IN THIS ARTICLE
- Data Analytics Portfolio: How Important it is to have one?
- How to Make a Good Data Analytics Portfolio
- Pro Tips for Choosing Data Analytics Projects for the Portfolio
- Learn while Building your own Data Analytics Portfolio
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You’ve decided to get build a career in the data analytics field. But much before you can begin your exciting journey on honing your data analytics skills and push yourself to accomplish things you never thought would be possible, you’ve got to understand an important first step in the career transition process: building a data analytics portfolio while you learn analytic skills on-the-go. Every successful data analyst had to begin with this one essential step. If you want to get a rewarding data analytics job and take your career to the next level, you’re going to need a data analytics portfolio.
A portfolio plays a vital role in not just showcasing your best work but also in establishing a brand for yourself in the analytics industry. It is an entry-ticket to landing desired interview calls from plenty of top tech companies and the secret key for entry into one of the top companies of your dreams.
For beginners in the analytics industry, building a data analytics portfolio is similar to the chicken-and-egg problem. You need a portfolio to land your first data analytics job, but without practical industry experience under your belt, it can be challenging to build a great portfolio of analytics projects to show off.
Whether you’re a beginner or changing career paths, it’s obvious to feel stuck on how to go about creating a slick analytics portfolio. What should a data analytics portfolio contain? What kind of projects gives you the best chance of being accepted by prospective employers? How to present the projects in your portfolio? What follows is a good roadmap on how to go about building an impressive analytics portfolio that will set you up for accomplishing success in your data analytics job search. But, let’s put first things first, let’s understand how important is a data analytics portfolio.
Data Analytics Portfolio: How Important it is to have one?
Let’s put it this way; in the data science and analytics industry where previous experience and PhD is not a strict prerequisite to landing your dream analytics role, a data analytics portfolio plays a vital role and is a lot more important than your resume. A portfolio acts as a meet and greet before the prospective employer actually gets to meet you in person. Your portfolio can mean the difference between getting called for an in-person analytics interview or instant rejection.
With 2020 expected to witness close to 1.5 lakh new data science and analytics job openings(an increase of 62% compared to 2019), and the number of job openings increasing year on year, there are more data analytics professionals in the market. For any data analytics job vacancy, the recruiter gets hundreds of job applications and they’ll likely spend only a few seconds to decide which application makes the cut. A winning data analytics portfolio is a great way to be a part of the select group as it helps you actually show them what data analytics skills you have. Having a data analytics portfolio is the perfect opportunity to showcase your well-rounded set of data analytics skills and differentiate yourself from others to land on that all-important interview stage.
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How to Make a Good Data Analytics Portfolio
Always add Your Contact Details
Showcase Your Best Analytics Projects
Add Data Events you have Attended and Network
Add Previous Employer/Freelance Client Testimonials
Relevant Data Analytics Coursework and Certifications
Seek Feedback and Reiterate
A good data analytics portfolio should show:
- Your ability to find new information in data.
- Your ability to communicate the information succinctly to various stakeholders.
Communication is a key skill for data analytics jobs. Make sure you create a portfolio that is readable for both technical and non-technical people. It is important that a data analytics portfolio clearly articulates the value of a data product or a model that you’ve built to a non-technical person. Here is a quick checklist of items to have in your data analytics portfolio:
1. Always add Your Contact Details
Your data analytics portfolio should make you easily accessible to the employers with an email id and phone number so they can get in touch with you about potential analytics job roles that best suit your skillset.
2. Showcase Your Best Analytics Projects
The general line of a data analyst work involves understanding a business problem, extracting data with SQL, data cleansing, and validation using Python or R, and finally visualising the insights for profitable business decisions. A data analytics portfolio should include modelling-level analytics projects that demonstrate all the data analytics skills required to transform data into actionable insights. A data analytics portfolio is not a place to include every project that you’ve completed. Include only those analytics projects that are relevant to the job position you are applying for and each must be chosen carefully following the guidelines mentioned later in the blog.
3. Add Data Events you have Attended and Network
Make it a point to highlight any note-worthy data events you’ve been a part of like analytics conferences, meetups, webinars, or workshops. Also, mention your learnings from these events and how these helped you add up to your knowledge. Participating in local meetups and other analytics conferences helps you network with fellow data geeks, and land interview calls for some of the hidden analytics job opportunities.
