A Ph.D. in big data analytics is preparing many professionals who can work in fields driven by data, including business, research, government, and healthcare. Usually, people are interested in pursuing a Ph.D. in a field related to data because they have a passion for data.
Most people who are pursuing a Ph.D. in the big data field are willing to have a special career that is involving research as well as making discoveries. The Ph.D. programs in data analytics allow the students to get deeper knowledge about research topics and methods.
Then, they can use those topics and methods throughout their future careers of those students. Just like many other doctoral degrees that are oriented in research, the Ph.D. degree in analytics usually is pursued by those interested in academic careers.
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The Applications of Ph.D. in Big Data Analytics
There are two applications of this Ph.D. degree in analytics. The first one is conducting research that is improving techniques and methods of data utilization. Data analytics research that is based on method will focus on getting a much deeper understanding of algorithms that are used in analytics.
Usually, this research method for Ph.D. in big data analytics will involve the details below:
- The research that involves algorithms understanding will lead to tremendous growth, especially in analytical tools. This is going to improve the performance of deep learning, especially on big-scale data.
- The researchers have been investing enough time to understand the methods so that they can collect the data with a lower ratio of signal-to-noise. Researchers also worked with incomplete data and generated synthetic data.
This way, researchers of Ph.D. in big data analytics can understand the natural phenomena where there is no available data or where the data is rare. Other researchers involve some research methods to combine data from various different sources.
For example, they may combine the voice data and self-reported questionnaires of psychiatric so that they can understand the emotions and moods.
- As organizations and people are now aware of the importance of data, there are increasing reports of data fraud and theft. This phenomenon leaves many vulnerable people at a loss. Data privacy and ethics become the most crucial research area in the world of data.
- Data that is growing explosively makes ongoing research grow tremendously. Researchers with Ph.D. in big data analytics can now develop storage systems that will improve the availability of data with consistency, particularly in real-time analysis.
And then there is research that is using techniques that are related to data. The goal of this research is to create or improve applications in a specific field. Another common research area of the Ph.D. in big data analytics involves understanding how the other fields are applying data analytics.
Researchers can learn how other practitioners, researchers, and also scientists in different fields apply various data analytics. The application areas range widely and are not limited to medicine or finance but also to various projects of social good.
Various examples of research in projects of social good solve some specific challenges that are related to the crisis, like responses to human-made and natural disasters in the disease outbreak and in missions of search and rescue.
The other research examples of Ph.D. in big data analytics are including solving environmental challenges, criminal justice, education, and the other challenges using analytics.
The Curriculum of Ph.D. in Big Data Analytics
The academic workload of the Ph.D. program is intensive. Usually, the academic workload can be completed in four to five years. Unfortunately, since the industry of data has only emerged in the last ten years, it is hard to find institutions that are providing a Ph.D. degree in analytics.
Specializations that are related to data analytics are now tied to research programs that are related to business or STEM. Below are some details you may want to know before enrolling in any Ph.D. program in data analytics.
1. Ph.D. in big data analytics components
Before enrolling in the Ph.D. program, especially in big data analytics, you need to learn about the general overview, specifically the requirements you need to complete the Ph.D. program. Below are some requirements to meet.
· Credit requirements
Each Ph.D. program has specific requirements for the candidates to complete the credits in a certain amount. Those credits must be related to advanced or foundational level quantitative and qualitative methods in statistics.
Based on each student’s flexibility and interest in the program, an institution may offer a specific cognate course option. The curriculum of the course will be similar to the program for the master’s level with some additions of classes that are related to research.
· Pre-candidacy research projects
For the first one to two years of the program for a Ph.D. in big data analytics, the students will be prepared for candidacy admission. Students should work on several research projects. Those research projects will also help students to develop their skills.
The skills each student will develop are necessary to frame various questions and also to save the data problems in the real world.
· Qualifying or preliminary examination
Each program of Ph.D. will require the students to pass the qualifying exam. The exam is going to test the student’s skills and make sure that the students meet the candidacy requirements. The pre-candidacy exams will assist students in fulfilling various requirements.
Some requirements students can fulfill with the help of the exams include the requirement of having practical and theoretical knowledge that they need to work on the research project.
