From Pandas to BI Dashboard via Google BigQuery by Python

Published: 13 November 2019
on channel: Data Science Garage
1,280
23

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.


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