Building your Data Analyst/Scientist Portfolio

Building your Data Analyst/Scientist SQL portfolio - Google Cloud edition
First, you will start by creating a @googlecloud account, then find a public dataset on BigQuery. You can use Google BigQuery to write SQL statements to pull the data then next, create a GitHub repo & add your SQL queries

Ensure you take screenshots of your queries, then analyze the data in Excel or any BI tool. Do a write-up explaining your process with screenshots doing this will prove your experience in SQL, GCP, GitHub & Excel/BI tools.

BigQuery Project and How to Access Public Datasets.

To access public datasets on Google BigQuery, here’s the doc. It’s really straightforward. If you’re not good with docs or refer to YouTube has excellent videos on the topic. 
cloud.google.com
BigQuery public datasets | Google Cloud



Examples of datasets done by Jessica Ayodele. Here she highlighted how to add your datasets to your MySQL database & write your queries. Also, BigQuery is a data warehouse with an engine to process SQL queries. Syntax is similar. It doesn’t take much to get around how to use it. towardsdatascience.com
Analysis of New York City Motor Vehicles Collisions
A Data Analyst Interview Case Study using Google BigQuery & Tableau



BigQuery uses similar SQL syntax as you’d have in MySQL, PostgreSQL. The only change is the environment, you’re still writing a similar SQL query. 

References

[1] BULB, 'Write to Earn. Read to Earn' (online, 2022) <https://www.bulbapp.io/>