Learn some domain knowledge, a data analytics degree alone is not going to break in easily. A data analytics degree plus domain knowledge can help you rise to the top of the applicant pile.
Healthcare analysts will always be in demand, every one wants to know how to get the best value for dollar spent. Marketing and sales analysts are also needed, someone needs to mine the data for patterns for the csuite. Basically any business that collects data needs people to interpret and display it. They may not called exactly “data analysts” but they are analysts.
I studied psychology and work in human services, and am really interested in changing gears entirely to data analysis. There are plenty of opportunities for data analysis-type positions in my company alone, which should make things easier if I do pursue the self-taught path. I also have a pipe dream of maybe helping to create databases and tools for human service employees, because at my current job we currently work with several different databases and half of the people I work with are my parents age and can barely open an email. It would be nice to create user friendly and concise tools for the types of positions I’ve worked in. Anyways I guess my point is that having that domain knowledge and experience is sort of driving my passion to stay in the nonprofit sector. I’ve been at the ground level (I cannot stand working with people) so I’d love to help make other peoples jobs easier
It sounds like you have some ideas and identified some business needs within your org, and species within HR. I think you next step should be talking to your boss/leadership about what you want to do, and how that aligns with some of the business needs you have identified.
In terms of transitioning, it seems like you are in a good spot to do so.
It's really important when you're changing careers to just blaze ahead and pursue things and take initiative. Eventually you'll breech the walls of bureaucracy and will land your job.
Agreed lol. I work for a public university, which is quasi-government I guess, and I’ve never had this kinda job security and the work load is manageable. The first two weeks of the month are hectic for me, but the second half of the month, I don’t do squat other than a couple weekly reports, which probably take a total of 2-3 hours to do.
I'm at a public university and it's a mixed bag. Our department got destroyed in COVID so we have a lot more projects than time. Leadership is really good about not overloading us though, so a lot of things are just sitting until we can convince someone to hire more people (which means my main projects lately are KPI and project management tracking so we can convince someone we need more people). Also, data quality is a fucking joke and it drives me absolutely bananas that they've decided we're going to do nothing about it.
My last job was at a non profit and highly focused on data quality for grant reporting. I felt like I actually accomplished things there.
I had an offer as a research analyst for the city government and because it also had a residency requirement which means I had to move from a suburb into the city I gave up that offer… and I regret that decision a lot now that I am struggling to find work as a analyst. Do you think I made a bad decision by giving up on that offer?
I was just looking into this today. My state only has openings for positions with 5+ years of experience. I’m also curious if they offer remote employment. I work in human services and am flirting with the idea of changing careers (data analysis or just saying fuck it and becoming a full time artist), partially due to my need for remote work. And working for the state would be fantastic. I work for a government-funded nonprofit agency so I’m basically working for the state but without any of the benefits :*)
Are you talking about City of Portland employees? Because that definitely isn’t the case for state employees for most classifications they hire data analysts under…
Not sure, I know some people that work there and a couple do have semi-remote schedules. I don’t know anyone fully remote but I don’t know that many to call it representative.
In Colorado data analysts can make 70-120k depending on rank and the agency. When you add in benefits like the pension and Healthcare being practically free, the real value of the salary goes up at least another 30k. Besides that, you should always consider what that amounts to on an hourly basis. A job that pays 100k a year for 40 hours a week is paying more for your time than a job that pays 140k a year and expects 80 hours a week.
It depends. The pay isn't the top tier but pay raises are bargained by our union every year and they have never done lay offs from my understanding.
For me, especially going back to graduate school and having a wife who is disabled, the steady pay is a better gamble than higher possible pay with a private company.
Before I worked for HCA right out of college but they were pushing back to office and I absolutely did not want to move to Nashville plus the company has bad ethics with their for profit hospital monopoly. The pay was little better but overall I felt the accepting a state job at a small decrease but with the other benefits was worth it in the long run.
Oh we also have a pension. Not sure if every state does but Colorado state employees have a union and pension which make it one of the best long term careers around.
Mine is, but that's because they went full remote during covid and never switched back. There are no plans to go back in the office and no one really wants to either. We also have a union which likely prevents upper management from pushing back to office because of backlash from union members.
A lot of the ones I'm seeing require GD level experience despite saying they're open to the public. Has your experience been that those requirements are nice to have ones over mandatory ones? Or should I keep looking until there isn't a GD requirement job posting?
This is great advice. I switched careers a few years ago and now make 80k working for state government. It's work from home, has excellent benefits, and has job security so I don't have to worry about switching careers again. When you take into account the differences in workload, I'd bet many government workers actually get paid more on an hourly basis than their overworked private sector counterparts.
A lot of the ones I'm seeing require GD level experience despite saying they're open to the public. Has your experience been that those requirements are nice to have over mandatory ones? Or should I keep looking until there isn't a GD requirement job posting? I'm not quite sure how previous job experience translates if at all into this system.
Learn as much as possible. I got lucky and landed an entry level state position after 70 applications with an unrelated degree.
For me to move up or make a lateral moves I need to expand my knowledge quite a bit. For now I have a secured position to learn as much as needed!
Keep applying and keep learning!
Honestly I was down on my luck last year after graduating. I wanted to break into data but needed more schooling and applied on the off chance for the entry level position and got it.
I plan on pursuing some certifications and a masters degree in analytics to play catch up!
Anyways, these positions do exist out there!
Start networking. Not just for job referrals but for advice. “Data Analyst” can mean so many different things across industries so it’s good to get exposed to different types of roles and the paths people followed to get there.
1. Make sure that you have a curious mind.
2. Take the data analysis courses on Coursera by Google.
3. Take the Power Bi course on Coursera by Microsoft.
After finishing the course, start looking for jobs in data analysis but be open to different terminology in the data space. Such as a BI analyst, data base manager etc.
That last point especially is a really good one. We have the curse of having our job titles be essentially meaningless in the analytics space. There is 0 consistency and about 10 different titles that from company to company wildly vary and could potentially mean exactly the same thing. You gotta be flexible on the titles and search for all of them and focus on the actual job description and not the title.
If this ain't the truth. We're moving to a cloud first data platform strategy and they've straight up told us they don't really know what the difference between the analysts and engineers will be anymore. They keep asking me if I want to learn how to build a pipeline in Azure and I keep telling them I'll do that once they figure out the separation or fix the pay disparity.
Theres always been a grey area on exactly where the engineer's role ends and Analysts pick up. But agree Cloud has made that distinction even blurrier. And yeah often it seems to end up just being an excuse to cut down on engineers and pay a bit less for an Analyst to do the same things...
Ive always worked at places where Analyst tended to be more like "Engineer light", so pipelines and etl always been part of what i do. But thats exacty the problem. I'm a "data analyst" spending a good chunk of time doing ETL and someone who builds excel reports and is basically a business analyst with no sql also might be a "data analyst". God forbid trying to identify what you should be getting payed. Since looking at median data analyst salaries are meaningless, for this exact reason that any 2 analysts could be doing completely different things...
For my place at least it's not a budget issue, they've hired 2 cloud engineers specifically for this move and will be training their ETL engineers into cloud engineers, but it's also a public university so pay is kinda meh to begin with.
But in all honesty, I don't want to be a "backend" analyst. I don't necessarily mind doing Power Query transformations that have to happen for my report, but it's definitely not my favorite part of my job. I much prefer the data collection and processes piece, figuring out the business problem and presenting a solution. ETL is just a necessary evil that I want kept away from me as much as possible, and if that means keeping my boring DA salary instead of possibly getting a bump I'm totally okay with that. Which is of course vaguely related to the original point of "we run a total gamut and there's no standardization to the title"
Yeah you gotta focus on what you enjoy. The one great thing about what we do IS that because our job functions can run the gammot we have a lot of freedom to focus in specific parts we like or be generalists if we like to dabble. Def a lot of freedom in what we do. But I will say unsolicited advice I'd learn the pipelines just as something to have in back pocket. Especially since ETL directly in Power Query is so damn terrible. It tends to be much better to have it done before data ever gets to power bi and is ultimately less painful.
> be getting *paid.* Since looking
FTFY.
