Introduction to Cloud Data Analytics with Google BigQuery

Introduction to Cloud Data Analytics with Google BigQuery, available at $39.99, has an average rating of 4.2, with 45 lectures, 4 quizzes, based on 27 reviews, and has 102 subscribers.

You will learn about Data Studio for Analytics and Visualization BigQuery User Interface and Key Features Introduction to Cloud Computing Basics Introduction Data Warehousing Basics Google BigQuery Essentials Loading Datasets to Google BigQuery Multiple Data Importing Techniques in Google BigQuery Google Cloud Storage – Buckets Exporting BigQuery Data in CSV Formats Exporting BigQuery Data to Google Account Data Handling Data Visualisation Data set Report Generation and Sharing This course is ideal for individuals who are Beginners in Data Visualisation, Data Warehousing or Students at their initial stage of learning BigQuery or Students at their initial stage of learning DataStudio It is particularly useful for Beginners in Data Visualisation, Data Warehousing or Students at their initial stage of learning BigQuery or Students at their initial stage of learning DataStudio.

Enroll now: Introduction to Cloud Data Analytics with Google BigQuery

Summary

Title: Introduction to Cloud Data Analytics with Google BigQuery

Price: $39.99

Average Rating: 4.2

Number of Lectures: 45

Number of Quizzes: 4

Number of Published Lectures: 45

Number of Published Quizzes: 4

Number of Curriculum Items: 49

Number of Published Curriculum Objects: 49

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Data Studio for Analytics and Visualization
BigQuery User Interface and Key Features
Introduction to Cloud Computing Basics
Introduction Data Warehousing Basics
Google BigQuery Essentials
Loading Datasets to Google BigQuery
Multiple Data Importing Techniques in Google BigQuery
Google Cloud Storage – Buckets
Exporting BigQuery Data in CSV Formats
Exporting BigQuery Data to Google Account
Data Handling
Data Visualisation
Data set Report Generation and Sharing

Who Should Attend

Beginners in Data Visualisation, Data Warehousing
Students at their initial stage of learning BigQuery
Students at their initial stage of learning DataStudio

Target Audiences

Beginners in Data Visualisation, Data Warehousing
Students at their initial stage of learning BigQuery
Students at their initial stage of learning DataStudio

This course is designed for the students who are at their initial stage or at the beginner level in learning the data warehouse, cloud computing data visualization and Analytics.

This course focuses on what cloud computing is followed by some essential concepts of data warehousing. It also has practical hands-on lab exercises which covers a major portion of big data importing and performing some Analytics on the big data.

The ETL tool used is Google BigQuery and analytics is performed using a visual tool known as data studio. The lab portion covers all the essentials of the two platforms starting from importing the datasets, loading it, performing powerful SQL queries and then analyzing the same data using the visual graphical tools available on DataStudio platform.

Course Curriculum

Chapter 1: Introduction to Cloud Computing

Lecture 1: What is Cloud?

Lecture 2: What is Cloud Computing?

Lecture 3: Cloud Computing Services

Lecture 4: Why Cloud Computing?

Chapter 2: Introduction to Data Warehouse

Lecture 1: How Data Warehouse Works?

Lecture 2: Types of Data Warehouse

Lecture 3: Data Warehouse Architecture

Lecture 4: Data Warehouse Components (Data Model)

Lecture 5: Why to use Data Warehouse?

Chapter 3: Google BigQuery

Lecture 1: Interacting with BigQuery

Lecture 2: BigQuery Architecture

Lecture 3: BigQuery Features

Lecture 4: When to use BigQuery?

Chapter 4: ETL Process

Lecture 1: What is ETL?

Lecture 2: ETL Process in Data Warehouse

Lecture 3: ETL Tools

Chapter 5: Practical Guide to BigQuery

Lecture 1: LAB: Importance of BigQuery

Lecture 2: LAB: Setting Up Account

Lecture 3: LAB: Familiarisation with BQ GUI

Lecture 4: LAB: Creating First Project in BigQuery

Lecture 5: LAB: Loading a CSV File

Lecture 6: LAB: Performing a SQL Query

Lecture 7: LAB: Grouping Data

Lecture 8: LAB: Why Join Data?

Lecture 9: LAB: Importing Multiple Datasets

Lecture 10: LAB: Joining Datasets

Lecture 11: LAB: Google Bucket and Import from Google Bucket

Lecture 12: LAB: MaxMin Profit and ItemType vs. Profit

Lecture 13: LAB: ItemType vs. SalesMedium

Chapter 6: Practical Guide to Google Cloud SDK and BQ CLI Tool

Lecture 1: Overview of Cloud SDK

Lecture 2: LAB: Install and Configure Google Cloud SDK

Lecture 3: LAB: Loading Data to BigQuery using Cloud BQ CLI Tool

Lecture 4: LAB: Performing SQL Query using BQ CLI Tool

Lecture 5: LAB: Interact with Cloud Storage with Gsutil Tool

Chapter 7: Google Data Studio

Lecture 1: LAB: Data Studio Overview

Lecture 2: LAB: Load Data to Data Studio

Lecture 3: LAB: Item Type vs. TotalProfit Data Studio

Lecture 4: LAB: Item Type vs. SalesMedium Data Studio

Lecture 5: LAB: Data Studio Report Motivation

Lecture 6: LAB: Loading and Visualising Data in Data Studio Brief

Lecture 7: LAB: Adding GeoLocation in Data Studio

Lecture 8: LAB: Adding Line Graphs and Control Buttons

Lecture 9: LAB: Report Level Feature and Score Card

Lecture 10: LAB: Add Formulas and Date Ranges

Chapter 8: Capstone Project

Lecture 1: Capstone

Instructors

SKILL CURB
TECHNOLOGY MADE EASY

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2 stars: 0 votes
3 stars: 8 votes
4 stars: 5 votes
5 stars: 14 votes

Frequently Asked Questions

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