Advice to transition to Data Analyst or Business Analyst roles

Hi All!

The title says it all: I want to transition into data analyst or business analyst roles. I'd love some advice on which skills to highlight and how to sell myself in a new role.

I've been in healthcare my entire working life from hospital food service to lab technician to research data manager to healthcare informaticist. I'm now looking to transition into data analytics or business analytics roles. I feel my skills would transition smoothly but I'm struggling with how to sell my experience as applicable to these other roles. I'm also struggling with how to address any shortcomings (e.g. lack of experience with Tableau).

1. Does anyone have any advice on successfully navigating career pivots?

2. Any advice on how to land data analyst roles?

3. Lastly, if anyone is willing to offer feedback on my resume or LinkedIn profile that would be awesome!

Long post incoming -First, career pivots:1. You are going to have to learn to tell your story and make it make sense. As someone who shifted from American Sign Language interpreting to leading an analytics firm as its Chief Visualization Officer, it can be done. It took me 5 years to really get over the imposter syndrome - with the right supports, I'm hoping you glide by that bit as much as possible.Here's one way I've told that story: https://www.tableaufit.com/tableau-ten-ured-serendipity-sign-language-storytelling/Here's another: https://bridgetcogley.com/storyAnd a post on imposter syndrome to keep in your back pocket: https://www.tableaufit.com/mathematics-imposter-syndrome/2. You'll want to understand your gaps - what are (truly) missing? The best way to do this is look at other people already doing the work first. You want to find several people that are newer in the analytics space as your starting point - looking for people fresh out of school or who are 1-2 years into their first analytics role. This gives you a better sense of where others are. One big note here: this is not to compare and despair, but to roadmap and benchmark. When you do this exercise, note what else you ADD to the mix: healthcare knowledge, direct experience AS a stakeholder for the analyses you'll eventually make. Don't discount these experiences. I cannot stress this section enough. Notice how it goes hand and hand with the first point. As someone who also does coaching, this is the #1 thing I end up stressing to career changes. Don't discount all the miles you travelled to this point.When I look entry level / early analytical roles, I'm considering (bridging between questions 1 and 2):- Basic understanding of data "shape," which covers relational algebra, dependancies, normal forms: you can get all of this from the "Modeling and theory" section of this course: https://www.edx.org/learn/relational-databases/stanford-university-databases-relational-databases-and-sql- Moderate understanding of chart choices (often bucketed under "stats") - what charts to choose, when, with the support of a chart chooser. Six Sigma, stats, and many Master's degrees fill this void typically. Financial Times Chart Chooser: https://github.com/Financial-Times/chart-doctor/blob/main/visual-vocabulary/README.md Abela's Chart Chooser: https://extremepresentation.typepad.com/files/choosing-a-good-chart-09.pdf Evergreen's Chart Chooser Cards: https://www.fassforward.com/chartchoosercards Storytelling with Data - to making a good chart: https://www.storytellingwithdata.com/- Logic or problem solving (sometimes mis-labelled as programming or computer science skills): This is one of the "hidden" cornerstone skills of analysis. How good are you at picking apart problems, breaking things down, and figuring out the order of things? You'll need this for creating calculations. General calcs in Tableau: https://www.tableaufit.com/excel-calculate-tableau-world-expressions/ Complex Example: https://www.tableaufit.com/excel-even-begin-calculate-tableau/- Communication Skills: the under-estimated skill in analysis. You'll need solid communication skills for requirements gathering, creating final expositions (dashboards, reports, presentations), validating work, and training. Requirements gathering: https://www.tableaufit.com/endless-abstraction-forms-ambiguous-requirements-gathering-modern-world/ General: https://www.tableaufit.com/designing-dashboards-that-deliver-translating-tableau-insights-for-business-users/ Advanced models of communication in dashboards: https://www.tableaufit.com/defining-accuracy-in-communication-interpreting-beyond-the-chart/- Curiosity: less a skill and more of a personality quirk - this shows up in a high number of job listings in a number of forms. At the end of the day: do you stick with the problem? Can you dig to the root of it? Another example of connecting your skillsets to the problem: https://www.tableaufit.com/data-and-the-world-in-which-i-live/More on this general skill set here: https://www.tableaufit.com/linear-aggression-degrees-data-science-career-development/Now getting specifically on how to land that job. As you've already seen and likely know, it is a tough market - one of the toughest I've seen in decades. You can still find work. You will want to build in the emotional supports for the job search and have a couple paths.There are 2 primary paths to consider:1. Working directly for a company2. Working as an analytics consultant.Working directly for a company may mean being the only analyst (do not recommend at this stage in your career) or within a team (generally recommended for supported learning). Usually junior analysts work under someone senior and may adapt existing work, or tackle tightly defined analyses. You'll generally show your work to a lead analyst first OR have someone you can call as a lifeline. Pay here is generally lower than consulting and career trajectories are more tightly managed. Growth tends to be slower (but not always!).Working as a consultant is generally fast-paced and great for people who like a lot of stimulation. You'll have less supports and may sometimes (or often) feel thrown in the deep end of the pool. I recommend this for self-learners who have a strong support network and are comfortable with a lot of ambiguity. In general, I find there's more jobs right now with consulting than with companies. This may or may not be a good path right out the gate. You may find it easier to get into something healthcare specific first and then bounce beyond that.Regardless of job, you should mentally budget to stay only about 2 years if you want to accelerate your growth. Regardless, every year, you should ensure you're choosing to stay, not defaulting to that choice. Keep those boundaries!Tableau is a good gateway tool. Tableau Public is free and they've just made it so you can now save locally. It has a high amount of support all available for free. IF you are considering a job using Tableau, I strongly recommend having at least 2-3 high quality dashboards that you made on your Tableau Public profile. You can see one presentation here: https://www.linkedin.com/events/6986790241089060864/comments/There's a vast number of FREE Tableau community initiatives to help with support, finding a data set, and establishing relationships: https://www.tableau.com/community/community-projects. To answer your final question, a number of people in the community will provide feedback, tools, and advice for free. Look for #DataFam #Tableau on LinkedIn and start connecting and interacting. You can find me on LinkedIn here - it's helpful if you include a note with your connection request that mentions Elpha: https://www.linkedin.com/in/bridgetcogley/In full disclosure, I provide coaching on careers on the side. From now until June 14th, I have a reduced rate of $150: https://calendly.com/theanalystsretreat/con-grad-ulations-career-talkAfter the 14th, I have my regular rate: https://calendly.com/theanalystsretreat/time-on-the-couch-careersThis is dedicated 1:1 time where we can tackle resumes, LinkedIn, etc. You can do this.