Hiring Manager Explains: Data Portfolio Do’s and Don’ts

so many online resources said that you need to build a portfolio to become an early career data analyst especially if you're transitioning from another industry but a lot of these resources do not tell you that if these projects don't have business relevant insights and don't show how you actually apply your technical skills to business relevant questions they're not actually going to help you stand out from the stack my name is Christine and I worked in analytics since 2015 starting out as a data analyst in healthcare Tech Consulting and eventually becoming a data director and hiring manager where I've helped hire interview and train many analysts over the years in this channel I'm going to be bringing you unique insights from inside the industry so that you can understand the most effective road map to becoming a data analyst today something that's really important for you to remember when it comes to portfolio projects is that there's a difference between projects that are for Learning and then projects that are for showing so the first bucket are projects that you do when you're getting comfortable with Excel SQL Tableau python are is not really commonly used in the industry anymore so sorry to those you guys who did the Google data analytics certificate I will talk more about this in another video but just know that if you are focusing on projects in this bucket that are clearly in the learning phase they're not going to get you past the resume wall you actually need to focus on projects that actually show how you apply your technical skills to relevant business questions by demonstrating your understanding of business metrics insights and Company recommendations to actually stand out from the stack so in the next few minutes I'm going to walk through a few critical dos and don'ts of what these kind of projects actually look like and then towards the end I will show you a stellar portfolio project that you could use to stand out to hiring managers and also talk about how you should actually demonstrate this on your resume and what interview questions you should prep for when talking about these projects I see a lot of projects that look like this this or this and these projects are just not going to cut it in today's job market and let me tell you why so in the first project we have a Google data analytics case study we have SQL project one SQL project 2 and then Excel project so you can probably already guess some of the things that I'm going to say about this portfolio one of them is that the Google analytics case study is just too generic and common place to stand out in today's job market so I really don't recommend doing this as an actual portfolio project for the showing bucket do it as a project more so for the learning bucket if you are doing that certificate then of course the project names are just way too generic this is not how we would be talking about projects at work we would actually be talking about projects at work probably using the company name or using some kind of business metric or team name and so you should do the same when you're actually talking about your portfolio projects you can see that the projects the write up also focuses on what this person did it talks about using SQL Excel to write queries and calculate certain things but I'm not actually interested in the fact that you use these tools I care a lot more about why you use these tools and what you use the tools to discover so it's completely devoid of insights and recommendations in this writeup and that's something that you need to have to be able to stand out and show your understanding of how you actually use use these tools as a cohesive system on the day-to-day job the other thing is that this is a personal website that is built on top of the GI of UI but it doesn't necessarily look like that nice so it doesn't actually help you to build a personal website if it looks like this you should actually be using GitHub because if you don't it's a lost opportunity to show that you know the real data ecosystem we use GitHub all the time as data analyst to store our projects and so the more your portfolio can represent the way that we actually use these tools on the job the better so here i' would have to click through many different links to actually get to the meat of the project I would first have to click on the header then it brings me to a Google drive folder where then I have to find the right file and then once I get to the right file I have to click on that file for a high manager who's going to be looking at your portfolio for honestly like maybe a few seconds if they even get there you should surface all the important stuff in a really accessible way so that it's right there for them when they go to your portfolio this project is focused on writing SQL qu to understand player performance in the US Open and the introduction to the project is kind of a personal story about why this person was interested in looking at the US Open metrics and then the project itself is just focused on showing the queries and then showing the output of these queries this overall to a hire manager it is very clearly a learning project because there aren't any company relevant metrics here that's not really clear to me what the so what is for why I want to understand player performance in the US Open for example example if I'm working in sales or marketing or product or Finance by showing just the SQL query and then the output of that query we know that so many people know how to write SQL these days that you need to go beyond what's actually in the query and the output of the query and talk more about the so what of what you calculated in this project one of my students had initially focused on Dungeons and Dragons analysis where he was using Excel to look at different stats of the different elements and weapons in the game to a hiring manager this is very obviously also a learning project because it has such a personal and Niche interest where if I was applying to any other company than the company that developed Dungeons and Dragons it's probably not going to be that relevant to me you can also see that he uses Excel functions like dropdowns conditional formatting color coding and there's kind of a lot going on in the spreadsheet where it's hard for me to actually see what's important this is not industry best practice where at work we care a lot more about Simplicity and Clarity rather than complexity so what does the company relevant portfolio actually look like first off make sure that you have a GitHub you can add a picture have a quick