Google BigQuery guide for beginners

[LeeAndro]

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 25 lectures (2h 53m) | Size: 980.8 MB

Window analytical functions - SUM OVER (PARTITION BY.

The best way to get you started with data science in Google BigQuery

Understand the concept of BigQuery and how does it stand next to other databases such as MySQL or Postgress

Import your data to BigQuery and Cloud storage, create your table, export data

SQL basics - SELECT, WHERE, ORDER BY, LIKE, JOIN, Date and String functions

SQL aggregation functions - SUM, AVG, COUNT, HAVING and GROUP BY

BigQuery ML to create your own machine learning model easily with SQL, make a series prediction

Visualise your data in Google Data Studio and make your own dashboard

Advanced BigQuery concepts - Partitioning tables, Clustering and Nested Fields

..)

Interest in data or cloud technologies

No specific technical knowledge needed

I designed this class for people that are starting with Google Cloud Platform and BigQuery. I put 5 years of my knowledge into 3 hours of video content where I try to explain all the important concepts of BigQuery.

We will take it through:

Understanding the concept of BigQuery

Import your data into BigQuery and Cloud storage

SQL basics (WHERE, GROUP BY, JOIN TABLES, CASE WHEN)

SQL Date and String functions

SQL BigQuery specific features (Nested fields, Partitioned tables, Clustering)

SQL window analytical functions

BigQuery ML - create easily your machine learning models using SQL

Making a series prediction using BigQuery ML

Visualise data in Data Studio

Export your data into Jupyter Notebook and Python using Google Collaboratory

This course is not supposed to master your SQL skills. Instead, I will take you through SQL basics and uncover to you the potential of BigQuery. In this class, I will take care that you know what BigQuery is, how you can get in and out your data, what are the most interesting features of BigQuery (BigQuery machine learning, Partitioning, Clustering, Nested fields...) and how you can use the advantage of them.

Bner data scientists

Geeks interested in Google Cloud

Web or marketing analysts that want to extend their data skills



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