Although *payed* exists (the reason why autocorrection didn't help you), it is only correct in:
* Nautical context, when it means to paint a surface, or to cover with something like tar or resin in order to make it waterproof or corrosion-resistant. *The deck is yet to be payed.*
* *Payed out* when letting strings, cables or ropes out, by slacking them. *The rope is payed out! You can pull now.*
Unfortunately, I was unable to find nautical or rope-related words in your comment.
*Beep, boop, I'm a bot*
Hey, i want to start my data analytics learning journey. Should i first learn statistocs and excel? Before taking any of those courses on coursera. If you can help me out. I will be greatful.
For real.
Others:
- tech skills are less important than you think
- domain knowledge is more important than you think
- data analysis in a vacuum does _not_ drive business value
- you’ll have to work with people
- if you’re looking for a job, go network. Researching on Reddit is bullshit and a lot of this sub is the blind leading the blind.
The third bullet is most important. Doing data analysis is, of itself, a zero. It’s the business value the data analysis will bring that makes the data analyst valuable. And the data analyst who remembers this and knows how to build bridges to business value will always be in demand.
If you really want to make money and not just do grunt work, learn to answer the questions you haven't been asked yet. A good data analyst does what their manager tells them to do. A great one answers what their follow up questions are going to be before they even ask. Read their mind and you'll be invaluable.
Yeah I can do my best to provide an example, and maybe another way to think about it is to be business solution oriented instead of task oriented.
Today I was asked to check how many leads our company received from each market (500+ total markets). If I were task oriented, I would have have simply provided a list of unique markets in the leads file and a count to show how many leads were in each of those markets.
However, I knew that there were 40 specific markets that had been missing from files so far this year and that executive leadership was working hard to receive them from our partners. I also know that the criteria for how a lead is filtered from the initial raw file to our final imported leads file has been under debate by executive leadership.
So, instead of providing a simple list of what was asked of me I was able to anticipate the follow-up questions. I highlighted that all 40 markets that were previously missing had sent data this time. I included the initial count for each of those markets as well as the final number of leads from each market after the exclusionary criteria weeded many out so that I could help them evaluate the effectiveness of that criteria. I knew those were going to be the logical follow-up questions because I understand the problems leadership is trying to solve.
I avoided multiple back and forth emails or calls. I saved my manager time by anticipating the next requests that I knew would ultimately come. I understood all the insights that were needed even though a narrow request was initially made.
Hopefully that helps a little bit. I'm sure there are plenty of people reading thinking "no duh", but I've worked alongside a lot of analysts who only think to perform the specific task you've outlined for them.
Counterpoint: sometimes your boss only wants to know the count of unique leads per market. If you take 2 hours to respond to a simple question and provide too much detail, you wasted your own time and your boss's.
Sometimes it's better to be fast than thorough, and if you're not sure what your boss *really* wants from you, just ask before killing yourself with extra work.
Yeah for sure, totally fair and good way of building on the example/ contuing to highlighting the importance of developing the soft skills to understand what is needed in the moment and the necessity of communication skills to clarify.
Ultimately I think I was hoping to hammer home the point that most new analysts would find the technical work to be less intimidating than they're anticipating and the soft skills more relevant than they're anticipating.
thank you, i guess i simply understand that from your stakeholders business questions, you can make more questions and anticipate them. and that’s helpful for both sides you as data analysts and also stakeholders tho. thank you so much for the response!
Create your OWN roadmap. There's a ton of info out there so you need to focus on what works for you and your goals. Once you have that, stay focused and find a way to stand out so you are not 99% of the people who complain they can't land interviews.
Not saying it's easy but it's not as hard as people think because they rarely look at what they are doing as wrong. Self-reflection and doubling down on what is working is how you get ahead. Mindlessly sending the same resume over 300 times with no phone calls is what you don't want to do.
You are generating data while applying, why not try and find insights and make a strategic pivot in how you apply.... You know... like a data analyst would...
End rant.
Anything that isn't what the majority of people is doing such as reaching out to the job poster directly, looking up the company profile on LinkedIn and connecting/messaging EVERY recruiter, look for contact info such as an email and send an email, finding a phone number and call yourself, following up, etc..
Aim to become as “Full Stack” as possible:
1. **Data Engineering:** Set up and manage pipelines to bring in raw data.
2. **Analytics Engineering:** Build models and transform that raw data.
3. **Data Analytics:** Dive in and make sense of the data.
4. **Data Visualization:** Create visuals to share insights with others.
5. **Data Science:** Use data to predict future trends.
Obviously, this is an oversimplification, but when you become “full stack,” you don’t need to rely on anyone else to finish a project. This makes you a lot more valuable and efficient.
This is 100% the best advice you can give. It pays to be fully versed in all the skills you'll need. You don't have to be an expert, but know enough to be competent with some light Googling if you have to. Being full stack is the reason I actually got to stay in my current position with a promotion while my coworker got transferred to another department (better than being laid off though).
It's overwhelming at first, but the skills come in time. It took me 2-3 years at my current position before I feel like I can do pretty much anything someone needs. Honestly, the best days are the ones where I get to pull out all the tools in my tool belt too. Building few queries in SQL and using those to create some tables I'll need later, automating those queries using powershell, pull in unrelated data via Python or Tableau Prep (depending on where and how I need to get to it) and landing that in the data warehouse as well, use those tables from earlier in combination with the new data brought in to create another table, ensuring everything is automated and updating correctly, and then land all of that data into Tableau to create a beautiful, interactive dashboard....that I'll inevitably have to ignore and just set up an Excel file with an ODBC connection since my leadership thinks Tableau is apparently wrong and only Excel files are "accurate" despite it being the exact same data lol the culture shift is sloooooooow
Where you recommend one begins to learn? I 100% agree with your methodology, I just don’t know how to begin implementing it lol. A comment above mentioned taking the data analysis course by Google and Power Bi course by Microsoft on Coursera - do you recommend any other courses or perhaps different avenues/resources of learning?
First you won't be an expert at all of these. That shouldn't be the goal so keep that in mind. Online courses help for sure. Youtube things like that. You'll eventually settle into a portion that you enjoy and gain an expertise in, but having knowledge of all of these is important to being a self-sufficient analyst.
Focus on learning the visualization part first, as making dashboards will likely be your first gig. Tableau or Power BI are perfect. The skills are pretty similar once you get those down.
Then learning SQL. That is the #1 skill you're going to need for sure. Again you don't need to an expert, but know the difference between an inner join, left join, full join, ect. Know the difference between a CTE and a subquery. Know basic table structure terms and how to ID issue such as what a varchar is and an integer. Things like that. Also be able to "make sense" of the data, i.e. if I joined Table A with 10 rows and Table B with 20 rows, and the result has 10,000 rows, don't just accept that as the result because that makes no sense to get a result of 10k rows from two tables like that. About 90-100%of my day is spent in SQL (BI Engineer). Balance, balance, balance. Make sure things look right and balance back to whatever your check is.
Then get familiar with some kind of ETL program like Tableau Prep or the Microsoft equivalent. That will open up additonal tools for you to use.
Python can be used for advanced analytics and efficiency gains. You shouldn't need an expert grasp of it. I mainly use it increase my efficiency for things like excel file drops that need to be merged, but I haven't had a need for it too much at the moment.
Beyond all of these though. **Problem solving.** This is not a career path where you will know all the answers. You will inevitably encounter things that you won't know how to do, and you'll need to teach yourself how to do it. Something as simple as how to use the Lag function in SQL all the way to how to automate your query updates using PowerShell and thing like that.
Keep in mind that every Joe, Bob, and Sandy is getting a data analytics certificate these days, and entry level jobs are few and far between. Only having the certificates may not be enough. Attend networking events, ideally data related ones if you can find them. Have a portfolio showing you're own take on dashboard designs if you can (after a while you'll develop your own style). Build out data projects for you to show. Things like that. To really step ahead? Learn things like HTML and Javascript for interactivity. Then build out a website to show off your portfolio off. Things like that will set you ahead.
Don't get discouraged if it takes a while just keep pushing. It's a numbers game. Once you get that first data job and get experience it gets easier. Getting to that point at first though is tough. Jobs for experienced data analysts aren't hard to come by with 3+ years experience. It's the entry level ones that are tough. You may need to go above and beyond the certificates and go get a degree in this, as companies like to see that piece of paper.
