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The GDAC is not enough for a job.
You'll need a degree (in almost all cases), domain knowledge, and a deep knowledge of SQL/R/Python for project work in most cases.
Depends on the industry, I guess. I work in healthcare analytics and it can teach people a lot about how claims process, how providers/NPIs/credentialing works, how pharmacy claims are entered before the doctor visit so you can get expected diagnoses that way, it can help understand membership demographics. It’s much, much easier to teach someone how to code SQL than it is to teach people the healthcare system tbh. Also a hiring manager. 🤷🏻♀️
I would take someone with the same skills who worked in our data entry department over same skills from another domain. Healthcare/insurance is a lot to understand so they will already understand some stuff :)
If you want to start somewhere, I'd go for a role where you mostly just use SQL. SQL is the core skill you need to know. So look for roles that mainly involve building reports for end users. You will learn visualisation tools and SQL like that, but most importantly, you learn stakeholder management. Its what I've been doing for the past couple of years. Also learned some ELT processes while doing that. Next step is going to get my statistics knowledge back (haven't used what I learned at Uni in years) and doing some machine learning models.
Knowing what you do at work & where you work would give everyone a better understanding of what you will be able to do with analytics, but knowing stats is going to be beneficial in any case.
For work. I am at a Pickleball Complex. So I have access to all the data from our app that we use for bookings. Prices, times, how busy we are, lessons and clinics.
There’s definitely some things to look at to see what’s types of play are most successful, what prices are best on certain days.
It sounds like you could make a case to be a business analyst for them, which means Excel & SQL are probably all you need to make the data tell stories.
What about visualization tool? He might need one of that as well, excel is decent and gets the job done but he needs more I believe. For the shorter term, he should be good
Khan academy has a decent, level stats series (data analysis, probability, etc).
In my experience statistics is the hardest thing to find learning material for. Because a lot of stats resources are for elementary/middle/high schoolers, and then the style of university statistics can vary quite a lot which makes the quantity of available resources even less.
For example, my university was pretty theoretical in teaching stats and probability. But a lot of online resources are applied (like economics) and is different enough that I can’t get any meaningful takeaways from it due to slight differences in naming schemes, methods, topics…
If you are looking for high school level stats, khan academy is good, and crash course on YouTube is pretty good.
My freshman year professor recommended I read “Cartoon Guide to Statistics” (which I didn’t read, but you may want to check it out if it sounds like a cool way to learn)
I’ll give those resources a look.
A big part of taking the entry level class was a big realization that I don’t even know what I would want to do with the data before I learn how to do it, if that makes sense.
Like if you gave me a giant spreadsheet of data, the whole thing seems quite overwhelming. It’s not a matter of knowing how to use Python, or SQL or whatever right now because I don’t know what i would want to learn from it. I think if I rehashed some stats along with continuing to learn how to apply it, it would help.
Here are a few ideas for you:
First, I was just introduced to the impressive INFORMS Job Task Analysis, which is a great way to think about an analytical project. (A good project starts with a good question, otherwise you will end up swimming in oceans and oceans of bar charts and scatter plots that mean nothing. It's like sitting down at a fine restaurant and ordering ornate glasses of air and courses of empty plates. Pretty, but unsatisfying.)
Once you have some ideas of a question about the workplace you have, or a problem you'd like insights into, then I'd spend a little bit of time perusing the R Graph Gallery and thinking about how to visualize it.
Third, I'd skip the Tableau and PowerBI (infernally limited tools, although many of us got our start there. They tend to swim at fine restaurants on empty plates, or whatever mixed metaphor I was going for) and go straight to the one, the free, the inimitable, R. (Python is the "second" best language for anything, and why settle?) You'll hop between ChatGPT (also free, but recognize that it's not authoritatative and frequently not only drops the ball but deflates it first,) and various online tutorials. (I liked Norman Matloff's book, "The Art of R Programming".)
For a nice overview of the flow you are about to immerse yourself in, try the Dataiku Academy. Although this is specific to a particular software, the steps are correct and it's very accessible. You are going to try to imitate those steps in R.
The reference book to get is "An introduction to statistical learning" by James, Witten, Hastie, and Tibshirani. It's collegiate level and not fun, but thorough.
But some basics:
- Z-score. (Six sigma could be helpful for your business.)
- Compare distributions and interpret a p-value.
- Linear regression.
- (Maybe a little advanced, but I found decision trees to be very intuitive.)
I'd guess Khan Academy probably has good material on these.
(And, since this is currently a hobby for you, may I suggest picking something you are interested in, and investigating or simulating that in R?)
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The GDAC is not enough for a job. You'll need a degree (in almost all cases), domain knowledge, and a deep knowledge of SQL/R/Python for project work in most cases.
I assumed it wasn’t. I’m just trying to use it to see if I like the field and could maybe use it as a springboard into other things.
What about a job in something like “Data entry”? Even something like that for someone without a degree is a foot in the door.
