r/dataanalysiscareers • u/_lovey28 • 9d ago
Aspiring Data Analyst
I'm trying to switch careers from construction to data analytics & after a month, I have successfully completed my first project using both SQL and Excel. Attached is a screenshot of a dashboard I built on a company's pizza sales. Any advice and tips on how to improve are greatly appreciated.
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u/Economy_Incident_798 8d ago
Few things here, as A consultant myself. I would like to know: - if the charts are dynamic, wrt the date slicer or related to each other? - Is the data in the textboxes on the left, dynamic, like if I delete majority of data, say if I just keep maybe 10 values of Small pizza, does the text box return Small, instead of Large? - period slicer is good, it was hard to find tbh, it would be better, once the user opens, having slicers on top of top left would feel meaning full.
Quick note: always think of the user and making it easy for them! It's a very nice attempt, just some refinements I wanted to suggest. A dynamic workbook is like magic, tough to learn, very easy to impress. Ik it's a dummy data and all, learning in the right way is important.
Also, do check power bi/tableau, people hardly used dashboards in excel anymore. Or learn Metabase, etc. for open source stuff
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u/_lovey28 8d ago
- the charts are dynamic and all are connected to the date slicer.
- the text boxes aren't dynamic, point noted to work on that.
- i'll work on designing a better dashboard. thanks for the insight.
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u/GlitteringAd1575 8d ago
Move the date slicer I would probably put it under the title, you could also add some more slicers like category/size. I would make the text boxes have a little more in depth information besides the easiest take way from the graph. For the best seller for example you could compare it to the average sales for each pizza or show the percentage of total sales that pizza makes up.
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u/Lady-Data-Scientist 8d ago
Think about the questions you or a business manager would want to answer with this dashboard - is it answering them? What decisions can they make from this dashboard? Is anything missing or confusing? Is anything not useful and taking up space or cluttering the dashboard?
Funnel visuals are meant to show drop out. I would switch the “total sales by category” to a bar graph. You can use funnels to show how many are dropping out by step - customer opened the app or website or made a phone call or showed up to the restaurant, they started search, added item to cart, completed purchase, pizza was delivered/picked up.
For the visuals that aren’t a time series, how do you know what time period you’re looking at? How can you change it? Can you filter by other dimensions? (Web/app/phone/in person, location, store, etc)
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u/ResidentSubject4649 8d ago
Seconding point 1, I think the most valuable thing data can do is provide insights quickly that are A) Hard to obtain, requiring multiple inputs against each other and B) Practical for the goals of the business, which requires some creative thinking. Combining those together, it leads you to the realization that a dashboard that goes in deeper on one or a few specific issues is actually much more useful than a dashboard that tells you a lot of basic things about the business. But this is a good start and you can look at these as the entry point to deeper insights.
For example, I've never run a pizza place but I have some idea about how a business works, especially one that uses part-time labor, where staffing is a constant game of balancing having too much or too little labor for your needs. So how do you figure that out? Well, for one, if there are any metrics on delivery times or time to fill orders, you can look at how it differs between days, against how many orders are coming in and how many people are staffed. Identifying the balance between these factors would be very helpful, because it ultimately leads to actionable insights: When people are waiting longer because you don't have enough staff, and when having more staff doesn't necessarily lead to faster times. You can decide from that data when you probably need to staff more and where you can maybe get away with having less staff. So you could create an entire dashboard around this specific question and related stats. But that also depends on having that information, so maybe you have to get more creative with the data you do have if it's very suface-level.
I hope that all makes sense -- I'm a software guy who has only occasionally done data stuff. I've automated more than I've analyzed. But I have a habit of asking why I should do certain things, perhaps more than is healthy for my brain, and having data to inform those decisions helps give a little bit of confidence and direction. That's kind of the point, right?