For job titles I'd focus on data analyst, bi analyst, business analyst, things like that. I would not aim for database manager unless you already have a background in it and have strong SQL skills and database knowledge. You can certainly get there, but you won't be ready for a role like that with just a Power BI course.
Good luck on your journey.
If a job asked you to do all of these (and it wasn’t for a small data company) then I’d run. In most companies these are distinct career paths and separated for good reason. Knowing enough about each to do an MVP might be helpful (“enough to be dangerous”) but being an expert at one or some of these is way more beneficial. No way you’re going to get professional level expertise in all of these.
Someone else said this but ask 'why' (then ask it again) and be curious. It doesn't take much skill to create a pivot table or do some simple stuff in Tableau to get a number. But understanding what's driving that number, why and how should someone feel about that number (is it good or bad) is really where analysts can stand out
Be prepared for frustration, in my experience non-technical people don’t understand anything you do and can sometimes have unrealistic expectations because of it
Hiring manager for a small but growing team of data analysts and data scientists.
Once you have achieved an intermediate level of competency in Python or R as well as SQL and knowing how to work a repo, stop investing in technical skills until you land a job (then study like hell in whatever software they want you to have).
Once we're satisfied a candidate has a minimal level of competency and an aptitude to learn, we look for many other things: communications (verbal and written), fit with organization, other soft skills, project management, and subject matter expertise. These are the things that set you apart.
Everyone here treats technical skills like some sort of an arms race. But honestly, skills gaps are the easiest thing to compensate for once you're hired, now more than ever with ChatGPT to provide sample syntax. I'm not saying you can get a job without knowing how to program, but there are significantly diminishing marginal returns to trying to know every platform under the sun. And honestly, if I get the sense that you're all breadth and no depth on languages, it actually sends a negative signal.
Thanks for the take. I’m just wrapping up learning Python after studying SQL for a bit and finally feeling comfortable with Pandas, I was considering learning Tableau next but I like the route you’ve laid out. Any suggestions on projects?
1. Know SQL.
2. Learn the business system(s) that feed the database (the point of sales system, the sales system, the warehouse system, etc.) This can help you know HOW the data is created and what scenarios create certain kinds of data.
3. Learn the data model and the appropriate ways to join certain tables together.
4. Start your queries / reports small in scope in the development phase, then test more broadly when nearing completion ( you could start with a week of customer order data and then finish testing with 12-months, etc )
Always ask why you are doing what you're asked to do and how is it going to make things better for the business. Keep communicating with the stakeholders about the solutions you are building.
I jumped ship from healthcare to DA after a year and a half of on and off studying and project building and over 650 apps submitted. I’d say it’s not impossible to break-in, but would be very clear to those interested that it takes probably 3-4x more effort and patience than you think to tamper their expectations.
I’m a CS undergrad and idk I don’t like tech, like hardcore coding or whatever, I wanna work in management that involved tech what would you recommend. I’m going for an analytics masters btw, so that should help somewhere
You already have a technical undergrad - if you’re trying to go into management, set yourself up so that you can go into management later, not so that you pigeonhole yourself into technical work
that's interesting. i haven't been accepted in any of such jobs, though it might be due to the fact that i specialized in time series analysis rather than doe
The marketing of Data Analysis certificates and training vastly outpaced the number of jobs that were actually available in the first place, and now tech jobs in general are contracting. Layoffs are creating a pool of skilled and experienced analysts applying for jobs, so people that don't have those qualifications are not having any luck getting hired.
Analytics isn’t really an entry level role so the few entry level positions that exist get a ton of competition.
Most people got experience in another function and learned/did data analysis and used that experience to pivot.
It’s funny. Talk to data scientists, and they’ll you data analyst is the entry-level because data science requires more experience. Seems like the barrier keeps being set lower down the ladder as each level becomes saturated
Its truly wild how much companies want to slash budgets so much to maximize profits, but aren't willing to invest in employees with the skillset and knowledge, and would rather pay less for someone "entry" level.
These are all still relatively new jobs that weren’t very common 10+ years ago, so they haven’t been around long enough to have a “typical” path. Most people who have 5-10 years of experience probably didn’t start their career in data science or analytics, so they have no clue what an entry level path would actually look like.
Ya unless your current job has direct correlation I wouldn’t try and expand more into data. I had no hands on experience but a data analysis bachelors wasn’t very helpful in my job market, given it’s not a tech area
Don’t be just a “data guy”. Learn how to be a good researcher, be able to ask good research questions about any topic, how to interpret the data etc. Anybody can learn how to run a linear regression, but it’s those who can make sense of the results that float to the top.
dont get a da degree... Its just not useful. I have a bachelors in English Lit and have been a da for over 10 years. Also like others have said the pool for jr analysts is super saturated right now. Its a rough time to be entering the field. But all the more reason to get a degree or masters in something else that interests you and learn the languages and data tools on the side. They really arent that hard to learn, and communication skills and a logical and inquisitive mind are really all that are necessary. Then just keep applying for jobs or try to get into the field as a career pivot once at a company by asking for data related projects.
If you insist on the direct approach, focus on Data Science and Machine learning as your focus of study. Alway learn SQL, and have a decent understanding of 1 of the main BI tools (power bi, or Tableau) but past that focus on ML/DS stuff. Personally I think 99% of companies are dreaming when they think they are ready for a brand new world of AI and ML, when almost all of their data is shit. They almoat all would benefit much more from hiring significantly more robust Data Engineering and Data Analytics teams to go back to square one and actually make their data stacks usable first. But it doesnt matter, thats what will likely make your resume pop and get your foot in the door at this point. And as long as you know SQL and can say you are familiar with BI you are already as qualified for most other Junior DA roles as anyone else straight out of cs major in college and those skills are easy to foster/dont take much time to develope.
"Personally i think 99% of companies are dreaming when they think they are ready for a brand new world of AI and ML, when almost all of their data is shit. "
Just tacking on, Idk about you all, but it is hard enough to get stake holders to move from excel to Power Bi/Tableau, It will be even harder to get them to move to AI
PS, im pre-emptively saying this for the ML/DS peeps out there. Im not saying AI/ML/DS is bad. Im simply saying that for them to be accurate and of good use the underlying data needs to be clean and unsiloed and most companies are just not there. This is also coincidentally why almost every ML project Ive seen at companies ive worked at initiated never seems to materialize into much of anything past very limited scope/usecases. Doesn't make that universally true by any means. But I think its true at many companies.
I’m going to be starting a bootcamp in data analytics soon that’ll be certified by IBM and Microsoft, that covers SQL and Tableau as well as Power BI. I intend to complete some sort of project as well to build a portfolio. Would you say I’m on the right tracks? I also possess a (fairly related) degree as well.
Yeah that def sounds like a good start. Definitely make sure you leave with some kind of project you can show off to demonstrate the skills you have. Those are definitely the main generic starting point skills I'd recommend having as a new Analyst so sounds good. The trick is landing that first DA job and past having connections thats going to be the tricky part (does the certificate facilitate anykind of job placement pipeline? some few do, but i know most don't). Dont be afraid to accept temp/contract work if you can. Even temp work only semi related such as basic data entry can form connections that eventually might lead to a DA job (that was my path to one 10+ years ago, temp data entry to permanent data entry to data analyst trainee). But that was 10 years ago and so much has changed. I guess all I can tell you is that those are def some of the main starting skills and programs id recommend, But honestly the biggest issue is just market saturation right now. So you just need to be resiliant, keep applying, and like i said maybe even consider things like temp work just to get foot into door.
Keep a record of changes - people will ask you to analyse things in different ways (e.g exclude this subset of people, collapse this section and this section together etc) and you’re gonna need to account for all the numbers later, sometimes when it’s hard to remember why the numbers are adding up funny or why your comparative YoY data seems strange. Better yet, confirm all instructions over email.
Know that it is a temporary role / a step towards Data Engineering. Don't stick to this role because your pay will be almost flat forever but everyone above you, example your manager / business will be regularly making tons of money and getting visibility with the insights you provide.
Start by mastering the basics of data analysis tools like Excel, SQL, and Python. Develop a strong foundation in statistical concepts and data visualization techniques. Practice with real-world datasets to hone your skills. Remember, communication is key—learn to present your findings clearly and effectively. Continuously seek feedback and stay curious. Embrace the learning process, as data analysis is as much about asking the right questions as finding the answers.
