The grad cert, in my opinion, isn't going to do much of anything for you alongside CIS. The cert is operations and risk decision-making coursework, so without academic/resume items in those areas as a foundation, it's random theory stuck on top of CIS. Further, without doing the foundation work for the classes (at least covering the undergrad Optimization class, either within the TESU degree, as a standalone class, or mastering the material independently, and maybe an operations management class, or finance, or whatevs), plus having some ability in data visualization (which is beyond the scope of these grad classes) as a bare minimum, I don't see the path to grad-level functioning in operations or finance...particularly if the BSBA is in neither ops nor finance.
The value of a data scientist is not in understanding a how to use a software package. Anyone can plug-n-pray data at the bottom salary tier, in data entry. The value of a data scientist is their understanding of the area/market under analysis, and the relationships between the many components they're observing. It's akin to a tech taking a page of medical lab results and reading "in range" and "out of range" and announcing what they just read off the paper, versus the doctor/PA/nurse practitioner understanding the biochemistry behind the results, why if one result is wonky, an entirely different-but-related panel needs to be run, how it all works together, and the complex analysis/algorithm that winds up finding a brain tumor from the starting point of a kidney stone. People pay the big bucks for the depth of knowledge underneath the analysis skills...so I'm not sure there's a quickie masters that's going to help move the income needle without foundation work in whatever market interests you.
I'd search your local job boards for "data analyst", "data scientist", "data research"...that sort of thing, and see what's out there for actual jobs right now in your area. That might give you an idea for direction. A lot of companies are jumping on the Big Data bandwagon without really understanding what it is, what it can do for them, and how they're going to implement "it". So scour the ads and see what skills they *think* they want, and who is offering what opportunities. Without a portfolio/references in the field, I don't see how you get remote work in this field...which means taking a close look at the on-site jobs on offer, as an initial guide. Also, hit Glassdoor to see what companies in your area are actually paying for each of these job titles. That may give you some direction if you desire not-entry-level wages.
AND.
You keep using the term "interesting", that your job must be "interesting", and listing many things which do not interest you. If I was into gambling, I'd put money on you not liking data much. Why? Because for even the top tier scientist who handles data, the overwhelming majority of time is spent on the very ugly, dry, frustrating, and critical task of data cleaning. (Yes, it's as sucky as it sounds. Fork-through-the-skull sucky for many people.)
Further, it's *all* numbers, in any sector. It's not theoretical math like doing proofs, but it's definitely developing mathematical relationships between variables. Understanding what algorithm was used to develop results, and why a different algorithm is more appropriate for that particular data set. (Software will have many/most of them...it's up to you to learn why and how to use them, vs the basics of running the analysis to get a results file.)
I believe you're capable of working in data, absolutely. But I don't get the sense that you'd enjoy it. Having said that, some logistics:
Payment plan: For the TESU student, covers the 8 required classes and 4 electives (from the list of 8 electives). It's possible to do the 10-course Stats.com Analytics for Data Science certificate (8 required, not identical to TESU but close, plus 2 electives...and still includes the Intro Stats for free, or did at the time of my enrollment)...but you'll want to choose electives carefully. I have some outside credits that fit TESU AOS electives, so option B worked better for me. For most people, it's going to be much easier to just sign up for the TESU plan and go with it.
Textbooks: Included for Intro Stats, but not for anything else. The classes often use texts written by the instructors, which is a mixed blessing. They can be found for $20-30 to $200...it's not a negligible line item on the program budget.
Time: Be prepared to do random hurried background work. (Like Machine Learning last week: "Now's a good time to learn Tableau or Spotfire. Go for it, then show us your images. It's graded." Besides working on the theory behind the visualizations, we had a week to learn and become at least somewhat proficient with a specific data viz package...which bumped study hours required *way* up. And that's the only week we need Tableau (or Spotfire), for this class. And there are no late assignment submissions. So...drinking from the firehose. Social Network Analysis was similar, with Gephi...kind of a "here, go play with this and get competent before your final project in 4 weeks."
Health Informatics is basically "medical records" (how data is organized, stored, secured, shared). Bioinformatics = computational biology. CS, math, statistics, and even engineering. Statistics.com offers 10-course certificates in Biostatistics and in Social Science Statistics. They offer payment plans, and a credential, though many (most?) classes are not ACE accredited so there's not a lot of transfer credit available & a hiring manager may/may not be interested in these without an academic "explanation" (like a biology/biochem/psych degree, for example).