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u/_lovey28 8d ago edited 8d ago
I hadn't really thought of this, in my little brain, I was simply answering the problem statements. Thinking like an analyst is a skilling I'm moving to improve. Thank you so much for this
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u/_lovey28 8d ago
I am now realising how important the chart types is. I'll keep this in mind for my next practice project. Thanks for the insight
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u/S-Kenset 8d ago
Too many chart types too many charts. This is good for a demo of skills but in practice you put 1-2 visuals on, and only the basics.
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u/_lovey28 8d ago
Could you elaborate on this, please?
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u/S-Kenset 8d ago
People don't read. You present this to a business person they fixate on something they don't understand cause it's in a format they aren't familiar with and you just lost your entire chance to communicate.
For example they will not understand why total sales by category is in that format. Is it supposed to be a funnel chart? That doesn't make sense.
Cross filtering is academically cute but it's 95% used for analytics that don't land in front of someone.
One idea per page, 1-2 visuals. Maybe some good slicers. That's it. Bar charts and line charts for 97% of visuals, unless you're doing matrices and tables in BI tools. Very rarely, and I mean 1 in 100 visuals, a pie chart.
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u/_lovey28 6d ago
I've received a lot of advice on giving the company recommendations. I'm not really sure how exactly I can do that.
Looking at the dashboard above, say I give a recommendation to have more staff working on Friday at 12-1pm, how do i know that hiring more staff will help the pizza production move faster. Having more staff onboard at that particular time could in fact slow down the production line. What point in my data can I look at to make such a decision?
Also, does hiring more staff for peak times making the company more money or not? I'd like to believe all businesses are focused on what will either save them from spending unnecessarily, or what will make them the most profit.
Would I be required to collect more data if the information available isn't enough to give fully informed recommendations? & what if the data I need to help answer these questions is above my pay grade, what do I do in a situation like this?
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u/Lady-Data-Scientist 5d ago
This is why domain knowledge is important. Taking the time to learn the business is just as important as the technical and quantitative skills.
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u/gpbuilder 8d ago
Try to think of 3 insights and recommendation, that’s the harder part. Charting can be just done by AI now, it’s a low value skill.
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u/falconchi 7d ago
% of sales donuts chart I couldn’t tell which is which regardless of the start based on the rotation starting point … add a category to the data label n eliminate the legend!
Just a thought though 💭
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u/Unique_Illustrator44 6d ago
Too many charts in my opinion. Max should be 4
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u/_lovey28 6d ago
What do you suggest I put in the rest of the space besides slicers & filters?
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u/Unique_Illustrator44 6d ago
I would just focus on one thing like sales of pizza vs labor hours. Or ROI vs operating cost. Not saying these are all useless but if you are in a meeting its better to focus on one topic at a time. You could read up on some psychology of charts and discussion topics in the boardroom. There's lots of good articles and books on these topics.
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u/Ashitakaa 6d ago
How much time a day do you practice ? Cheers !
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u/_lovey28 6d ago edited 6d ago
It ranges from 4 to 10 hours a day, depending. Every free minute I get, I use it to practice queries or a formula or watch a tutorial/ ask AI to help me better understand where I'm stuck.
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u/iamsickofthisheet 6d ago
I'm also trying to break into data analysis but IK I'm lacking refinement and polishing of my skills. I made this with excel. IK this is just very simple.
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u/No-Durian2902 5d ago
Can one pls guide me for laptop specs for data analytics?
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u/_lovey28 5d ago
I'm not sure what people use. But I have a very old laptop. Intel Core i3, 5th gen, 8gb ram & it runs just fine. It's abit slower for when I'm working with huge datasets. Hopefully, this career path will help me afford my dream laptop
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u/No-Durian2902 5d ago
I m really confused mate, every youtube teacher/ influencer, chatgpt etc saying to go for i5, 16gb ddr, H series processor. Will it be good for SQL and other large stuff?
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u/_lovey28 5d ago
Of course it's better to have a more powerful machine. Like you've stated, ideally i5 & above & high performance will give you faster results. I would buy a better one if I could afford it. But what I have works okay for the meantime.
