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How To Build a Data Analyst Portfolio (And Why You Need One)

Preparing for a career as a data analyst? Your data analyst portfolio is your chance to showcase your ability to tell a story, which is an essential element of data analysis. But this time, the story isn't just about data — it's about yourself as a professional. Nothing conveys the power of a story better than tangible examples, and your data analyst portfolio is your opportunity to show how your story can intersect with that of the company you’re applying to.

In this article we'll share some tips to help you build your own data analyst portfolio. We'll provide information about what to include in your portfolio, the skills you'll want to showcase, as well as ideas for actually creating and hosting your portfolio.

What should be in a data analyst portfolio

Not sure what to include in your portfolio? Here are a few ideas tips to help set you up for success.

Use visually appealing projects and imagery

One of the most important attributes of your data analyst portfolio is its visual appeal. Data science may not always seem like a discipline packed with intriguing images, but choosing just the right ones can help your audience see and feel the insights you derive from data. And on the job, you'll often have to showcase your work in a visual way.

Consider including some of the following visual elements in your portfolio:

  • Charts
  • Graphs
  • Images representative of people or groups the data represents
  • Images of spaces that coincide with the data in a report, such as factory floors, data centers, or hospital rooms
  • Logos of familiar companies included in your data analysis

Another important facet of your portfolio’s visual appeal is the stylistic layout of any reports or projects inside. When an interviewer is reviewing your portfolio, they may not have time to comb through each paragraph, so it’s best to make it scannable. You might have to restructure work that has already succeeded at accomplishing its objective. You may want to consider incorporating the following elements:

  • Relatively frequent headings that describe what each section discusses
  • Bullet points of the highlights of each section
  • Images, even stock photos, that connect to certain sections
  • Clear, concise topic sentences at the beginnings of paragraphs

These will make it easier for your potential employer to read your data analyst portfolio.

Showcase your best work

When it comes to your portfolio, quality is better than quantity. Include your best work and feel free to leave out anything that doesn’t reflect well on you or your professionalism. Aim to include work that shows you can:

  • Handle a variety of clients and projects
  • Adjust to changing circumstances
  • Make complex concepts easy to digest

Because data analytics plays a key role in so many industries, you don’t have to hyper-focus on one or two business sectors. Rather, it’s best to hone in on having a variety of different applications of data analysis. Here are some good options:

Show off data analysis that boosts sales

Highlight work that directly impacts the sales of a company. For many organizations, sales revenue is the primary driver of income. Therefore, if a company checking out your portfolio sees you have experience in helping an organization boost its bottom line, it may be more likely to secure your services. You may choose to emphasize projects where you:

  • Used historical sales trends to discover challenges and identify opportunities
  • Incorporated demographic data to identify a new market for a product or service
  • Analyzed the performance of individual sales or support people, providing data that could be used for training

Share work that helped improve efficiency

If your portfolio has a project that helped an organization run leaner, cleaner, or greener, include it. Data analysis that reveals ways to enhance efficiency can help a company produce their product or deliver their service for less money or in any way that has a less-drastic impact on the environment. It can also make life easier for the company’s employees, resulting in higher employee retention rates and lower turnover.

Show how you saved a company money

In addition to making a company run more efficiently, data analysis can discover crucial savings opportunities. If you have produced work that saved an organization money, it should be central to your portfolio. If you’re not sure which work to highlight, keep in mind that savings can come from a wide variety of expenditures and operational procedures. Some of these include:

  • Re-organizing or reducing the number of employees
  • Analyzing the cost of goods sold (COGS), then reducing it
  • Examining the costs associated with different marketing channels, isolating the most effective ones, and getting rid of those with the lowest return on investment (ROI)
  • Finding ways to reduce overhead, whether it’s lowering utility expenses, the cost of storage, shipping costs, or others

How do I create a data analyst portfolio?

Aside from figuring out what should be in a data analyst portfolio, explore your options when it comes to creating one. While a hard copy you keep in a portfolio or briefcase never hurts, this can be bulky, expensive, and cumbersome to update. You will want to use a digital portfolio, regardless of how great your physical one looks.

Make your own portfolio

Creating your own portfolio from scratch can help showcase your technical chops, and it'll also offer more customizability than you'd get with a template. In the video below, we'll show you how to build your own portfolio with HTML and CSS.

And if you want to make it interactive, check out Part 2.

Use an online portfolio hosting service

There are several options for hosting your portfolio online, often for free. Some of these sites have ready-to-use templates that can complement your work. Although many portfolio sites are geared towards creative artists, their visual features can make the work of a data scientist or analyst easier to digest.

What are the top 3 skills for data analysts?

Although the job of a data analyst requires several different skills, you should definitely showcase the following top three in your portfolio.

1. Microsoft Excel

Microsoft Excel is a must-have in your arsenal because it is one of the leading spreadsheet applications in the business world. In addition to presenting data, Excel is used to analyze data sets, create charts, and produce graphs for analysis. If a potential employer sees you know your way around Excel, they may feel confident that you know how to organize, execute, and present your analyses.

2. Structured Query Language (SQL)

SQL is a database language, and databases are central to the work of a data analyst. With knowledge of SQL, you can not only read and interpret data in an SQL database, but you can create new databases for processing data in a way that produces tangible value for a company.

3. Critical Thinking

Although it may seem like a challenge to show critical thinking in a portfolio, there are straightforward ways of showing you know how to think critically. Critical thinking involves analyzing a situation by evaluating the different options and creating actionable solutions. By highlighting the problems, steps, discoveries, and solutions your data analysis projects have managed, you can show a prospective employer that you can use critical thinking to advance their organization as well.

A strong data analyst portfolio will help you show employers you have the ability to use data to help them solve problems and explore new opportunities. A visually appealing presentation that underscores the value your analysis can bring to a company can move you to the top of their list.


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Adam Carpenter

Adam Carpenter

Adam Carpenter is a tech, fintech, and business innovations writer. Passionate about user safety, Adam writes about cybersecurity solutions, software, and innovations.

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How To Build a Data Analyst Portfolio (And Why You Need One)
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