspere Memorial Diversity Scholarship

This $10,000 scholarship was begun by The Collective LLC in 2015 to encourage undergraduates and postgraduates to consider careers in data science. Applicants must be black, Asian, Hispanic, Native American, multiracial, or LGBTQ. A minimum of 60 college credits completed with a minimum of 3.25 GP is required.

Amount: $4,000 | Type: Scholarship | Deadline: Varies

Daniel Larose Scholarship for Data Mining Excellence

This annual award is worth $4000 per year or $2000 per semester and is offered to post-graduates who excel in a master of science in the data-mining program. Big data students must have finished at least 12 master’s credits.

Amount: $1,500-2,000 | Type: Scholarship | Deadline: Varies

HIMSS Minnesota Graduate Health IT Scholarship

The HIMSS Minnesota Chapter offers this $1500 scholarship for master’s and $2000 for doctoral students who are studying health informatics, including data science and data analytics. You must live in MN, WI, IO, ND, or SD and have at least a 3.0 GPA.

Amount: $3,000 | Type: Scholarship | Deadline: Varies

INFORMS Analytics Society Student Scholarship

The Institute for Operations Research and Management Sciences partners with SAS each year and hosts the Analytics Society Student Scholarship Competiton each spring to provide a $3000 big data scholarship to a college student who presents the most compelling analytical project proposal. You must be 18 or older, submit a resume, and two references.

Amount: $5,000 | Type: Scholarship | Deadline: Varies

Lilly Endowment Scholarship for Data Science

The Lilly Endowment Scholarship offers $1000 per term for $5000 total for outstanding male or female postgraduates who are pursuing a Master of Science in Data Science. Qualified candidates must live in Indiana, have graduated from an accredited college in the last year in the state, have two semesters of calculus, and a 3.0 GPA.

Amount: $5,000 | Type: Scholarship | Deadline: Varies

Milliman Opportunity Scholarship Fund

Overseen by Scholarship America for the Chicago Public Schools system, this fund awards $5000 each year to minority IL residents of Latino, black, American Indian, Native American, or Pacific Islander heritage, including Dreamers without legal documentation. Students need to have been admitted into a four-year, US college for majors including data science, data analytics, economics, statistics, mathematics, and computer science.

Amount: $1,000 | Type: Scholarship | Deadline: Feb/Sept

Remote DBA Experts to Students Scholarship

Since 2015, Remote DBA has offered $1000 through the Experts to Students Scholarship to support high school seniors or current college students who want a data-focused career with training in data science, data analytics, database administration, and related disciplines. You must have a 2.8 GPA, submit an online application, cover letter, and 500-word essay.

Amount: $1,000 | Type: Scholarship | Deadline: Varies

Strong Analytics Data Science Scholarship

Strong Analytics is a big data company in Chicago that offers a $1000 scholarship to post-secondary students studying data science. Each applicant must use publicly available datasets to select research questions, code analysis, and make PDF presentations that visualize data findings. Projects are judged on rigor, creativity, methodology, and reproducibility.

Amount: $5,000 | Type: Scholarship | Deadline: Varies

UNCF/Alliance Data Scholarship and Internship

Alliance Data Systems has partnered with the United Negro College Fund to provide a $5000 scholarship each year to minority undergraduates who are going to historically black colleges and studying computer science, data science, IT management and digital marketing. A 3.0 or higher GPA is required and students must be rising juniors or seniors.

Amount: Varies | Type: Scholarship | Deadline: Varies

Russ Peterson Technology Scholarship

The CUNY School of Professional Studies in Manhattan provides almost $400,000 annually with financial aid, such as the Russ Peterson Technology Scholarship. The scholarship program supports full-time students with career goals in big data who are within 30 credits of finishing their MS in Data Analytics or BS in Information Systems with a 3.0 or higher GPA.

Amount: $2,000| Type: Scholarship | Deadline: Varies

Carlson School of Management Scholarship

The University of Minnesota offers a $20,000 scholarship for students pursuing a Master of Science in Business Analytics. Twenty scholarships will be awarded to students who are admitted to begin the program in June 2020.

