A bachelor’s degree in data science or a bachelor’s degree in data analytics allows individuals to enhance their skills by exposing them to challenges faced in different industries when working with an extensive amount and variety of datasets. Because of this, a data science degree is multidisciplinary. The data science department often collaborates with other departments to provide you with hands-on experience working with data in different domains and foundational classes in data science and data analytics.
Data expertise is in high demand because decision-makers rely on data and evidence to make informed decisions. Examples that support this knowledge include the growth of precision and personalized healthcare that needs support from evidence-based medicines. Impact assessment is another example that heavily relies on data in decision sciences and nearly all kinds of industries.
As technological innovation advances, it has become increasingly possible to store large amounts of data. Such vast data has provided advantages by increasing the sample size to remove bias.
In the past, any individual with a degree in distinct disciplines such as computer science, operations research, or statistics had the skill set needed to analyze the required data.
However, data science and data analytics programs are becoming increasingly more sophisticated. The “five V’s of data”—velocity, volume, value, variety, and integrity in recent times pose unique challenges. This has led to the rise of multidisciplinary undergraduate and master’s degrees in data science and analytics programs and opportunities.
Some universities offer a data science undergraduate degree as a standalone program, while others offer it as a majors/minors program. Students enrolled in this program often complete their degrees in four to five years, depending on their enrollment status.
The format of the course also differs from university to university. Some universities offer this program in person; others provide it entirely online. A few others choose a hybrid model conducting in-person classes and online lectures, allowing flexibility to pace the course. Most universities that enroll students for a bachelor’s in data science will need you to have proof of completing a high school education or a GED. Some universities will also consider your SAT/ACT score and an additional TOEFL exam for international students.
Tuition for a bachelor’s degree will vary whether you consider a degree from a community college or a university. Some degrees may be cheaper than others depending on whether you are an in-state student, out-of-state student, or an online degree.
Data Analytics Bachelor’s Degree Curriculum
There are many different ways to earn credentials in data analytics. The most popular options include data analytics bootcamps, data analytics certifications, and data analytics degree programs.
Universities have started offering data science and analytics degrees in four-year undergraduate programs. Due to the nascency of these programs and variability in the field, there is a considerable variation in the curriculum. Some programs are oriented toward the business applications of analytics, while others dive deep into the technical aspects of data science.
Since each program is different, students are encouraged to contact the school offering these programs to understand better the course and the fit based on their interests. Courseworks include many projects to get hands-on experience to make students comfortable working with real-world data. Even though programs vary, foundational courses remain the same and include concepts related to:
Data Mining and Exploration
Data mining generally refers to gathering relevant data from multiple structured and unstructured sources. Data exploration refers to extracting descriptive statistics from the mined data.
Data Visualization
Data visualization involves studying techniques to represent the outcomes from raw data in readable and visual formats easily understood by the stakeholders.
Statistical Analysis
Statistical analysis includes learning statistical methods to draw inferences from the given dataset. These range from essential topics like linear regression, classification, principal component analysis to more specialized topics such as neural networks, time series models, survival analysis, Markov chains, Bayesian statistics, graph models, and spatial processes.
Data Engineering
This coursework exposes students to technologies used in building infrastructures to handle large datasets that data scientists and analysts can easily consume.
Machine Learning
While statistical analysis teaches how to draw inferences from a population, machine learning is about understanding generalized predictive patterns in the dataset.
Ethics and Privacy
Coursework in ethics and privacy help students realize the principles behind using technology with data to maintain individual privacy. This is especially true when working with involving identity data, patient data, or personal finance data.
Data Science Bachelor Degree Online
The majority of universities have started offering undergraduate programs in data science on-campus. For individuals looking to pursue a degree in data science but have constraints related to location and other responsibilities, there are online programs to offer flexibility and continue with the degree. There have been preconceived notions about getting an online degree.
However, with upgrades to technology and the rise of MOOC (think Coursera, edX), many highly accredited universities have started offering online degrees. With the COVID-19 outbreak in 2020, there has been a rise in the degrees that have been offered online by these institutions. As long as you have researched the institution offering the degree on a few basic criteria, there aren’t any major differences between an online and a traditional degree that will affect your job search. There are some selectivity criteria that one should keep in mind some selectivity criteria when pursuing an online degree.
Getting an online degree from a major institution that has been publicly known, such as Arizona State University and many more, will not have negative consequences on your job search as these universities are well known to employers.
Given that a degree in data science is a marketable major and if you intend to get an online degree from a for-profit institution, you will still have to invest more time in researching this institution. Look up the accreditation process, admission selectivity criteria, program cost, alumni career tracks, and recent employer tie-ups.
Employers have been known to focus on a program’s selectivity criteria to ensure quality candidates from the institution during the interview process. Earning a degree from a for-profit institution can also be expensive compared to other institutions.