· Teaching requirement
Almost all programs for Ph.D. in big data analytics will require all students to teach courses at the undergraduate level or to assist their professor in some teaching classes. The experiences and opportunities will prepare the students for their academic careers.
· Dissertation proposal
About the dissertation proposal, contains the student’s research hypothesis that must meet the publication’s standards, specifically in data analytics. Before students start working on the proposal, the faculty members’ committee should approve the proposal first.
· Dissertation defense that is successful
Hopefully, all students can present their original work during the dissertation proposal. Those students should be experts in their dissertation topic that is related to data and can defend the analysis they have made.
This is a super crucial aspect since this is going to signify that a student has grasped the entire skills he needed successfully and he can now conduct his own independent research after completing their degree.
· Optional requirements
The Ph.D. is not only about completing qualifying examinations and taking credits. During the program, there will be so many opportunities that all students can benefit from. For example, getting internships and attending conferences will help students form social connections and find jobs.
The data field is evolving at a faster rate today. It keeps the students who are pursuing a Ph.D. in big data analytics abreast of the new trends, especially in the industry of data. Conferences will provide all students with discounted prices to attend the conferences.
Online platforms will also help students. Those online platforms will offer opportunities to form teams, and networks, and to participate in various challenges so that students can showcase their skills.
2. The online Ph.D. program in big data analytics
Various opportunities in the online educational program are now available, particularly in higher education. The big data analytics Ph.D. program, for example, also comes in an online program. The online degree program offers flexibility in various terms like geographic location, workflow, and also timing.
Many leading universities are now offering a program that will bring the best of faculty research to many people. So many great master’s programs in data analytics are now available entirely online. But Ph.D. program is still taught in traditional settings since this requires research that is more collaborative.
Many Ph.D. programs in data analytics also require some components like the teaching component. This teaching component cannot be handled in person.
Ph.D. in Big Data Analytics’ Career Paths
For those who complete the Ph.D. program, especially in the big data analytics field, many career pathways are available. Usually, this degree leads to an academic career. But organizations and businesses are increasingly looking for practitioners and researchers of data analytics.
Below are some examples of career paths that will open for those who have a Ph.D. degree.
1. Research fellow or postdoctoral researcher
Postdoctoral associate or postdoctoral fellow is also known as the research staff. The main goal of this position is to extend the experience and education of the candidate. Although the candidate holds a doctoral degree, he isn’t considered an independent researcher.
Also, the candidate will not serve as the principal investigator. In this career, the candidate may be required to teach. The position is often for a fixed term which ranges between six months and three years. The average salary for this career is USD89,514.
2. Professor or assistant professor
Another career available for those who hold a Ph.D. certification is an assistant professor or a professor. This career is usually the first step you need to tenure and to conduct your independent research. When you complete your tenure, you can get a professor title.
The track of tenure is usually a long journey that involves evaluating the publications of associate professors, research, and also teaching. The track of your tenure will last between five and seven years. The average salary for this job is about USD 61,119.
3. Data scientist
If you choose this career path after completing your Ph.D. in big data analytics, you will be wrangling with data. Your goal is to develop insights that are meaningful. Data scientists should also help organizations spot and solve any problem that is related to services and products.
A data scientist needs to combine statistics, computer science, and also business knowledge to assist organizations in creating objective decisions by using strategies that are driven by data. USD119,413 is the average salary for a data scientist in the USA.
4. Quantitative research or research scientist
Unlike data engineers or data scientists, research scientists are not working to develop products. Instead, research scientists will design and conduct various experiments by measuring the experiments’ outcomes and developing hypotheses. The career’s average salary is about USD162,604.
5. Chief analytics officer
As a chief analytics officer, you must be able to lead the data analytic strategy of an organization. Moreover, those who reach this position must be able to drive the business changes that are related to data and work with data scientists when developing products that are related to data.
If you are interested in getting this position after completing your Ph.D. program in big data analytics, you may want to know the average salary for this position: USD95,195.
Interested in enrolling in Ph.D. in big data analytics program? Then you need to know the prerequisites for acceptance. Many institutions will require you to prepare for your bachelor’s degree. If you have a degree in a quantitative field, you may be accepted for the Ph.D. program.
Some other institutions require work experience. But usually, work experience is optional and not necessary. To gain admission to the Ph.D. program in the big data analytics field, you need to have a strong interest in research.