Amount: $1,000| Type: Scholarship | Deadline: Varies

Minneanalytics Data Science Scholarship

This nonprofit organization with more than 10,000 members awards this scholarship of $1000 before awarding a grand prize of $5000 at the end of the year. This is a big data scholarship that is suitable for undergraduates and post-graduates at in-state universities who are working on analytics degrees.

Amount: $2,000| Type: Scholarship | Deadline: Varies

Fisher Family Fund Scholarship

A $2000 scholarship offered to students at the University of North Carolina-Charlotte for students pursuing a degree in data science or business analytics.

Amount: $1,000| Type: Fellowship| Deadline: Varies

Jack Larson Data for Good Fellowship

The University of California Berkeley School of Information offers $8500 of scholarships to students in master’s programs in information and data science.

Amount: $1,000| Type: Fellowship| Deadline: Varies

Women in Data Science Scholarship offers a $1000 scholarship to women earning a bachelor’s or master’s degree in data science or data analytics. Must be enrolled full or part-time in a relevant degree program in the US in 2019 and 2020, such as computer information systems, business analytics, statistics or computer science.

Amount: $15,000 | Type: Fellowship | Deadline: Varies

ACM SIGHPC/Intell Computational & Data Science Fellowship

The Association for Computing Machinery’s Special Interest Group on High-Performance Computing has partners with Intell to offer this fellowship for $15,000 to master’s or doctoral students doing research on big data. Eligible candidates are females or members of minority groups who have finished less than half of their computer science degrees at US universities.

Why STEM for Data Analytics?

Data science is on the rise, and it is increasing the demand for STEM (Science, Technology, Engineering, and Mathematics) students. The greater need for STEM students in because of the growing importance of data science and how it can change the world for the better. This fact means more educational institutions want to produce more students skilled in STEM so they can be more effective data analytics professionals tomorrow. (

With the assistance of big data, it is possible to sort through tons of data that is produced in the daily activities of a company. Big data helps to calibrate a company’s strategy, optimizes its new product development, and helps to find the root causes of failure in a company.

Studying big data and data analytics is challenging, but it is the wave of the future. Students are embracing STEM have the ability to be the innovators of industry tomorrow and will probably make a big impact in the big data field.

Below is more information on why big data and data analytics is driving a need for STEM students.

Leaving a Big Impact

As the world is progressing technologically and data analytics is becoming so important, students want to join in on the excitement as data scientists. With data science and analytics, students can help change the world by solving serious problems such as terrorism, help police to reduce crime, fight climate change, and more.

For example, at the frontier of data analytics is the company Palantir, a Silicon Valley firm that provides critical insights into companies’ daily operations by analyzing big data. This company can help in fighting crime and in war zones. Most of their skilled workforce are young people who have a strong STEM background.

STEM students are investing much knowledge and time to solve many of the issues we have in the world right now. There is a study ongoing today that is being done by chemistry and biology students to attempt to beat cancer by using nanogold particles that can detect cancer cells. With a helping hand from data analytics, these STEM students may unlock some new knowledge to fight cancer we never had before.

Showing Interest

For a professional to work in STEM and data analytics, it is first necessary to be interested in both. Students of all ages who are interested in the sciences, engineering, and math are more likely to have a career in data analytics and data science.

With this in mind, many companies are investing in STEM in students from kindergarten to high school to ensure they have the labor they need in the future. According to one recent study, STEM jobs will increase by 14% by 2024, so there are millions of new jobs available for people with skill and interest in STEM and big data. (

For companies with vision, managers need to invest in STEM and data analytics to ensure there is enough labor available to get the job done in the future. Still, some estimates say that millions of data analytics jobs may go unfilled because there are not enough skilled workers to fill them. (

Improve Your Skills

With data analytics and data science, you will improve your technical skills because you will do more because more is always needed as technology changes. That is why many students in high school on their way to college are attending summer programs that can help them improve their STEM skills.

Getting internships from companies also can enhance your STEM skills and gain you work experience. Leading companies such as Amazon, Apple, and Google always need new talent with interest in STEM and data analytics. If you do well in your internship, you may be able to get a full-time position later.

Excellent Pay

STEM students who decide to pursue a career in data analytics can get large salaries from many companies. Data scientists with a few years of experience can earn salaries that can rise above $100,000 per year.

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[How-To-Guide] Getting Started in Business Analytics — Our career expert dives deep into the aspects of business & data analytics and provides a one-of-a-kind analysis of how to start a career in this exploding field.

