Google BigQuery PostgreSQL Big Query for Data Analysis

Become BigQuery expert by mastering Google BigQuery for data analysis. Cover all SQL qureies in PostgeSQL & Big Query
Google BigQuery PostgreSQL Big Query for Data Analysis
File Size :
3.87 GB
Total length :
11h 31m



Start-Tech Academy


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Google BigQuery PostgreSQL Big Query for Data Analysis

What you’ll learn

Knowledge of all the essential SQL commands in BigQuery and PostgreSQL
Become proficient in SQL tools like GROUP BY, JOINS and Subqueries
Become competent in using sorting and filtering commands in SQL

Google BigQuery PostgreSQL Big Query for Data Analysis


Just a PC with any web browser


6 Reasons why you should choose this PostgreSQL and BigQuery courseCarefully designed curriculum teaching you everything in SQL and Google BigQuery that you will need for Data analysis in businessesComprehensive – covers basic and advanced SQL statements in both PostgreSQL and Google BigQueryBusiness related examples and case studies on SQL and Google BigQueryAmple practice exercises on Google BigQuery because SQL and Google BigQuery require practiceDownloadable resources on SQL and Google BigQueryYour queries will be responded by the Instructor himselfA Verifiable Certificate of Completion is presented to all students who undertake this SQL and Google BigQuery course.Why should you choose this course?This is a complete tutorial on Google BigQuery and PostgreSQL which can be completed within a weekend. SQL is the most sought-after skill for Data analysis roles in all the companies. Google BigQuery is also in high demand in data analysis field. So whether you want to start a career as a data scientist or just grow you data analysis skills, or just want to learn Google BigQuery this course will cover everything you need to know to do that.What makes us qualified to teach you?The course is taught by Abhishek and Pukhraj. Instructors of the course have been teaching Data Science and Machine Learning for over a decade. We have experience in teaching and using Google BigQuery and PostgreSQL for data analysis purposes.We are also the creators of some of the most popular online courses – with over 400,000 students and thousands of 5-star reviews like these ones:I had an awesome moment taking this course. It broaden my knowledge more on the power use of SQL as an analytical tools. Kudos to the instructor! – SikiruVery insightful, learning very nifty tricks and enough detail to make it stick in your mind. – ArmandOur PromiseTeaching our students is our job and we are committed to it. If you have any questions about the course content, Google BigQuery, PostgreSQL, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.Download Practice files, take Quizzes, and complete AssignmentsWith each lecture, there is a practice sheet attached for you to follow along. You can also take quizzes to check your understanding of concepts on Google BigQuery and PostgreSQL. Each section contains a practice assignment for you to practically implement your learning on Google BigQuery and PostgreSQL. Solution to Assignment is also shared so that you can review your performance.By the end of this course, your confidence in using Google BigQuery and PostgreSQL will soar. You’ll have a thorough understanding of how to use Google BigQuery and PostgreSQL for Data analytics as a career opportunity.Go ahead and click the enroll button, and I’ll see you in lesson 1 of this Google BigQuery and PostgreSQL course.CheersStart-Tech AcademyFAQ’sWhy learn SQL?SQL is the most universal and common used database language.It powers the most commonly used database engines like PostgreSQL, SQL Server, SQLite, and MySQL. Simply put,If you want to access databases then yes, you need to know SQL.It is not really difficult to learn SQL. SQL is not a programming language, it’s a query language. The primary objective where SQL was created was to give the possibility to common people get interested data from database. It is also an English like language so anyone who can use English at a basic level can write SQL query easily.SQL is one of the most sought-after skills by hiring employers.You can earn good moneyHow much time does it take to learn SQL?SQL is easy but no one can determine the learning time it takes. It totally depends on you. The method we adopted to help you learn SQL quickly starts from the basics and takes you to advanced level within hours. You can follow the same, but remember you can learn nothing without practicing it. Practice is the only way to learn SQL quickly.What are the steps I should follow to learn SQL?Start learning from the basics of SQL. The first 10 sections of the course cover the basics.Once done with the basics, try your hands on advanced SQL. Next 10 sections cover Advanced topicsPractice your learning on the exercise provided in every section.What’s the difference between SQL and PostgreSQL?SQL is a language. Specifically, the “Structured Query Language”PostgreSQL is one of several database systems, or RDMS (Relational Database Management System). PostgresSQL is one of several RDMS’s, others of which are Oracle, Informix, MySQL, and MSQL.All of these RDMSs use SQL as their language. Each of them have minor variations in the “dialect” of SQL that they use, but it’s all still SQL.What is BigQuery used for?BigQuery is a web service from Google that is used for handling or analyzing big data. Google BigQuery is part of the Google Cloud Platform. As a NoOps (no operations) data analytics service, Google BigQuery offers users the ability to manage data using fast SQL-like queries for real-time analysis.Is BigQuery free?For users of Google BigQuery the first 10GB of storage per month is free and the first 1TB of query per month is free. Post these limits, Google BigQuery is chargeable.Which is better, PostgreSQL or MySQL?Both are excellent products with unique strengths, and the choice is often a matter of personal preference.PostgreSQL offers overall features for traditional database applications, while MySQL focuses on faster performance for Web-based applications.Open source development will bring more features to subsequent releases of both databases.Who uses these databases?Here are a few examples of companies that use PostgreSQL: Apple, BioPharm, Etsy, IMDB, Macworld, Debian, Fujitsu, Red Hat, Sun Microsystem, Cisco, Skype.Google BigQuery is used by companies such as Spotify, The New York Times, Stack Etc.