It would be best if you considered factors when deciding whether to go for an online degree or a traditional one. It requires some careful planning to make the right choice.
Learning Approach
Some people work better in an unstructured or less structured environment, while others may not be able to adjust to it. It does require some amount of self-discipline to keep yourself on track with online classes and assignments. For people who have a day job or a family responsibility, an online degree may better suit their needs due to online degree programs’ flexible/self-paced nature.
Cost
The costs of online and traditional degrees may vary significantly. One should carefully plan their finances that cover the entire planned term of your education. One approach is to consider if you are eligible for federal loans like FAFSA if you enroll in a given program. The tuition for an online degree may still differ for in-state students compared to out-of-state students.
Institution
Opting for a degree from a well-recognized institution would be helpful for future job searches. Information about the program’s quality is readily available due to the institution’s recognition. Students are advised to reach the universities to learn more details or ask current students and alumni about the curriculum structure, class quality, and career outcomes.
Job Placement
Any institution that does not have job placement opportunities should be considered cautiously. It is always good to talk to current students and reach out to the institution’s alumni before enrolling in a program.
Curriculum Structure
Not all data science programs are the same. Some programs may be focused on specialized areas such as health care, while others on business analytics. Some programs may include many capstone projects, while others may have more online classes and require you to collaborate with other enrolled students for group assignments. Some programs take into account your life experiences in constructing your curriculum. This shortens the time to get a degree and reduces the cost. It would be great to think about what kind of portfolio you would like to create for your future employment.
Career Paths
The jobs mentioned here cover the major career areas that individuals with data science and analytics pursue. The salaries provided here are a national average, and the numbers will differ based on company sector, location, and work experience.
Data Scientist
According to Linkedin, the base salary for a Data Scientist is $105,000 per year, with top-paying locations being San Francisco Bay Area, Greater Seattle Area, New York City Metropolitan Area, Portland Metropolitan Area, and Houston. The Bureau of Labor Statistics has provided a more detailed report on employment and wage statistics for data scientists.
Data Analyst
LinkedIn says the average base salary is $64,500 per year. Top-paying locations are San Francisco Bay Area, Greater Seattle Area, Washington DC Baltimore Area, New York City Metropolitan Area, and Denver Metropolitan Area.
Data Architect
The average base salary is $125,000 per year. Top-paying locations are San Francisco Bay Area, Washington DC Baltimore Area, New York City Metropolitan Area, Greater Boston, and Greater Seattle Area.
Business Intelligence Analyst
The average salary for a business intelligence analyst in the United States is $75,000 per year. This salary is based on 1,131 salaries submitted by LinkedIn members who have “Business Intelligence Analyst” in the United States. The top-paying locations for this career are located in the San Francisco Bay Area, Greater Seattle Area, Greater Houston, Denver, and Los Angeles.
Data Visualization Developer
The average salary for the role of Developer in the United States is $78,000 per year. This salary is based on 284 salaries submitted by LinkedIn members who have “Developer” in the United States. The top-paying locations include Greater Seattle Area, San Francisco Bay Area, Washington DC Baltimore Area, Los Angeles Metropolitan Area, and Greater Boston.
Data Solutions Architect
The average salary for the role of Solutions Architect in the United States is $130,000 per year. This salary is based on 2,685 salaries submitted by LinkedIn members who have “Solutions Architect” in the United States. The top-paying locations for this title include San Francisco Bay Area, Washington DC Baltimore Area, Los Angeles Metropolitan Area, New York City Metropolitan Area, and Greater Phoenix Area.
Data Engineer
The base salary for a Data Engineer is $96,000 per year in the United States based on 2439 responses on LinkedIn. The top-paying locations for a data engineer are San Francisco Bay Area, Greater Seattle Area, New York Metropolitan Area, Portland Oregon Metropolitan Area, Los Angeles Metropolitan Area.
Machine Learning Engineer
The average salary for a Machine Learning Engineer in the United States is $130,000 per year. This salary is based on 997 salaries submitted by LinkedIn members who have “Machine Learning Engineer” in the United States. The top-paying locations for this title include San Francisco Bay Area, Greater Seattle Area, New York City Metropolitan Area, Los Angeles Metropolitan Area, and Greater Boston Area.
Data Science and Data Analytics Degree Outlook
There are many ways to enter a career in data science. However, a bachelor’s in data science or analytics provides a jumpstart to your career in this field, making you equipped with all the necessary skills.
After graduation, data science students can find work in various sectors, including healthcare, education, government, technical services, and research and development. Students take different career paths and gain upward mobility with further experience. According to the Bureau of Labor Statistics, the employment of data professionals is projected to grow 22 percent from 2020 to 2030, much faster than the average for all occupations. With the given statistics, it looks like data-related jobs are here to stay, making a bachelor’s in data science a good decision to pursue if you have a knack for solving data challenges.