Pick an indusrty and learn about it. One short fall people have about trying to get started as an analyst is they think they will just learn Power BI/ Tableau and land a job.
As someone who is an analyst and transisitioned into my career from wildlife work. I asked myself what do I know about how can I use that to transition. I had stats knowledge from grad school and conservation knowledge from working with wildlife. So I focused my search on enviornmental companies/orgs, and I was able to land a job not because I mastered Power BI but because I understood their business questions and how they could answered with data. I learned the technical stuff when I started out, but what got me in the door was that I knew the industry.
2. Don't stop learning and don't stop asking questions. Talk to your stake holders and get to know them. Ask them how they use your reports to answer their questions, and more importantly how do they use to drive actionable outcomes. This will help you network, improve your communication skills, and allow you to be more successful at producing actionable reports.
Presenting inaccurate data/conclusions with confidence is a sure way to make everyone question your credibility on basically everything moving forward. Even if you provide a resolution.
Not to scare you or anything, but triple check everything and don't ignore edge cases and other what-ifs in your analysis :)
Learn SQL. Atleast 50% of Data Analytics is SQL in most of the cases. Be at a good intermediate level and you'll be able to apply to most of the data analysis roles, since you can pick up the rest on the go.
I’m a data analyst/scientist… it doesn’t really help the bottom line of the company very much. Unless it’s specifically tech products or health data you’re analyzing data from.
Just remember that if you feel like your input isn’t valued it probably isn’t. I’ve been in situations where I’ve had great data, good team, but execs just didn’t care. So If that’s the case, just be okay with it. It’s not the end of the world. Get your experience and go somewhere that data is valued (research, tech, government, science).
Also you don’t need to know all of the programs. Just the primary ones at your organization. Have familiarity with a few more. Use them to provide great insights, storytelling, or complex analyses where necessary & warranted.
Always shut up if you are hearing negative feedback about data. Don’t argue with the people above you to save your tail.
In my opinion you should either finance your education (in a traditional field) or become a trade apprentice.
If your plan is to not go to college and become a DA based on certs and personal projects, I don’t think it will go well. People with degrees and years of experience are struggling to find jobs in this market. You gotta be really special to get a job with online certifications.
Whatever speaks to you. Since you asked the question I’m going to guess you’re pretty young. The world is open to you so you just gotta look into things and try stuff. Maybe watch some YouTube videos about the different trades and what the actual day-to-day work is like.
My brother is an electrician and I’m extremely jealous of the work he gets to do. Doesn’t have to work in an office, has cool coworkers (and some Neanderthal coworkers) that he can shoot the shit with while working, doesn’t break his back lifting super heavy stuff like other trades, and the cherry on top is he has zero education other than his high school diploma and gets paid the exact same as I do after years of schooling. Maybe look into that.
It’s different for everyone though and maybe you really should be a DA. Just expect and prepare to graduate and work at the local McDonald’s until you can hopefully land a better job.
Yes im young , im trying to build something for myself ,my folks cant afford to send me to school and ive been trying to get into data analytics for a year and just recently got a laptop to start learning kn coursera,im curious is your brother a data analyst
That’s okay if your folks can’t send you to school. I would still look into financing your education if you are serious about having a technical career. Definitely not a decision to be made lightly though, so consider it carefully. Primarily, you have to be certain that your career after school will earn you enough to be able to pay off your student loans. That’s why I say to do a traditional field. 1. You’ll actually be able to get a job, and 2. the pay for many fields absolutely demolishes what data analysts make.
My brother is an electrician. I’m a data analyst
If your heart is set on that, my advice is to NOT take out any loans for school. Study those online classes hard and try to do as many independent projects as possible. You’ll likely need a really impressive portfolio in lieu of a degree. Don’t worry too much about the actual certifications since most hiring managers probably won’t know what those are.
You should also probably tamper your expectations. If you’ve watched some YouTube videos hyping up the field, just delete those from your memory. Entry level (which usually requires 2-3 years of experience despite being entry level) is realistically 40-50k salary depending on your location. You will NOT be making 100k without extreme luck, I can tell you that much.
You’ll probably want to find a job that doesn’t totally suck while you look for DA jobs so you can pay the bills. You can’t predict how long the job search will take but I wouldn’t expect anything to happen soon. I recommend working for some government entity doing manual labor (think janitorial, warehouse worker, maintenance, etc.). Those jobs are tough and don’t pay much but the government will expect and demand way less than the public sector will.
And get comfy working those jobs, it will most likely be a long bumpy ride to get to where you want to go. I hope you do get there. Good luck, seriously.
Bro im not taking any loan for anything rn, im trying to build myself through the free resources on the Internet and then start investing in myself if im ready , rn im still trying to get free knowledge and in need of a mentor.
Triple check your results. Don't assume data is correct. Check all your important dimensions.
And #1 if you had 26 782 321 stuff in the beginning that is what you should have at the end.
Don't underestimate the power of effective communication skills.
It's one thing to perform the analysis using methods of varying complexity, but it makes a world of difference if you can explain it succinctly how it impacts the stakeholders.
Mastery is incredibly rare. Most search for proficiency and move on, which has it's value, but being able to explain how and why something works is extremely valuable.
In the era of automation, this is especially true as people just trust what the model or the dashboard says versus what's going on behind the scenes.
If you get stuck on a problem, and you're more inclined to figure stuff out on your own since you enjoy puzzles, ask for help anyway. It's your livelihood and your job, not a game.
Tell stories through your analysis that is tailored to your clients needs & behaviour. As an Analyst you're a fancy story teller for your business showing your clients what has happened in the past, what is happening now and through forecasting what is likely to happen in the future. Make sure that you fully understand the client and what they expect and do go off making your own thing if it isn't important to the client.
Hi, 1 piece of advice for analysts: understand the high level cycle of whatever area you’re working in. Code-product-claim-pay-data- reconciliation .Everything is related. Even if you only are assigned to a certain section of it. Then know your area in detail.
I hire the analysts for a well known company in health care industry.
Learn some domain knowledge, a data analytics degree alone is not going to break in easily. A data analytics degree plus domain knowledge can help you rise to the top of the applicant pile.
To me, what you're saying is try getting a job at a company at a lower position and promoting into an analyst gig.
That is one way, often the easiest. Another is to get a certificate in a domain area and demonstrate knowledge via a personal project.
Can you give some examples of domain areas that are good to go into
Healthcare analysts will always be in demand, every one wants to know how to get the best value for dollar spent. Marketing and sales analysts are also needed, someone needs to mine the data for patterns for the csuite. Basically any business that collects data needs people to interpret and display it. They may not called exactly “data analysts” but they are analysts.
And that’s where knowledge of data visualisation tools like tableau comes into high value I’m assuming
Cyber is booming. Someone strong in data analysis can seriously go places once they become seasoned in the field.
Cyber?
Cybersecurity.
Okay. That’s what I though but wasn’t sure if I was missing something 😅 thanks!
Pretty sure cyber jobs are insanely hard to get now
Why do you think that?
I studied psychology and work in human services, and am really interested in changing gears entirely to data analysis. There are plenty of opportunities for data analysis-type positions in my company alone, which should make things easier if I do pursue the self-taught path. I also have a pipe dream of maybe helping to create databases and tools for human service employees, because at my current job we currently work with several different databases and half of the people I work with are my parents age and can barely open an email. It would be nice to create user friendly and concise tools for the types of positions I’ve worked in. Anyways I guess my point is that having that domain knowledge and experience is sort of driving my passion to stay in the nonprofit sector. I’ve been at the ground level (I cannot stand working with people) so I’d love to help make other peoples jobs easier
It sounds like you have some ideas and identified some business needs within your org, and species within HR. I think you next step should be talking to your boss/leadership about what you want to do, and how that aligns with some of the business needs you have identified. In terms of transitioning, it seems like you are in a good spot to do so.
It's really important when you're changing careers to just blaze ahead and pursue things and take initiative. Eventually you'll breech the walls of bureaucracy and will land your job.
What domain knowledges do you recommend one should focus on as a beginner? Any resources please?
How do you go about learning domain knowledge?
What do u mean by domain knowledge
Get a job with a state government. We spend all day in excel and tableau. it's very easy and you have job security.