Sorry this is so disjointed - I have a close family member going active on the Boston lung transplant list imminently (the committee has voted, they're getting the allocation score now), so it has been a little nutty here. My best advice to you is to research the h#ll out of the jobs/opportunities and plan accordingly, and be very cautious about how you spend your education $...be sure it gets you where you want.
The value of a data scientist is not in understanding a how to use a software package. Anyone can plug-n-pray data at the bottom salary tier, in data entry. The value of a data scientist is their understanding of the area/market under analysis, and the relationships between the many components they're observing. It's akin to a tech taking a page of medical lab results and reading "in range" and "out of range" and announcing what they just read off the paper, versus the doctor/PA/nurse practitioner understanding the biochemistry behind the results, why if one result is wonky, an entirely different-but-related panel needs to be run, how it all works together, and the complex analysis/algorithm that winds up finding a brain tumor from the starting point of a kidney stone. People pay the big bucks for the depth of knowledge underneath the analysis skills...so I'm not sure there's a quickie masters that's going to help move the income needle without foundation work in whatever market interests you.
I'd search your local job boards for "data analyst", "data scientist", "data research"...that sort of thing, and see what's out there for actual jobs right now in your area. That might give you an idea for direction. A lot of companies are jumping on the Big Data bandwagon without really understanding what it is, what it can do for them, and how they're going to implement "it". So scour the ads and see what skills they *think* they want, and who is offering what opportunities. Without a portfolio/references in the field, I don't see how you get remote work in this field...which means taking a close look at the on-site jobs on offer, as an initial guide. Also, hit Glassdoor to see what companies in your area are actually paying for each of these job titles. That may give you some direction if you desire not-entry-level wages.
AND.
You keep using the term "interesting", that your job must be "interesting", and listing many things which do not interest you. If I was into gambling, I'd put money on you not liking data much. Why? Because for even the top tier scientist who handles data, the overwhelming majority of time is spent on the very ugly, dry, frustrating, and critical task of data cleaning. (Yes, it's as sucky as it sounds. Fork-through-the-skull sucky for many people.)
Further, it's *all* numbers, in any sector. It's not theoretical math like doing proofs, but it's definitely developing mathematical relationships between variables. Understanding what algorithm was used to develop results, and why a different algorithm is more appropriate for that particular data set. (Software will have many/most of them...it's up to you to learn why and how to use them, vs the basics of running the analysis to get a results file.)
I believe you're capable of working in data, absolutely. But I don't get the sense that you'd enjoy it. Having said that, some logistics:
Payment plan: For the TESU student, covers the 8 required classes and 4 electives (from the list of 8 electives). It's possible to do the 10-course Stats.com Analytics for Data Science certificate (8 required, not identical to TESU but close, plus 2 electives...and still includes the Intro Stats for free, or did at the time of my enrollment)...but you'll want to choose electives carefully. I have some outside credits that fit TESU AOS electives, so option B worked better for me. For most people, it's going to be much easier to just sign up for the TESU plan and go with it.
Textbooks: Included for Intro Stats, but not for anything else. The classes often use texts written by the instructors, which is a mixed blessing. They can be found for $20-30 to $200...it's not a negligible line item on the program budget.
Time: Be prepared to do random hurried background work. (Like Machine Learning last week: "Now's a good time to learn Tableau or Spotfire. Go for it, then show us your images. It's graded." Besides working on the theory behind the visualizations, we had a week to learn and become at least somewhat proficient with a specific data viz package...which bumped study hours required *way* up. And that's the only week we need Tableau (or Spotfire), for this class. And there are no late assignment submissions. So...drinking from the firehose. Social Network Analysis was similar, with Gephi...kind of a "here, go play with this and get competent before your final project in 4 weeks."
Health Informatics is basically "medical records" (how data is organized, stored, secured, shared). Bioinformatics = computational biology. CS, math, statistics, and even engineering. Statistics.com offers 10-course certificates in Biostatistics and in Social Science Statistics. They offer payment plans, and a credential, though many (most?) classes are not ACE accredited so there's not a lot of transfer credit available & a hiring manager may/may not be interested in these without an academic "explanation" (like a biology/biochem/psych degree, for example).
Sorry this is so disjointed - I have a close family member going active on the Boston lung transplant list imminently (the committee has voted, they're getting the allocation score now), so it has been a little nutty here. My best advice to you is to research the h#ll out of the jobs/opportunities and plan accordingly, and be very cautious about how you spend your education $...be sure it gets you where you want.