bio and have one to three repositories where in every single repository you have a read me that actually covers your insights and recommendations in this project from one of my workshops I analyzed subscriptions data from Zoom where I was looking at overall Trends and recommendations for the marketing and sales team since 2020 and the business question I was answering is essentially what are the trends in sales and how does this differ across key customer segments what areas do you recommend we look further into to improve sales over time the data is a mix of madeup data I blended from kagle and chat GPT and it's available for you to download through my GitHub which is linked in the description below right away this is a lot more company relevant because Zoom is a SAS company and SAS businesses often share similar Northstar metrics so use a business model that is widely applicable to the kinds of industries that you're actually interested in in the read me I give some context on the company from the standpoint of a data analyst actually working at that company so it's as if I'm presenting to the marketing or sales team notice that I didn't dive into the technical details and process I'm going right into the Northstar metrics the insights and the recommendations if we look at the Tableau dashboard it's also using industry best practices on dashboard structure and design in terms of its Simplicity Clarity and cleanliness here I see that you not only Built tables for reporting line graphs for Trend analysis and mix graphs for distribution analysis and from this I can learn a lot more about your business thinking in terms of the insights and recommendations a lot of the analysis in this project is founded on taking a key business metric like sales and then just slicing it by key Dimensions like plan type plan region and plan period and then highlighting these ups and downs and outliers in an easy to understand way and this tells hiring managers a lot of other things like the fact that you know fundamentals of Storytelling with data you can separate highlevel facts from low-level facts and you can also communicate to non-technical audiences for recommendations we're not necessarily looking for something that is extremely mathematically complex or even that conclusive it doesn't have to be something like and therefore we should stop selling this product once and for all it can be something that's more along the lines of where people should spend their time investigating or further looking into the data so for example work with the product and sales team to understand why there's a dip in this specific plan type over the last 3 months this represent how data analysts actually work with people on the job it's not necessarily our job to come up with a final recommendation but rather to guide People based on what we're seeing in those numbers so overall this project stands out a lot more because it has business relevant metrics and dimensions it focuses on insights and recommendations so I understand what value you would actually be bringing to the team when you're using these tools and it has a readme and a GitHub profile and it uses more than one tool at a time to demonstrate that you know how to use the real data ecosystem that we use at work to be honest with you guys hiring managers are not going to be spending a ton of time actually looking through your portfolio if they even get there instead it's more important for you to focus on building these projects so that you have rigorous enough experience for you to actually talk about when you get to the interview stage you do however need to be able to represent these projects well on your resume if they're actually going to help you when you're actually applying to jobs so here's an example of an impactful bullet that does this project Justice conducted analysis in SQL to to surface insights on sales Trends and SAS metrics for a self-created zoom data set containing 100K subscription records worked independently for 3 weeks to clean and analyze data in SQL and built performance dashboard in Tableau to visualize Trends related to plan types regions and plan periods surface insights and recommendations geared towards sales and marketing teams focusing on monthly promotions and Enterprise plans so notice that I not only talk about the tools here but I mentioned the actual metrics and I also include important keywords like SAS metrics sales and marketing team so in your final portfolio this is how your project should look in GitHub have one to three public repositories with one repo per project and for each project have a readme file that walks through those insights and recommendations and gives context on what you're doing as if you're an actual data analyst at that company also make sure that your GitHub is linked in your resume and that it's an actual clickable link so that someone can go to it very easily and also include your GitHub in your LinkedIn profile so that when you reach out to data hiring managers which I will talk about in a future video in terms of how to do that effectively people can really quickly go to that portfolio and get a sense for your skills when talking about your portfolio projects in early career data analyst interviews be prepared to answer questions like how did you clean this data set and what were some of the challenges that you bumped into what are some of the more interesting insights that you discovered and how did you find them how would you make sure that your insights are understandable to non-technical audiences and then also walk me through a tableau dashboard that you built and tell me more about why you structure the dashboard in this way leave a comment below if you want to understand how to give standout responses to these kinds of interviews because I know that these kinds of questions can be a bit tricky if you haven't actually worked as a data analyst before so I have a lot more to share about portfolio projects and how to actually apply your technical skills to real business questions and business thinking on the job but that's all we have time for today I am going to be doing some free live workshops soon so just check out the description to see if there's one coming up if you have questions or comments please just drop me a note below I will read through every single one and I would love to hear from you directly on what exactly you're struggling with and what you would like to see more content on so don't forget to subscribe and I'll see you soon

Channel: Christine Jiang

Views: 10,516

Keywords:

Id: csRK636TALQ

Length: 11min 11sec (671 seconds)

Published: Fri Jun 21 2024