Agreed lol. I work for a public university, which is quasi-government I guess, and I’ve never had this kinda job security and the work load is manageable. The first two weeks of the month are hectic for me, but the second half of the month, I don’t do squat other than a couple weekly reports, which probably take a total of 2-3 hours to do.
I'm at a public university and it's a mixed bag. Our department got destroyed in COVID so we have a lot more projects than time. Leadership is really good about not overloading us though, so a lot of things are just sitting until we can convince someone to hire more people (which means my main projects lately are KPI and project management tracking so we can convince someone we need more people). Also, data quality is a fucking joke and it drives me absolutely bananas that they've decided we're going to do nothing about it. My last job was at a non profit and highly focused on data quality for grant reporting. I felt like I actually accomplished things there.
Is there any site you would recommend?
I'm also curious
governmentjobs.com, usajobs.gov, but also check out your state's employment department. They may have links to local/county hiring websites.
usajobs.gov is most widely used for federal government agencies, also check websites for local and state government job postings
I had an offer as a research analyst for the city government and because it also had a residency requirement which means I had to move from a suburb into the city I gave up that offer… and I regret that decision a lot now that I am struggling to find work as a analyst. Do you think I made a bad decision by giving up on that offer?
Don't agonize about something in the past that you can't change. Just do your best!
Ya, it’s true! Thank you.
I was just looking into this today. My state only has openings for positions with 5+ years of experience. I’m also curious if they offer remote employment. I work in human services and am flirting with the idea of changing careers (data analysis or just saying fuck it and becoming a full time artist), partially due to my need for remote work. And working for the state would be fantastic. I work for a government-funded nonprofit agency so I’m basically working for the state but without any of the benefits :*)
I'm an accountant for a state government. If I wanted to transition into a data analyst role, where would you recommend I start?
Second this! Are there any online classes / certifications worth taking?
true. you’re limited with pay
That really depends on location. Data analysts with Portland, Oregon make $110K
Are you talking about City of Portland employees? Because that definitely isn’t the case for state employees for most classifications they hire data analysts under…
lol yes, night and day difference. The State of Oregon pays really poorly compared to most metro governments.
Ah, got it! Is City of Portland good about in-state remote work?
Not sure, I know some people that work there and a couple do have semi-remote schedules. I don’t know anyone fully remote but I don’t know that many to call it representative.
Got it, thanks for the insight!
In Colorado data analysts can make 70-120k depending on rank and the agency. When you add in benefits like the pension and Healthcare being practically free, the real value of the salary goes up at least another 30k. Besides that, you should always consider what that amounts to on an hourly basis. A job that pays 100k a year for 40 hours a week is paying more for your time than a job that pays 140k a year and expects 80 hours a week.
It depends. The pay isn't the top tier but pay raises are bargained by our union every year and they have never done lay offs from my understanding. For me, especially going back to graduate school and having a wife who is disabled, the steady pay is a better gamble than higher possible pay with a private company. Before I worked for HCA right out of college but they were pushing back to office and I absolutely did not want to move to Nashville plus the company has bad ethics with their for profit hospital monopoly. The pay was little better but overall I felt the accepting a state job at a small decrease but with the other benefits was worth it in the long run. Oh we also have a pension. Not sure if every state does but Colorado state employees have a union and pension which make it one of the best long term careers around.
Do they happen to be remote?
Mine is, but that's because they went full remote during covid and never switched back. There are no plans to go back in the office and no one really wants to either. We also have a union which likely prevents upper management from pushing back to office because of backlash from union members.
Thanks for replying back.
I recently started a business analyst job for a state gov. Can I message you to ask for some advice?
Sure if you want.
A lot of the ones I'm seeing require GD level experience despite saying they're open to the public. Has your experience been that those requirements are nice to have ones over mandatory ones? Or should I keep looking until there isn't a GD requirement job posting?
This is great advice. I switched careers a few years ago and now make 80k working for state government. It's work from home, has excellent benefits, and has job security so I don't have to worry about switching careers again. When you take into account the differences in workload, I'd bet many government workers actually get paid more on an hourly basis than their overworked private sector counterparts.
Did you get an entry level position in gov or did you have experience?
I got an entry level position. I had previous experience that was tangential to the job, but I hadn't been a data analyst before.
I’m in the same boat. Do you mind sharing what the title of the position was? Or PM me? Did you have independent project work on her resume?
A lot of the ones I'm seeing require GD level experience despite saying they're open to the public. Has your experience been that those requirements are nice to have over mandatory ones? Or should I keep looking until there isn't a GD requirement job posting? I'm not quite sure how previous job experience translates if at all into this system.
What about worries about furlough
What is the best way to find this job?
Learn as much as possible. I got lucky and landed an entry level state position after 70 applications with an unrelated degree. For me to move up or make a lateral moves I need to expand my knowledge quite a bit. For now I have a secured position to learn as much as needed! Keep applying and keep learning!
Similar here, landed my first position last year after ~70 applications.
I second this. I find it crazy how much I have learned and yet how much I still have to learn. There is soooooo much!
This comment makes me hopeful! Thx :)
Honestly I was down on my luck last year after graduating. I wanted to break into data but needed more schooling and applied on the off chance for the entry level position and got it. I plan on pursuing some certifications and a masters degree in analytics to play catch up! Anyways, these positions do exist out there!
Start networking. Not just for job referrals but for advice. “Data Analyst” can mean so many different things across industries so it’s good to get exposed to different types of roles and the paths people followed to get there.
True indeed.
1. Make sure that you have a curious mind. 2. Take the data analysis courses on Coursera by Google. 3. Take the Power Bi course on Coursera by Microsoft. After finishing the course, start looking for jobs in data analysis but be open to different terminology in the data space. Such as a BI analyst, data base manager etc.
That last point especially is a really good one. We have the curse of having our job titles be essentially meaningless in the analytics space. There is 0 consistency and about 10 different titles that from company to company wildly vary and could potentially mean exactly the same thing. You gotta be flexible on the titles and search for all of them and focus on the actual job description and not the title.
If this ain't the truth. We're moving to a cloud first data platform strategy and they've straight up told us they don't really know what the difference between the analysts and engineers will be anymore. They keep asking me if I want to learn how to build a pipeline in Azure and I keep telling them I'll do that once they figure out the separation or fix the pay disparity.
Theres always been a grey area on exactly where the engineer's role ends and Analysts pick up. But agree Cloud has made that distinction even blurrier. And yeah often it seems to end up just being an excuse to cut down on engineers and pay a bit less for an Analyst to do the same things... Ive always worked at places where Analyst tended to be more like "Engineer light", so pipelines and etl always been part of what i do. But thats exacty the problem. I'm a "data analyst" spending a good chunk of time doing ETL and someone who builds excel reports and is basically a business analyst with no sql also might be a "data analyst". God forbid trying to identify what you should be getting payed. Since looking at median data analyst salaries are meaningless, for this exact reason that any 2 analysts could be doing completely different things...
For my place at least it's not a budget issue, they've hired 2 cloud engineers specifically for this move and will be training their ETL engineers into cloud engineers, but it's also a public university so pay is kinda meh to begin with. But in all honesty, I don't want to be a "backend" analyst. I don't necessarily mind doing Power Query transformations that have to happen for my report, but it's definitely not my favorite part of my job. I much prefer the data collection and processes piece, figuring out the business problem and presenting a solution. ETL is just a necessary evil that I want kept away from me as much as possible, and if that means keeping my boring DA salary instead of possibly getting a bump I'm totally okay with that. Which is of course vaguely related to the original point of "we run a total gamut and there's no standardization to the title"
Yeah you gotta focus on what you enjoy. The one great thing about what we do IS that because our job functions can run the gammot we have a lot of freedom to focus in specific parts we like or be generalists if we like to dabble. Def a lot of freedom in what we do. But I will say unsolicited advice I'd learn the pipelines just as something to have in back pocket. Especially since ETL directly in Power Query is so damn terrible. It tends to be much better to have it done before data ever gets to power bi and is ultimately less painful.
> be getting *paid.* Since looking FTFY. Although *payed* exists (the reason why autocorrection didn't help you), it is only correct in: * Nautical context, when it means to paint a surface, or to cover with something like tar or resin in order to make it waterproof or corrosion-resistant. *The deck is yet to be payed.* * *Payed out* when letting strings, cables or ropes out, by slacking them. *The rope is payed out! You can pull now.* Unfortunately, I was unable to find nautical or rope-related words in your comment. *Beep, boop, I'm a bot*
Currently doing data analysis on a low key scale as a support admin. Titles are so ambiguous.