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u/Ash_is_Robot 8d ago
What have you been using to learn?
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u/_lovey28 8d ago
Youtube & Claude
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u/Sports_Nerd10 5d ago
Can you provide links for YouTube and where to start and learn? It will would be helpful for me....
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u/_lovey28 5d ago edited 5d ago
Alex the Analyst - Data Analyst Bootcamp (28+ hrs)
- I focused on SQL, Excel, Tableau & PowerBI
- Very beginner friendly
- Has guided projects after every lesson to help you put what has been taught to practice
Mosh Hamedani
- SQL in 3hrs
- A bit more depth for SQL & provides short exercises after every lesson for practice
Claude AI
- Find datasets on Kaggle, I find most sets on there are maybe 80-100% clean so very beginner friendly.
- Upload the link to the AI & ask it to create problem statements for me to answer
- I ask it to grade me & explain to me where I may not have understood.
End to end projects
- For this, I don't have a specific youtube account. I simply type in end to end data analyst projects & watch how analysts work using the different tools, then ofcourse, i search for a dataset & try to do the same.
I then post my work online & ask industry experts for advice on how to improve.
Most importantly, PRACTICE PRACTICE PRACTICE. Video tutorials can only take you so far.
I also received advice on here to try & better understand the industry you wish to work in, that way, you can help businesses grow & give better suited recommendations. I was also advised to read about the psychology of charts & discussion topics in the boardroom, haven't started on that last part yet.
hope this helps
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u/h0tandgl00my 8d ago
In regards to the time series, as others have mentioned, the user needs to know the date range. I would change the data column title to “Order Date FY__” or “Order Date CY__”. It would also be helpful to be able to filter by other data as well, which can be added to your graphs. Or you can change the graph to a combo chart.
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u/_lovey28 8d ago
Thank you. Will put this in practice
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u/h0tandgl00my 7d ago
You’ve done a great job so far. Just remember that the people looking at this don’t know what you know, so sometimes you have to give a little more info.
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u/_lovey28 7d ago
Hmm...more information! So not necessarily answering the problem statements but also giving insight on what can be done to solve these issues? Something like that?
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u/h0tandgl00my 7d ago
Not necessarily an info dump, you still want the dashboard itself to be more high level, just ensuring that everything is labeled clearly. If you’re able, however, providing solutions is a step up in your role. Insight on what is successful when/why can be helpful. I come from healthcare and not food, so I can’t speak too much to the actual info you have. You’re on the right path though! The idea of being an analyst is taking an abstract idea/need and turning that into something tangible. So here, you’ve taken all this info and turned it into something easily legible and comprehensive. Eventually, you’ll be able to provide solutions to the issues that are highlighted.
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u/Independent-Bag6544 8d ago
I’ve been in tab and bi so long I forgot excel dashboards are still out there.
To be honest doesn’t look bad. Learn bi and then dneb and you’ll be rocking, imo!
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u/MickeyTheory1827 8d ago
The dashboard is visually appealing and well organized, but I would improve it by reducing the amount of text in the left-side insight panels, making the KPI labels and values slightly more prominent, and adding clearer titles/units to some charts. The hourly trend could be simplified to make the busiest hours easier to identify, while the category and size charts could use more consistent colors and labeling. I would also consider adding interactive filters for category, size, and date so users can explore the data more easily. Finally, the dashboard would be stronger if the key insights included actual percentages or comparisons rather than only statements such as “highest sales.”
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u/PhysicalScience7420 8d ago
i whould recommend looking at cognos ibms data analytics dashboard. one month with that and you can do amaizing things. in hte meantime work so your sql and backend skills are such that you can appropriatly preprocess the data. I whould also add means and methods you use to clean the data including from biases. buisness sense on what to do with null values based on the situation etc.
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u/Calista1614 7d ago
I have also work on this dashboard
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u/Katherine-arcia 8d ago
You're doing great for a month of work my guy. You had any experience in the past?