Portfolio Projects: Beautify Your SQL Queries
We’ve all heard it before: creating projects is essential on your journey to becoming a data analyst.
As a quick review, here are a few reasons why projects should be part of your repertoire:
- They demonstrate practical skills.
- They show your problem solving ability.
- They give you hands-on experience.
- They showcase your communication skills, both written and visual.
- They set you apart from others in a competitive job market.
- They give you confidence that you have the necessary skills.
And best of all, projects can be fun!
What does a project consist of?
Project overview
You can start with a brief description of the project. Explain the objectives, context, and the problem or questions you aim to solve/answer through your analysis.
Data information
Include info like where you got your dataset and the type of data you’re using. Give an overview of what’s contained in the data: number and name of tables, types of columns, what information is found in them, etc.
Data cleaning
Talk about the steps you took to clean and process the data. Were there missing values, outliers, mismatched data types, or anything else that impacted your ability to complete your analysis? Discuss what you did and why.
Data exploration
A great way to get to know your data is through exploratory data analysis (EDA). Use simple queries and visualizations to find basic information about the data. How many records does your dataset contain? If there are date values, what timeframe does it cover? This could also be a great time to build an EER diagram to showcase the relationships between the tables in your data.
Data analysis
Showcase the SQL queries or Excel formulas you used to extract relevant data for analysis. Include a variety of queries that show your skills including filtering, grouping, joining, and aggregating data. Aim to answer the questions you laid out in your project overview.
Data insights and interpretation
Summarize what you found in your data analysis. Answer the questions that originally guided your project. Give recommendations and meaningful conclusions.
Data visualization
Create a dashboard or visualization with Power BI, Tableau, Excel, or another data visualization platform. Make sure to include only relevant information and keep your objectives in mind.
What next?
Wrap up your project by considering:
- Did I answer the questions laid out in my project overview?
- Did I provide solutions for problems?
- Are there steps I would take next to advance the analysis?
Provide a conclusion, a link to the data you used, and any references to external sources.
You’ve put together a fantastic project!
By the end of the process, you’ll have a polished dashboard or visual that clearly demonstrates your ability to gain insights from data and communicate them in a meaningful way…
But here’s one thing we often run into: sure, your portfolio project demonstrates your ability to put together a great Power BI, Tableau, or Excel dashboard, but it doesn’t exactly show the complexity of the SQL queries you wrote or how you found the information you’re displaying.
So what can you do?
Depending on where you’re hosting your project portfolio, you have a couple of options. If you’re hosting it on GitHub, you can add your SQL files to a repository. You can also simply add the SQL queries as markdown within a file. If you use WordPress, SquareSpace, or Wix, you can take screenshots of your queries and add them to your site or use code blocks in the pages.
What if you want to really focus on your SQL queries, though? If you’re using JOINs, CTEs, subqueries, and/or window functions (just to name a few), you may want to display that level of skill and expertise! You put a lot of hard work into them and to simply have them as an afterthought may not be the route you want to take. Maybe you really want to draw attention to the particularly complex queries you wrote as evidence that you have the skills needed to be a data analyst.
Here’s a few options…
There are multiple websites that allow you to create images of your source code so find the one that fits you and your needs best!
You can think about:
- Do I want something basic or an editor that allows me more flexibility and customization?
- Do I want titles on my queries to explain what their purpose is?
- Do I want a description section or will I stick with commenting my code throughout the query itself?
All of these questions will help guide you to the best fit.
Carbon
Carbon is easy to use and the interface is straightforward. It gives you some customization options, including theme, background color, and coding language. You can also create your own custom theme to choose the color of different keywords, numbers, and more. Carbon doesn’t give you the option of gradient backgrounds but does allow you to use an image. Interestingly, Carbon doesn’t give you an obvious option to provide a title for your image like some of the other editors you’ll see. You’ll definitely want to include some comments within your code to explain the purpose. Carbon is middle-of-the-road when it comes to customization options but it’s a great place to get started.
Snappify
Snappify has some of the most unique customization options that I’ve found and if you upgrade to a paid version, you get access to even more. In the free version, there are 6 preset themes to choose from. However, you can customize those even further and create entirely new ones in the Background section of the editor. You can choose to add a title or other elements including images, a profile picture, or other form elements. This editor has plenty of options but might feel a little overwhelming at first.
Ray.so
Ray.so allows you to change your theme and coding language. It also lets you give your query a title. While Ray.so gives you some amount of control over your customization, there aren’t as many options as with some of the other code editors; but, it still produces a visually aesthetic image! This might be a little less overwhelming for some beginners.
CodeKeep
CodeKeep’s interface is definitely more complex than some of the other options here and there are some pros and cons. It allows you to choose from preset templates, but those templates aren’t the typical color or gradient options. For instance, I chose the “Paper” template. It gives you a ton of customization options, including language, showing/hiding a title and description, adding social icons or other images, and much more. This one might be a little overwhelming but there are some cool options to explore!
CodeToImg
CodeToImg allows you to choose a background (color, gradient, or picture from Unsplash), coding language, image format, and more. It also allows you to provide a title to the image to give more context. In terms of customization, CodeToImg gives you a lot of freedom, from font size to amount of padding to scale and more.
Chalk.ist
Yet another option, Chalk.ist lets you choose from eight predefined themes, customize amount of padding on the X and Y axes, and choose from a set of coding language (SQL is, interestingly, not one of the choices). I like the look of the source code but there are definitely fewer customization options with Chalk.ist.
CodeImg
CodeImg asks you to start by choosing a Social Network Template and gives you insight into which ones are used most often. This allows you to ensure that the image fits the dimensions of different platforms, like Facebook and Twitter. Once you’ve done that, you’re directed a page that is similar to the other interfaces we’ve seen. CodeImg gives you a lot of control over canvas width and height, as well as editor theme. It doesn’t allow you as much customization in terms of background but is generally easy to use.
Still not sure how to put this into practice?
Here’s an example of a project I completed early in my data analyst journey. Scroll to the bottom to see how I added additional images to my project that display my SQL queries with Snappify!
Portfolio projects are a great tool for any data analyst who is looking for a job. They can clearly demonstrate the ability to think critically, problem solve, determine and communicate important insights, and more. Adding images of SQL queries can be an additional tool in your toolbox to show exactly how you did your analysis, the complexity of your queries, among many other benefits.
What do you think? Will you start adding images of your SQL queries to your projects?
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Happy learning!