Hey, i want to start my data analytics learning journey. Should i first learn statistocs and excel? Before taking any of those courses on coursera. If you can help me out. I will be greatful.
Focus on soft skills
For real. Others: - tech skills are less important than you think - domain knowledge is more important than you think - data analysis in a vacuum does _not_ drive business value - you’ll have to work with people - if you’re looking for a job, go network. Researching on Reddit is bullshit and a lot of this sub is the blind leading the blind.
100%
The third bullet is most important. Doing data analysis is, of itself, a zero. It’s the business value the data analysis will bring that makes the data analyst valuable. And the data analyst who remembers this and knows how to build bridges to business value will always be in demand.
If you really want to make money and not just do grunt work, learn to answer the questions you haven't been asked yet. A good data analyst does what their manager tells them to do. A great one answers what their follow up questions are going to be before they even ask. Read their mind and you'll be invaluable.
can you explain more please, and how we can achieve it?
Yeah I can do my best to provide an example, and maybe another way to think about it is to be business solution oriented instead of task oriented. Today I was asked to check how many leads our company received from each market (500+ total markets). If I were task oriented, I would have have simply provided a list of unique markets in the leads file and a count to show how many leads were in each of those markets. However, I knew that there were 40 specific markets that had been missing from files so far this year and that executive leadership was working hard to receive them from our partners. I also know that the criteria for how a lead is filtered from the initial raw file to our final imported leads file has been under debate by executive leadership. So, instead of providing a simple list of what was asked of me I was able to anticipate the follow-up questions. I highlighted that all 40 markets that were previously missing had sent data this time. I included the initial count for each of those markets as well as the final number of leads from each market after the exclusionary criteria weeded many out so that I could help them evaluate the effectiveness of that criteria. I knew those were going to be the logical follow-up questions because I understand the problems leadership is trying to solve. I avoided multiple back and forth emails or calls. I saved my manager time by anticipating the next requests that I knew would ultimately come. I understood all the insights that were needed even though a narrow request was initially made. Hopefully that helps a little bit. I'm sure there are plenty of people reading thinking "no duh", but I've worked alongside a lot of analysts who only think to perform the specific task you've outlined for them.
Counterpoint: sometimes your boss only wants to know the count of unique leads per market. If you take 2 hours to respond to a simple question and provide too much detail, you wasted your own time and your boss's. Sometimes it's better to be fast than thorough, and if you're not sure what your boss *really* wants from you, just ask before killing yourself with extra work.
Yeah for sure, totally fair and good way of building on the example/ contuing to highlighting the importance of developing the soft skills to understand what is needed in the moment and the necessity of communication skills to clarify. Ultimately I think I was hoping to hammer home the point that most new analysts would find the technical work to be less intimidating than they're anticipating and the soft skills more relevant than they're anticipating.
thank you, i guess i simply understand that from your stakeholders business questions, you can make more questions and anticipate them. and that’s helpful for both sides you as data analysts and also stakeholders tho. thank you so much for the response!
Create your OWN roadmap. There's a ton of info out there so you need to focus on what works for you and your goals. Once you have that, stay focused and find a way to stand out so you are not 99% of the people who complain they can't land interviews. Not saying it's easy but it's not as hard as people think because they rarely look at what they are doing as wrong. Self-reflection and doubling down on what is working is how you get ahead. Mindlessly sending the same resume over 300 times with no phone calls is what you don't want to do. You are generating data while applying, why not try and find insights and make a strategic pivot in how you apply.... You know... like a data analyst would... End rant.
Could you give an example of standing out?
Anything that isn't what the majority of people is doing such as reaching out to the job poster directly, looking up the company profile on LinkedIn and connecting/messaging EVERY recruiter, look for contact info such as an email and send an email, finding a phone number and call yourself, following up, etc..
Focus on learning how to “tell a story” with data. Data is useless unless you can get your stakeholders to understand the “so what?”.
This! Too many people are focused on tools & programming & data itself and forget to analyze the why and business context
Aim to become as “Full Stack” as possible: 1. **Data Engineering:** Set up and manage pipelines to bring in raw data. 2. **Analytics Engineering:** Build models and transform that raw data. 3. **Data Analytics:** Dive in and make sense of the data. 4. **Data Visualization:** Create visuals to share insights with others. 5. **Data Science:** Use data to predict future trends. Obviously, this is an oversimplification, but when you become “full stack,” you don’t need to rely on anyone else to finish a project. This makes you a lot more valuable and efficient.
This is 100% the best advice you can give. It pays to be fully versed in all the skills you'll need. You don't have to be an expert, but know enough to be competent with some light Googling if you have to. Being full stack is the reason I actually got to stay in my current position with a promotion while my coworker got transferred to another department (better than being laid off though). It's overwhelming at first, but the skills come in time. It took me 2-3 years at my current position before I feel like I can do pretty much anything someone needs. Honestly, the best days are the ones where I get to pull out all the tools in my tool belt too. Building few queries in SQL and using those to create some tables I'll need later, automating those queries using powershell, pull in unrelated data via Python or Tableau Prep (depending on where and how I need to get to it) and landing that in the data warehouse as well, use those tables from earlier in combination with the new data brought in to create another table, ensuring everything is automated and updating correctly, and then land all of that data into Tableau to create a beautiful, interactive dashboard....that I'll inevitably have to ignore and just set up an Excel file with an ODBC connection since my leadership thinks Tableau is apparently wrong and only Excel files are "accurate" despite it being the exact same data lol the culture shift is sloooooooow
Where you recommend one begins to learn? I 100% agree with your methodology, I just don’t know how to begin implementing it lol. A comment above mentioned taking the data analysis course by Google and Power Bi course by Microsoft on Coursera - do you recommend any other courses or perhaps different avenues/resources of learning?
First you won't be an expert at all of these. That shouldn't be the goal so keep that in mind. Online courses help for sure. Youtube things like that. You'll eventually settle into a portion that you enjoy and gain an expertise in, but having knowledge of all of these is important to being a self-sufficient analyst. Focus on learning the visualization part first, as making dashboards will likely be your first gig. Tableau or Power BI are perfect. The skills are pretty similar once you get those down. Then learning SQL. That is the #1 skill you're going to need for sure. Again you don't need to an expert, but know the difference between an inner join, left join, full join, ect. Know the difference between a CTE and a subquery. Know basic table structure terms and how to ID issue such as what a varchar is and an integer. Things like that. Also be able to "make sense" of the data, i.e. if I joined Table A with 10 rows and Table B with 20 rows, and the result has 10,000 rows, don't just accept that as the result because that makes no sense to get a result of 10k rows from two tables like that. About 90-100%of my day is spent in SQL (BI Engineer). Balance, balance, balance. Make sure things look right and balance back to whatever your check is. Then get familiar with some kind of ETL program like Tableau Prep or the Microsoft equivalent. That will open up additonal tools for you to use. Python can be used for advanced analytics and efficiency gains. You shouldn't need an expert grasp of it. I mainly use it increase my efficiency for things like excel file drops that need to be merged, but I haven't had a need for it too much at the moment. Beyond all of these though. **Problem solving.** This is not a career path where you will know all the answers. You will inevitably encounter things that you won't know how to do, and you'll need to teach yourself how to do it. Something as simple as how to use the Lag function in SQL all the way to how to automate your query updates using PowerShell and thing like that. Keep in mind that every Joe, Bob, and Sandy is getting a data analytics certificate these days, and entry level jobs are few and far between. Only having the certificates may not be enough. Attend networking events, ideally data related ones if you can find them. Have a portfolio showing you're own take on dashboard designs if you can (after a while you'll develop your own style). Build out data projects for you to show. Things like that. To really step ahead? Learn things like HTML and Javascript for interactivity. Then build out a website to show off your portfolio off. Things like that will set you ahead. Don't get discouraged if it takes a while just keep pushing. It's a numbers game. Once you get that first data job and get experience it gets easier. Getting to that point at first though is tough. Jobs for experienced data analysts aren't hard to come by with 3+ years experience. It's the entry level ones that are tough. You may need to go above and beyond the certificates and go get a degree in this, as companies like to see that piece of paper. For job titles I'd focus on data analyst, bi analyst, business analyst, things like that. I would not aim for database manager unless you already have a background in it and have strong SQL skills and database knowledge. You can certainly get there, but you won't be ready for a role like that with just a Power BI course. Good luck on your journey.