For example, a data analyst earns an average salary of $67,138 with a maximum of $118,500. A senior data analyst earns an average wage of $99,456 with a maximum of $155,500. A head of data analytics has average earnings of $145,994 and a maximum salary of $235,500. A manager of data analytics makes $109,519 per year on average, with maximum earnings of $134,000. (

This high level of potential compensation has made students want to focus on sharpening their skills in math, science, and technology so they can get those types of jobs.

Top 25 Highest Paying Cities for Data Scientist Jobs

CityAnnual Salary
Palo Alto, CA - Data Scientist Salary$140,507.00
San Francisco, CA - Data Scientist Salary$139,150.00
Dublin, CA - Data Scientist Salary$132,820.00
New York City, NY - Data Scientist Salary$130,011.00
Boston, MA - Data Scientist Salary$128,286.00
Arlington, VA - Data Scientist Salary$126,344.00
Los Angeles, CA - Data Scientist Salary$125,706.00
Washington, DC - Data Scientist Salary$125,305.00
Parsippany, NJ - Data Scientist Salary$124,787.00
Alexandria, VA - Data Scientist Salary$124,216.00
Irvine, CA - Data Scientist Salary$122,934.00
Fairfax, VA - Data Scientist Salary$122,501.00
Minneapolis, MN - Data Scientist Salary$121,677.00
Chicago, IL - Data Scientist Salary$121,624.00
San Diego, CA - Data Scientist Salary$121,425.00
Sacramento, CA - Data Scientist Salary$120,961.00
Denver, CO - Data Scientist Salary$119,703.00
Atlanta, GA - Data Scientist Salary$119,317.00
Dallas, TX - Data Scientist Salary$119,100.00
Portland, OR - Data Scientist Salary$118,537.00
Philadelphia, PA - Data Scientist Salary$118,495.00
Detroit, MI - Data Scientist Salary$117,941.00
Houston, TX - Data Scientist Salary$117,884.00
Milwaukee, WI - Data Scientist Salary$117,633.00
Albany, NY - Data Scientist Salary$116,958.00

Source:, Jan, 2020

STEM and Data Analytics Are Hot

Data analytics are hot. It is a big thing because there is so much data out there now that companies have access to but they do not always know what to do with it. If they have the right data professionals working for them, they can have that data analyzed and use it to make better business decisions,  make better products, and make more money. These advantages are making smaller and smaller companies adopt data analytics, making the profession even more in demand.

Companies such as Uber, Palantir and Airbnb will pay you well if you are skilled in data analytics. Facebook is known to be one of the highest-paying companies for data scientists. They get a lot of information from their users and that information is used to serve them very specific advertisements when they are on the site.

Data Analytics Can Be Combined With Machine Learning

When data analytics is combined with machine learning, it can be very powerful. The two technologies can solve very complex problems, such as how YouTube can effectively serve you content, and how Google has greatly improved its search results in recent years. Data science and machine learning also can help in the fight against terrorism and prevent crime in our neighborhoods. (

Palantir uses big data and machine learning in their daily operations and so do many other tech companies. The two together help to unlock some answers to questions that may not have been possible before. For example, Kaggle, a website that studies data science and machine learning, assists engineers land jobs at the companies they prefer. All of this has made students with skills in STEM more likely to land hot jobs in data analytics.

Bottom Line

The bottom line is that data science and data analytics is creating millions of new jobs and will create more in the coming years. Students who focus on honing their STEM skills will be the first in line to get some of these high-paying and fascinating data analytics jobs. Are you in?

What is Business Analytics?

Data rules our world, and nowhere is this truer than in the realm of business. Without a steady influx of accurate and useful data, it is difficult (if not impossible) for businesses to stay competitive and relevant today. That data flows in from a thousand different sources each and every day, such as:

  • Customer and client orders
  • Survey results and customer feedback
  • Email, social media and marketing reports
  • Profits, losses, budgets and other financial documents
  • Operational efficiency
  • Manufacturing efficiency
  • Employee statistics, such as sales figures or hiring-and-firing numbers

… and so much more. Depending on the type of industry in which you work, and the products and services with which your company is concerned, the sources of data will vary. What doesn’t vary is the fact that your organization can’t succeed without paying attention to all that data.