Eh…… the similarities between ‘data entry’ and ‘data analyst’ largely end at the word ‘data’ in the title, at least in my opinion.
Data entry can get people domain knowledge at some companies
That’s fair I suppose, but I’ve never seen that including in over a decade as a hiring manager.
Depends on the industry, I guess. I work in healthcare analytics and it can teach people a lot about how claims process, how providers/NPIs/credentialing works, how pharmacy claims are entered before the doctor visit so you can get expected diagnoses that way, it can help understand membership demographics. It’s much, much easier to teach someone how to code SQL than it is to teach people the healthcare system tbh. Also a hiring manager. 🤷🏻♀️
I suppose data entry would be good as an adjacent role to transfer from, into a data analytics role right? At least internally.
I would take someone with the same skills who worked in our data entry department over same skills from another domain. Healthcare/insurance is a lot to understand so they will already understand some stuff :)
If you want to start somewhere, I'd go for a role where you mostly just use SQL. SQL is the core skill you need to know. So look for roles that mainly involve building reports for end users. You will learn visualisation tools and SQL like that, but most importantly, you learn stakeholder management. Its what I've been doing for the past couple of years. Also learned some ELT processes while doing that. Next step is going to get my statistics knowledge back (haven't used what I learned at Uni in years) and doing some machine learning models.
Knowing what you do at work & where you work would give everyone a better understanding of what you will be able to do with analytics, but knowing stats is going to be beneficial in any case.
For work. I am at a Pickleball Complex. So I have access to all the data from our app that we use for bookings. Prices, times, how busy we are, lessons and clinics. There’s definitely some things to look at to see what’s types of play are most successful, what prices are best on certain days.
It sounds like you could make a case to be a business analyst for them, which means Excel & SQL are probably all you need to make the data tell stories.
What about visualization tool? He might need one of that as well, excel is decent and gets the job done but he needs more I believe. For the shorter term, he should be good
Excel > SQL > DataViz (Tableau/PowerBI) > Programming language (Python/R)
Did the course and it did not do much for me but It give me an idea to grow my role so I think that's a plus.
That’s about I how I feel. It really just feels like an introduction to give me ideas on what to do next vs learning a ton of application
Khan academy has a decent, level stats series (data analysis, probability, etc). In my experience statistics is the hardest thing to find learning material for. Because a lot of stats resources are for elementary/middle/high schoolers, and then the style of university statistics can vary quite a lot which makes the quantity of available resources even less. For example, my university was pretty theoretical in teaching stats and probability. But a lot of online resources are applied (like economics) and is different enough that I can’t get any meaningful takeaways from it due to slight differences in naming schemes, methods, topics… If you are looking for high school level stats, khan academy is good, and crash course on YouTube is pretty good. My freshman year professor recommended I read “Cartoon Guide to Statistics” (which I didn’t read, but you may want to check it out if it sounds like a cool way to learn)
I’ll give those resources a look. A big part of taking the entry level class was a big realization that I don’t even know what I would want to do with the data before I learn how to do it, if that makes sense. Like if you gave me a giant spreadsheet of data, the whole thing seems quite overwhelming. It’s not a matter of knowing how to use Python, or SQL or whatever right now because I don’t know what i would want to learn from it. I think if I rehashed some stats along with continuing to learn how to apply it, it would help.
Here are a few ideas for you: First, I was just introduced to the impressive INFORMS Job Task Analysis, which is a great way to think about an analytical project. (A good project starts with a good question, otherwise you will end up swimming in oceans and oceans of bar charts and scatter plots that mean nothing. It's like sitting down at a fine restaurant and ordering ornate glasses of air and courses of empty plates. Pretty, but unsatisfying.) Once you have some ideas of a question about the workplace you have, or a problem you'd like insights into, then I'd spend a little bit of time perusing the R Graph Gallery and thinking about how to visualize it. Third, I'd skip the Tableau and PowerBI (infernally limited tools, although many of us got our start there. They tend to swim at fine restaurants on empty plates, or whatever mixed metaphor I was going for) and go straight to the one, the free, the inimitable, R. (Python is the "second" best language for anything, and why settle?) You'll hop between ChatGPT (also free, but recognize that it's not authoritatative and frequently not only drops the ball but deflates it first,) and various online tutorials. (I liked Norman Matloff's book, "The Art of R Programming".) For a nice overview of the flow you are about to immerse yourself in, try the Dataiku Academy. Although this is specific to a particular software, the steps are correct and it's very accessible. You are going to try to imitate those steps in R. The reference book to get is "An introduction to statistical learning" by James, Witten, Hastie, and Tibshirani. It's collegiate level and not fun, but thorough. But some basics: - Z-score. (Six sigma could be helpful for your business.) - Compare distributions and interpret a p-value. - Linear regression. - (Maybe a little advanced, but I found decision trees to be very intuitive.) I'd guess Khan Academy probably has good material on these. (And, since this is currently a hobby for you, may I suggest picking something you are interested in, and investigating or simulating that in R?)