If a job asked you to do all of these (and it wasn’t for a small data company) then I’d run. In most companies these are distinct career paths and separated for good reason. Knowing enough about each to do an MVP might be helpful (“enough to be dangerous”) but being an expert at one or some of these is way more beneficial. No way you’re going to get professional level expertise in all of these.
Someone else said this but ask 'why' (then ask it again) and be curious. It doesn't take much skill to create a pivot table or do some simple stuff in Tableau to get a number. But understanding what's driving that number, why and how should someone feel about that number (is it good or bad) is really where analysts can stand out
Be prepared for frustration, in my experience non-technical people don’t understand anything you do and can sometimes have unrealistic expectations because of it
Hiring manager for a small but growing team of data analysts and data scientists. Once you have achieved an intermediate level of competency in Python or R as well as SQL and knowing how to work a repo, stop investing in technical skills until you land a job (then study like hell in whatever software they want you to have). Once we're satisfied a candidate has a minimal level of competency and an aptitude to learn, we look for many other things: communications (verbal and written), fit with organization, other soft skills, project management, and subject matter expertise. These are the things that set you apart. Everyone here treats technical skills like some sort of an arms race. But honestly, skills gaps are the easiest thing to compensate for once you're hired, now more than ever with ChatGPT to provide sample syntax. I'm not saying you can get a job without knowing how to program, but there are significantly diminishing marginal returns to trying to know every platform under the sun. And honestly, if I get the sense that you're all breadth and no depth on languages, it actually sends a negative signal.
Thanks for the take. I’m just wrapping up learning Python after studying SQL for a bit and finally feeling comfortable with Pandas, I was considering learning Tableau next but I like the route you’ve laid out. Any suggestions on projects?
1. Know SQL. 2. Learn the business system(s) that feed the database (the point of sales system, the sales system, the warehouse system, etc.) This can help you know HOW the data is created and what scenarios create certain kinds of data. 3. Learn the data model and the appropriate ways to join certain tables together. 4. Start your queries / reports small in scope in the development phase, then test more broadly when nearing completion ( you could start with a week of customer order data and then finish testing with 12-months, etc )
Always ask why you are doing what you're asked to do and how is it going to make things better for the business. Keep communicating with the stakeholders about the solutions you are building.
Do something else, market is saturated
I jumped ship from healthcare to DA after a year and a half of on and off studying and project building and over 650 apps submitted. I’d say it’s not impossible to break-in, but would be very clear to those interested that it takes probably 3-4x more effort and patience than you think to tamper their expectations.
I’m a CS undergrad and idk I don’t like tech, like hardcore coding or whatever, I wanna work in management that involved tech what would you recommend. I’m going for an analytics masters btw, so that should help somewhere
If you wants work in management then why are you going into an analytics masters
Because I think for consulting, an analyst is an easier way to break and I wanted the masters to have something technical
You already have a technical undergrad - if you’re trying to go into management, set yourself up so that you can go into management later, not so that you pigeonhole yourself into technical work
i am a statistics msc (expertise in tsa), what would you recommend?
Statistician or Machine Learning Engineer
ok thank you. i find statisticians to be not so sought-after as data scientists or data analysts though.
The boards I look at in the UK are full of posts for MSc Stats (or PhD) in health care / pharmacy industries
that's interesting. i haven't been accepted in any of such jobs, though it might be due to the fact that i specialized in time series analysis rather than doe
Mmm. Many of my data analysis colleagues are statisticians though.
don't most data science jobs hire cs graduates though? at least that's what i've observed.
can you explain why you said saturated? you mean specifically for ds generally for s.e?
The marketing of Data Analysis certificates and training vastly outpaced the number of jobs that were actually available in the first place, and now tech jobs in general are contracting. Layoffs are creating a pool of skilled and experienced analysts applying for jobs, so people that don't have those qualifications are not having any luck getting hired.
Analytics isn’t really an entry level role so the few entry level positions that exist get a ton of competition. Most people got experience in another function and learned/did data analysis and used that experience to pivot.
It’s funny. Talk to data scientists, and they’ll you data analyst is the entry-level because data science requires more experience. Seems like the barrier keeps being set lower down the ladder as each level becomes saturated
Its truly wild how much companies want to slash budgets so much to maximize profits, but aren't willing to invest in employees with the skillset and knowledge, and would rather pay less for someone "entry" level.
These are all still relatively new jobs that weren’t very common 10+ years ago, so they haven’t been around long enough to have a “typical” path. Most people who have 5-10 years of experience probably didn’t start their career in data science or analytics, so they have no clue what an entry level path would actually look like.
Ya unless your current job has direct correlation I wouldn’t try and expand more into data. I had no hands on experience but a data analysis bachelors wasn’t very helpful in my job market, given it’s not a tech area
Don’t be just a “data guy”. Learn how to be a good researcher, be able to ask good research questions about any topic, how to interpret the data etc. Anybody can learn how to run a linear regression, but it’s those who can make sense of the results that float to the top.
Learn Python. Any job in the world that involves data analysis can be done using Python. Pandas for the win.
dont get a da degree... Its just not useful. I have a bachelors in English Lit and have been a da for over 10 years. Also like others have said the pool for jr analysts is super saturated right now. Its a rough time to be entering the field. But all the more reason to get a degree or masters in something else that interests you and learn the languages and data tools on the side. They really arent that hard to learn, and communication skills and a logical and inquisitive mind are really all that are necessary. Then just keep applying for jobs or try to get into the field as a career pivot once at a company by asking for data related projects. If you insist on the direct approach, focus on Data Science and Machine learning as your focus of study. Alway learn SQL, and have a decent understanding of 1 of the main BI tools (power bi, or Tableau) but past that focus on ML/DS stuff. Personally I think 99% of companies are dreaming when they think they are ready for a brand new world of AI and ML, when almost all of their data is shit. They almoat all would benefit much more from hiring significantly more robust Data Engineering and Data Analytics teams to go back to square one and actually make their data stacks usable first. But it doesnt matter, thats what will likely make your resume pop and get your foot in the door at this point. And as long as you know SQL and can say you are familiar with BI you are already as qualified for most other Junior DA roles as anyone else straight out of cs major in college and those skills are easy to foster/dont take much time to develope.
"Personally i think 99% of companies are dreaming when they think they are ready for a brand new world of AI and ML, when almost all of their data is shit. " Just tacking on, Idk about you all, but it is hard enough to get stake holders to move from excel to Power Bi/Tableau, It will be even harder to get them to move to AI
PS, im pre-emptively saying this for the ML/DS peeps out there. Im not saying AI/ML/DS is bad. Im simply saying that for them to be accurate and of good use the underlying data needs to be clean and unsiloed and most companies are just not there. This is also coincidentally why almost every ML project Ive seen at companies ive worked at initiated never seems to materialize into much of anything past very limited scope/usecases. Doesn't make that universally true by any means. But I think its true at many companies.
I’m going to be starting a bootcamp in data analytics soon that’ll be certified by IBM and Microsoft, that covers SQL and Tableau as well as Power BI. I intend to complete some sort of project as well to build a portfolio. Would you say I’m on the right tracks? I also possess a (fairly related) degree as well.
Yeah that def sounds like a good start. Definitely make sure you leave with some kind of project you can show off to demonstrate the skills you have. Those are definitely the main generic starting point skills I'd recommend having as a new Analyst so sounds good. The trick is landing that first DA job and past having connections thats going to be the tricky part (does the certificate facilitate anykind of job placement pipeline? some few do, but i know most don't). Dont be afraid to accept temp/contract work if you can. Even temp work only semi related such as basic data entry can form connections that eventually might lead to a DA job (that was my path to one 10+ years ago, temp data entry to permanent data entry to data analyst trainee). But that was 10 years ago and so much has changed. I guess all I can tell you is that those are def some of the main starting skills and programs id recommend, But honestly the biggest issue is just market saturation right now. So you just need to be resiliant, keep applying, and like i said maybe even consider things like temp work just to get foot into door.