The truth is, data is only useful if it’s in the right format. That means data must be:

  • Clean, without competing or interfering factors or “background noise”
  • Organized across departments for a full picture
  • In standardized metrics that are useful to all departments
  • Recent and relevant

Those aren’t the only requirements for good data, of course, but they’re a good place to start. Again, though, this isn’t the form in which data arrives. Rather, it pours in raw and unedited in a great deluge. Without the right people to manage it, a business can’t hope to make good use of it. In response, an entire industry has sprung up to help: business data analytics.

But what is this industry, and how does it pertain to your career path? Let’s take a look at some of the most pertinent questions today.

What’s the Difference Between Business Analysis and Business Data Analysis?

As Harvard Business School points out, the two fields are not the same. “Business analysis has less to do with data and instead focuses on analyzing and optimizing the processes and functions that make up a business,” explains the Ivy League institution. “They analyze what a business needs to function optimally and what it needs to improve, and then work to implement solutions. This may include improving processes, changing policies or introducing new technology.”

Business data analytics, on the other hand, “focuses on data, statistical analysis and reporting to help investigate and analyze business performance, provide insights, and drive recommendations to improve performance. They may also work with internal or external clients, but their focus is to improve the product, marketing or customer experience by using insights from data, rather than analyzing processes and functions.”

Essentially, the role combines two of the most lucrative and interesting career paths available today: business and analysis. That said, what exactly does a business data analyst do?

What Does a Business Data Analyst Do?

A business data analyst’s job is to take the massive influx of data that arrives at a given company’s doorstep every day and turn it into meaningful insight. In order to transform that raw data into actionable recommendations that can improve a business’s bottom line, they must:

  1. Collect and mine data from the right sources. Collecting data is easier, because some of it comes in ready to be processed. Other data must be extracted, or mined, from mountains of existing data. For instance, if you need a single metric from social media data (such as conversions to the sale of a particular product), you will need to create methods for hunting through all the rest of the data to find it.
  2. Sort the data. Once your data is extracted from amongst extraneous factors and figures, you need to sort it to do what you want. Maybe you sort by product, by department, by day of the week, or any other category.
  3. Clean the data. Then the task becomes to turn the data you have into readable intelligence. That means cleaning the data to remove competing factors that might create false impressions (for instance, to account for the fact that a product sold really well during a certain week, when in fact that week was Black Friday). You need to remove any confounding factors that might alter the nature of the data, which would in turn alter the answers you need to the questions you’re asking.
  4. Transform the data into the right metrics. If you want to compare sales dollar to dollar, you obviously need all those figures in dollars. If you sell overseas, though, many of your figures will come in listed in pounds, yen, pesos or other forms of currency – all of which need to be recalculated using exchange rates on the day of the sale. This is just one example showing how much data needs to be put into a new metric before it’s usable.
  5. Create and run algorithms to extract meaning. For the most part, humans don’t have the speed or insight to extract intelligence from the vast quantities of data generated by businesses every day. Instead, they need to create programs that can do it for them.
  6. Turn insight into actionable recommendations. Once business data analysts have the insights they need to answer questions they’ve been given, they must prepare reports or presentations to hand that intelligence off to superiors or stakeholders.

It’s a lot of work, and the field is both complex and challenging. However, those who are interested in gleaning insight from numbers will find it fascinating and ever-changing – a rich and complex career for life. They need the right aptitudes, however.

What Skills Does Business Data Analytics Require?

Those who want to succeed in the field of business data analytics need a wide array of skills. These include:

  • Expert management of computer systems, software and programs
  • Understanding of artificial intelligence and machine learning, both of which play an increasingly significant role in data analysis
  • The ability to think outside the box, spotting confounding variables and creating new approaches to solving problems
  • The ability to turn figure-based conclusions into visual and verbal reports
  • Good communication, which will enable business data analysts to transmit the information they find to those who need it
  • People skills, since the job entails working with others to take action based on the meaning created through data analysis
  • A love of lifelong learning, since the technologies used in this field will never stop changing

If that sounds like you, chances are good you will do well in a career as a business data analyst. Of course, you’ll need a degree in order to begin, which you can get through either a bachelor’s or a master’s degree in business analytics program. If you’d like to learn more about your options, get in touch today.