From Pandas to BI Dashboard via Google BigQuery by Python
This video explain how to upload data from Pandas DataFrame to BigQuery and then retrieve that data from Google BigQuery to a Business Intelligent (BI) dashboard by using Python as backend and SQL for data extraction from a Google Cloud.
So, the pipeline is very simple: Pandas with Python, then send data to Google BigQuery and then setup BI dashboard to retrieve that data by using SQL. That's all.
The content of the video is:
0:04 - Useful videos before starting (to learn more about concat CSV files and how to upload Pandas data to BigQuery via Google API).
0:49 - Starting tutorial.
0:55 - Step 1: Preparing data for project.
1:14 - Step 2: Upload Pandas DataFrame to BigQuery via API by Python.
3:08 - Step 3: Checking SQL commands in BigQuey.
3:57 - Step 4: Setup BigQuery credentials (Service account) for BI Framework.
6:50 - Step 5: Retrieve BigQuery data by using SQL in BI dashboard.
7:41 - Step 6: Create your first dashboard from a data retrieved from BigQuery.
8:31 - Step 7: Add new data to BigQuery and update BI dashboard quickly by SQL.
9:20 - Result: Updated and Old charts in BI dashboard.
Additional videos:
1. Join Multiple CSV Files into one Pandas DataFrame. QUICKLY : • Join Multiple CSV Files into one Pand...
2. Upload Pandas DataFrame to BigQuery and make SQL in Google Cloud Console : • Upload Pandas DataFrame to BigQuery a...
As BI dashboard I used Mode Analytics for this tutorial: https://mode.com
I hope this tutorial will be useful for data analytics and data scientists across the world.
Wishes! Vytautas.