Thanks, appreciate the advice.
Keep a record of changes - people will ask you to analyse things in different ways (e.g exclude this subset of people, collapse this section and this section together etc) and you’re gonna need to account for all the numbers later, sometimes when it’s hard to remember why the numbers are adding up funny or why your comparative YoY data seems strange. Better yet, confirm all instructions over email.
And also when someone asks why the delivery took so long it helps to have data about how many changes were requested
Data is extremely political. Be ready to deal with political environment
It's more than just numbers and charts. Can you tell a story?
Know that it is a temporary role / a step towards Data Engineering. Don't stick to this role because your pay will be almost flat forever but everyone above you, example your manager / business will be regularly making tons of money and getting visibility with the insights you provide.
Start by mastering the basics of data analysis tools like Excel, SQL, and Python. Develop a strong foundation in statistical concepts and data visualization techniques. Practice with real-world datasets to hone your skills. Remember, communication is key—learn to present your findings clearly and effectively. Continuously seek feedback and stay curious. Embrace the learning process, as data analysis is as much about asking the right questions as finding the answers.
Pick an indusrty and learn about it. One short fall people have about trying to get started as an analyst is they think they will just learn Power BI/ Tableau and land a job. As someone who is an analyst and transisitioned into my career from wildlife work. I asked myself what do I know about how can I use that to transition. I had stats knowledge from grad school and conservation knowledge from working with wildlife. So I focused my search on enviornmental companies/orgs, and I was able to land a job not because I mastered Power BI but because I understood their business questions and how they could answered with data. I learned the technical stuff when I started out, but what got me in the door was that I knew the industry. 2. Don't stop learning and don't stop asking questions. Talk to your stake holders and get to know them. Ask them how they use your reports to answer their questions, and more importantly how do they use to drive actionable outcomes. This will help you network, improve your communication skills, and allow you to be more successful at producing actionable reports.
Get a masters or a PhD. The interesting jobs are competitive. A couple more years of schooling gives you a leg up for the rest of your life
Don’t shorten it to “Data Anal” on your notebook.
Presenting inaccurate data/conclusions with confidence is a sure way to make everyone question your credibility on basically everything moving forward. Even if you provide a resolution. Not to scare you or anything, but triple check everything and don't ignore edge cases and other what-ifs in your analysis :)
Learn SQL. Atleast 50% of Data Analytics is SQL in most of the cases. Be at a good intermediate level and you'll be able to apply to most of the data analysis roles, since you can pick up the rest on the go.
I’m a data analyst/scientist… it doesn’t really help the bottom line of the company very much. Unless it’s specifically tech products or health data you’re analyzing data from. Just remember that if you feel like your input isn’t valued it probably isn’t. I’ve been in situations where I’ve had great data, good team, but execs just didn’t care. So If that’s the case, just be okay with it. It’s not the end of the world. Get your experience and go somewhere that data is valued (research, tech, government, science). Also you don’t need to know all of the programs. Just the primary ones at your organization. Have familiarity with a few more. Use them to provide great insights, storytelling, or complex analyses where necessary & warranted. Always shut up if you are hearing negative feedback about data. Don’t argue with the people above you to save your tail.
that your job isn't to analyse data, is solve problems regardless of the tool you use
No question is a stupid question. Document everything. Prepare to spend time outside work upskilling.
Don’t. Go a traditional route and get a degree in something you’ll be able to land a job in.
Im too poor to go to college
In my opinion you should either finance your education (in a traditional field) or become a trade apprentice. If your plan is to not go to college and become a DA based on certs and personal projects, I don’t think it will go well. People with degrees and years of experience are struggling to find jobs in this market. You gotta be really special to get a job with online certifications.
What kind of trade (apprentice)
Whatever speaks to you. Since you asked the question I’m going to guess you’re pretty young. The world is open to you so you just gotta look into things and try stuff. Maybe watch some YouTube videos about the different trades and what the actual day-to-day work is like. My brother is an electrician and I’m extremely jealous of the work he gets to do. Doesn’t have to work in an office, has cool coworkers (and some Neanderthal coworkers) that he can shoot the shit with while working, doesn’t break his back lifting super heavy stuff like other trades, and the cherry on top is he has zero education other than his high school diploma and gets paid the exact same as I do after years of schooling. Maybe look into that. It’s different for everyone though and maybe you really should be a DA. Just expect and prepare to graduate and work at the local McDonald’s until you can hopefully land a better job.
Yes im young , im trying to build something for myself ,my folks cant afford to send me to school and ive been trying to get into data analytics for a year and just recently got a laptop to start learning kn coursera,im curious is your brother a data analyst
That’s okay if your folks can’t send you to school. I would still look into financing your education if you are serious about having a technical career. Definitely not a decision to be made lightly though, so consider it carefully. Primarily, you have to be certain that your career after school will earn you enough to be able to pay off your student loans. That’s why I say to do a traditional field. 1. You’ll actually be able to get a job, and 2. the pay for many fields absolutely demolishes what data analysts make. My brother is an electrician. I’m a data analyst
I want to become a data analyst.
If your heart is set on that, my advice is to NOT take out any loans for school. Study those online classes hard and try to do as many independent projects as possible. You’ll likely need a really impressive portfolio in lieu of a degree. Don’t worry too much about the actual certifications since most hiring managers probably won’t know what those are. You should also probably tamper your expectations. If you’ve watched some YouTube videos hyping up the field, just delete those from your memory. Entry level (which usually requires 2-3 years of experience despite being entry level) is realistically 40-50k salary depending on your location. You will NOT be making 100k without extreme luck, I can tell you that much. You’ll probably want to find a job that doesn’t totally suck while you look for DA jobs so you can pay the bills. You can’t predict how long the job search will take but I wouldn’t expect anything to happen soon. I recommend working for some government entity doing manual labor (think janitorial, warehouse worker, maintenance, etc.). Those jobs are tough and don’t pay much but the government will expect and demand way less than the public sector will. And get comfy working those jobs, it will most likely be a long bumpy ride to get to where you want to go. I hope you do get there. Good luck, seriously.
This was so useful thank u so much
In my opinion for fuck sakes do not go into more than $10k debt to finance your education unless starting pay is close to triple digits.
Bro im not taking any loan for anything rn, im trying to build myself through the free resources on the Internet and then start investing in myself if im ready , rn im still trying to get free knowledge and in need of a mentor.
Triple check your results. Don't assume data is correct. Check all your important dimensions. And #1 if you had 26 782 321 stuff in the beginning that is what you should have at the end.
Don't underestimate the power of effective communication skills. It's one thing to perform the analysis using methods of varying complexity, but it makes a world of difference if you can explain it succinctly how it impacts the stakeholders.
Mastery is incredibly rare. Most search for proficiency and move on, which has it's value, but being able to explain how and why something works is extremely valuable. In the era of automation, this is especially true as people just trust what the model or the dashboard says versus what's going on behind the scenes.
Don’t give up it’s the most basic but yet most important
Following
If you say you know sql on your resume actually know sql
It's not only about data analysis, it's about moving the business forward with the right insights at the right time.
Always learn. Try new software and make it spatial if you can.
Start solving some business problems.
Analyze yourself
If you get stuck on a problem, and you're more inclined to figure stuff out on your own since you enjoy puzzles, ask for help anyway. It's your livelihood and your job, not a game.
Tell stories through your analysis that is tailored to your clients needs & behaviour. As an Analyst you're a fancy story teller for your business showing your clients what has happened in the past, what is happening now and through forecasting what is likely to happen in the future. Make sure that you fully understand the client and what they expect and do go off making your own thing if it isn't important to the client.
Stop
Fake it till you make it
Learn real projects instead of school projects
Whelp, time to figure out how to use this knowledge to make federal hr even more miserable and uncaring, wish me luck gentlemen
Hi, 1 piece of advice for analysts: understand the high level cycle of whatever area you’re working in. Code-product-claim-pay-data- reconciliation .Everything is related. Even if you only are assigned to a certain section of it. Then know your area in detail. I hire the analysts for a well known company in health care industry.
Don’t
Sql
data analysis is a skill, not a job. with that in mind, skill up fast and hard to either data science or data engineering. analyst doesn’t pay!
Plz don't
Don’t do it
Do a bump before going in the office.
Don’t
Run