4 answers
Ram
Student
Kathmandu, Central Development Region, Nepal
7
Questions
Asked
716 views
How different would a path be for someone wanting to do data science work by taking a graduate program in Business Analytics instead of the traditional Data Science path?
Hi, I'm a Computer Science graduate. I'm planning for a Master's program and the Business Analytics program looks interesting, but most programs are 10months, comparing that with a MSCS programs? How different of a job role would it be.
Thanks.
#computer-science #business #graduate-school #business-analytics #masters-program
Login to comment
4 answers
Sandi Besen
Consulting
4
Answers
Boston, Massachusetts
Updated
Sandi’s Answer
CS is a great foundation of data, but lacks the application to business that the Business Analytics degree provides. If you are interested in going into a pure Data Science Role, I recommend the MS ins Business Analytics program as it will teach you how to apply the fundamental knowledge you have to real world problems. Data Science entry level roles can be difficult to ascertain with just a Bachelors degree. If you are fluid and not dead set on going into data science directly (and analytics or reporting instead) after graduation, going into industry will be a great benefit in business understanding. If you are passionate about data science only, then you might want to consider grad school, as your chances of specialized job roles increase with your education level!
Dinesh Singh
Technical Manager
62
Answers
Philadelphia, Pennsylvania
Updated
Dinesh’s Answer
Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.
Data scientists examine which questions need answering and where to find the related data. They have business acumen and analytical skills as well as the ability to mine, clean, and present data. Businesses use data scientists to source, manage, and analyze large amounts of unstructured data. Results are then synthesized and communicated to key stakeholders to drive strategic decision-making in the organization.
Skills needed: Programming skills (SAS, R, Python), statistical and mathematical skills, storytelling and data visualization, Hadoop, SQL, machine learning
The first waves of data scientists were primarily from development personnel, computer scientists, and engineers. They were the ones who created machine learning models, that optimized the process and minimized the cost function. They would analyze unstructured data, create specific programs for each problem, and, due to limitations of the computational processing, do manual map / reduces. Fortunately that time is gone, most of these operations have been greatly facilitated by high-performance programs and packages, and currently most Data Scientist is spending more time on modeling and less on engineering.
https://www.forbes.com/sites/quora/2017/01/20/whats-the-best-path-to-becoming-a-data-scientist/76ba234737d2
Data scientists examine which questions need answering and where to find the related data. They have business acumen and analytical skills as well as the ability to mine, clean, and present data. Businesses use data scientists to source, manage, and analyze large amounts of unstructured data. Results are then synthesized and communicated to key stakeholders to drive strategic decision-making in the organization.
Skills needed: Programming skills (SAS, R, Python), statistical and mathematical skills, storytelling and data visualization, Hadoop, SQL, machine learning
The first waves of data scientists were primarily from development personnel, computer scientists, and engineers. They were the ones who created machine learning models, that optimized the process and minimized the cost function. They would analyze unstructured data, create specific programs for each problem, and, due to limitations of the computational processing, do manual map / reduces. Fortunately that time is gone, most of these operations have been greatly facilitated by high-performance programs and packages, and currently most Data Scientist is spending more time on modeling and less on engineering.
Dinesh recommends the following next steps:
Tia Stafford
Consultant
19
Answers
New York, New York
Updated
Tia’s Answer
Analytics is about translating data into actionable advice to management. Your CS degree is going to teach you how data is structured. You need to be able to translate that structure to report building. And once you understand report building and what the report tell you, then you can analyze the results and report more than just numbers- you provide insights, . You don't need a degree to do this. You need practice. I would encourage you to get some job experience before entering a Master's program.
On the practical side: It will be hard to get an entry level business analytics job with a Master's degree as 90% of your peers will not have it. A company will have a hard time justifying your salary with your advanced degree but no work experience. Get two years experience and learn about your data and what trends/insights you can get from the data. There are several online resources that will help increase your skills to understand your data and how to provide insights to leadership.
Who am I to be giving this advice? My previous career was as a Director of Analytics and I will tell you that my Master's is an MBA in International Business. Nothing Analytics related. Everything I did to rise in my career I did on the job.
On the practical side: It will be hard to get an entry level business analytics job with a Master's degree as 90% of your peers will not have it. A company will have a hard time justifying your salary with your advanced degree but no work experience. Get two years experience and learn about your data and what trends/insights you can get from the data. There are several online resources that will help increase your skills to understand your data and how to provide insights to leadership.
Who am I to be giving this advice? My previous career was as a Director of Analytics and I will tell you that my Master's is an MBA in International Business. Nothing Analytics related. Everything I did to rise in my career I did on the job.
I definitely agree with aspects, but it is also very dependent on what the student studied in undergrad and what type of position they are looking for after graduation. If they wish to enter into a pure Data Science role, Graduate degrees are actually quite common! Coming from a pure business background, I would never have been able to secure my role if it weren't for my MS in Business Analytics. There are many moving parts, but my graduate program had a 90% placement ratio!
Sandi Besen
Neha Rathnakar
Business Analytics from Harvard Business School Online, IT Analyst, Software Testing, Professional Scrum Master.
1
Answer
Madison, Wisconsin
Updated
Neha’s Answer
Any degree or education you choose will only give you a knowledge start and you will need to develop and learn the skills in practice , in a job.
MS in Business Analytics is more for ones who want to leverage business and technical skills to create value for clients. Data science is little heavier on the coding and technology.
They are both interrelated and many a times course contents will be more or less similar. It is about what you are interested in learning. I would suggest to compare course contents on both Analytics and data science and then decide. If you want to get into Data science then you should look for a data science course/degree.
People enter either of these fields via different paths and nothing is impossible if you have the right skills and acumen for it.
MS in Business Analytics is more for ones who want to leverage business and technical skills to create value for clients. Data science is little heavier on the coding and technology.
They are both interrelated and many a times course contents will be more or less similar. It is about what you are interested in learning. I would suggest to compare course contents on both Analytics and data science and then decide. If you want to get into Data science then you should look for a data science course/degree.
People enter either of these fields via different paths and nothing is impossible if you have the right skills and acumen for it.