For example, you can participate in some of the top analytics conferences like Cypher2020 , Gartner Data and Analytics Summit, The Machine Conference or participate in local or nearby meetups like data science and analytics meetups that offer a great opportunity for networking with like-minded professionals and also provide some hands-on building sessions on analytics projects
4. Get Social
Include social media handles to add to the employer’s knowledge of you as a professional and begin building confidence with them. For analytics enthusiasts, there are two important social media networks that are non-negotiable: LinkedIn and GitHub. These networks are a prime source where recruiters look for the online footprint of potential candidates. You can also provide a link to your Stack Overflow profile – provided you are an active user and have a good reputation score.
5. Add Previous Employer/Freelance Client Testimonials
Testimonials or reviews from previous employers or any freelance client you’ve worked with are an excellent resource to show prospective employers that they will be similarly satisfied and happy with the analytics projects you create for them. Whether you were featured in an analytics newsletter or an analytics leader you admire tweeted about your ingenious analysis, make it a point to include in your portfolio. Testimonials about your work are proof that you really have the data analytics skills that you claim on your resume.
6. Relevant Data Analytics Coursework and Certifications
This includes any online or offline data analytics courses or even college classes that you’ve taken. Certifications are a powerful add-on on your portfolio as they provide evidence of your data analytics skills.
7. Seek Feedback and Reiterate
Another set of eyes on your data analytics portfolio will help you understand what others found interesting and where they got lost. Iterate on your portfolio by making a note of what resonates and what is unclear. The biggest faux-pas for a data analytics portfolio is for it to stop changing. An analytics portfolio should always be evolving just as your analytics skills, it should always be upgrading and improving to push you forward. A data analytics portfolio is always a work in progress and you can keep adding to it as you learn and improve your skills.
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Pro Tips for Choosing Data Analytics Projects for the Portfolio
A data analytics portfolio is not intended to be a collection of all data analytics projects that you’ve done. Instead, it should showcase your best projects or work that you’ve finished. When considering the projects you want to include in the portfolio, think about:
- Which analytics projects I worked on presented a technical challenge and how I overcame that successfully?
- On which projects did I leverage most of my data analytics skills?
- From which analytics projects did I bring the most value and learned the most?
Answer these questions to refine your final choices of projects for your data analytics portfolio and follow these tips :
- Do not choose analytics projects that tackle common problems, however, that does not mean you have to choose projects that involve fancy modelling. The best portfolio projects for data analytics jobs are more about working with interesting data. Web scraping is one of the best ways to scrape your own interesting data for portfolio projects. A data analyst’s job is to make the data shine and not complicate things too much. For example, you can just take some rap song lyrics dataset and analyse what it takes to make it to the billboard charts.
- Clean vs Messy Dataset: The first step of analysis involves looking into the data and understanding it. It is a good idea to work with clean datasets when you are just getting started. However, if you are to showcase your well-rounded set of analytics skills to the employers you need to play with messy datasets to show you know how to clean and pre-process the data.
- Choosing the right angle for an analytics project is the key to a great data analytics portfolio. Pick a dataset that you are excited to talk about and not something that you think will impress the recruiter. If the dataset interests you, it is easier and fun to find interesting angles with it.
- A data analytics portfolio should have a diverse collection of projects – exploratory data analysis projects, a really intense data cleaning project, a project that uses SQL, and data visualisation and storytelling projects.
- You get bonus points for productionising a data analysis model or a data product you built.
- Include well-structured analytics projects that have modular code, high-performance, and good documentation. The whole process from downloading data to text and visualisations should be easily reproducible.
Learn while Building your own Data Analytics Portfolio
While building a portfolio is much easier with a couple of analytics projects already in place, we must all start somewhere. Always remember, the best way to build an awesome analytics portfolio that will land you a top gig is to acquire in-demand skills. If you wish to level up your analytics skill set or if you feel your analytics portfolio is a little lean, get in touch with our career coaches to hone your skills and get hired as a data analyst.
Springboard’s 1:1 mentoring-led, project-driven Data Analytics Online Program is oriented to the creation of real-life projects and helps you build your own data analytics portfolio while acquiring data analytics skills. The program also provides an official certificate to showcase your analytical skills and validate your achievements with two industry-worthy projects to increase your job prospects while you get guidance and feedback from mentors. Go build some awesome data analytics projects!
Since you’re here…
Interested in a career in data analytics? You will be after scanning this data analytics salary guide. When you’re serious about getting a job, look into our 40-hour Intro to Data Analytics Course for total beginners, or our mentor-led Data Analytics Bootcamp.