Creating a data analytics portfolio, focus on 3 things using DataCamp
- IVAN CHAVEZ
- January 11, 2023
- Blog Post
Who I am and why you should follow this guide to create a data analytics portfolio
Hello, this is Ivan Chavez and I define my professional role as “Data Analytics Delivery Manager”
Having a BSC. Degree in Mechatronics engineering I began my career working as a project management -business- side. As an engineer working in “administrative” stuff, I always feel I need an extra intellectual challenge which could keep me learning. Then I had the chance to work in a Tableau partner Data & Analytics Business Consultant small firm, here discovered the data world and decided I want to keep performing in this path.
Planning, executing, leading & coordinating data team efforts I figured out I have those soft skills which complements pretty well those hard skills introvert engineers are used to be lack off. So, I have decided to focus on being that understanding bridge between business & tech teams.
As delivery manager, I have specialized on making sure business is getting value and tech teams understands what’s the “job-to-be-done”. More a people manager instead of individual contributor. A generalist more than a specialist.
Now, I have the chance to share my knowledge with you so you don’t mess with the same things I have done within the process of understanding the data world.
Please don’t hesitate to check a detailed professional experience at my LinkedIn Profile:
If I have had to start over data, which things would focus on?
I would focus on 3 things:
- Tableau
- Python
- SQL
In that exact order, and the explanation is simple. This is the simplest-lower effort path to begging building portfolio from day 1 and making sure the time you’re spending on learning gets reflected on a potential professional outcome -portfolio-.
Key Concept: Building portfolio basements from an early start while developing those final visual layer delivery for final user skills.
If you want to have a quick track in roles such as: “Tableau Developer” or “Tableau Data Analyst”. This is the learning path you should follow, here’s all the considerations I would take if I had to re-into data.
Tableau Public (free)
I would take Tableau DataCamp training and download Tableau Public and create a profile which can serve as the foundation of my data analytics portfolio.
I would look for videos on YouTube as well as complementary information.
Creating an account on Kaggle to familiarize myself with the platform to learn how to download datasets of my interest.
I would upload all my work to Tableau Public, which would give me the opportunity to learn from my mistakes.
I would focus on creating many dashboards and visualizations, working to master fluency in Tableau. If at that time I were a student of any academic institution, I would apply for a Tableau Desktop license for students.
Having a Tableau license, I would also download “Tableau Prep” and learn the principles of ETL in practice. This way I will be more self-sufficient in the future.
Note: You demonstrate your Tableau skill by having a data analytics portfolio on Public.
Remind: The key is to learn Tableau Basics and begin uploading work, you surely will suck at your first visualizations -Allow yourself to suck-. The good thing about this approach is as far you begin learning intermediate or advanced tableau concepts, you will be able to execute them practically while developing that Tableau Visualization Maker agility.
“Practice make the master”
DataCamp Tableau Resources:
Python on DataCamp and creating Kaggle Projects
I would see this more as a complement, focusing on learning primarily to clean data and connect to sources such as BigQuery from Kaggle. I would learn Python on DataCamp.
Furthermore, I would look to do personal projects where the data cleaning I did using “Prep” I could do only with Python + Notebook.
Likewise, I wouldn’t pay attention to investigating visualization libraries. The truth is that the graphics are horrible and a notebook full of code isn’t something that should be given to a business user, manager, or executive. That’s what Tableau is for.
Note: You demonstrate your Python skill in your Kaggle profile by participating in projects. Create a data analytics portfolio.
DataCamp Python Resources:
SQL with Cloud providers
I would learn SQL with DataCamp as well, and creating an account on Google Cloud Platform to learn how to use BigQuery as the main data storage.
I would leave aside the administrative and server management aspect of databases and look for a more practical approach by learning how to handle this with Cloud providers.
Since my focus is to become a data analyst, I would focus on mastering those functions that allow me to “denormalize” tables, generate aggregates and groupings, because in the end, that analytical modeling is what serves business level.
Note: All DataCamp courses provide you a “digital” you can complement your resume, so you can put those main keywords.
DataCamp SQL Resources:}
Remember:
🎖️ Personal projects in portfolio + Personal brand + Good resume + Credentials = Winning combination 🚀
SQL skills should be invisible at business level, focus on show your skills communicating effectively your data insights.
IVAN CHAVEZ
Hi there! If you’re into the data world like me, then you’re in the right place.
In this website, we’re going to dive into the exciting world of DataOps & Analytics. From the latest trends and innovations to practical tips and tricks, I got everything you need to stay on top of the game.
So grab a cup of coffee (or your beverage of choice), get comfortable, and let’s get started!