Section 1: Introduction

Lecture 1 Welcome to the Course

Lecture 2 Course Flow

Section 2: Installation and getting started

Lecture 3 Course Resources

Lecture 4 This is a milestone!

Lecture 5 Installing PostgreSQL and pgAdmin in your PC

Lecture 6 If pgAdmin is not opening…

Lecture 7 Setting up BigQuery on Google Cloud Platform

Lecture 8 BigQuery Interface

Section 3: Fundamental SQL statements

Lecture 9 CREATE

Lecture 10 CREATE in BigQuery

Lecture 11 Exercise 1: Create DB and Table

Lecture 12 INSERT

Lecture 13 INSERT in BigQuery

Lecture 14 Import data from File

Lecture 15 Importing data from File using BigQuery Web User Interface

Lecture 16 File Upload in Google Big Query through Google cloud sdk

Lecture 17 Importing data from Google Drive

Lecture 18 Exercise 2: Inserting and Importing

Lecture 19 SELECT

Lecture 20 SELECT in BigQuery


Lecture 22 SELECT DISTINCT in BigQuery

Lecture 23 WHERE

Lecture 24 WHERE in BigQuery

Lecture 25 Logical Operators – AND, OR, NOT

Lecture 26 Logical Operators in BigQuery

Lecture 27 Exercise 3: SELECT & WHERE

Lecture 28 UPDATE

Lecture 29 UPDATE in BigQuery

Lecture 30 DELETE

Lecture 31 DELETE in BigQuery

Lecture 32 ALTER

Lecture 33 ALTER in BigQuery

Lecture 34 Exercise 4: Updating Table

Section 4: Restore and Back-up

Lecture 35 Restore and Back-up

Lecture 36 Debugging Restoration

Lecture 37 Creating DB using CSV files

Lecture 38 Data Set creation in BigQuery

Lecture 39 Exercise 5: Restore and Back-up

Section 5: Selection commands: Filtering

Lecture 40 IN

Lecture 41 IN in BigQuery

Lecture 42 BETWEEN

Lecture 43 BETWEEN in BigQuery

Lecture 44 LIKE

Lecture 45 LIKE in BigQuery

Lecture 46 Exercise 6: In, Like & Between

Section 6: Selection commands: Ordering

Lecture 47 ORDER BY

Lecture 48 ORDER BY in BigQuery

Lecture 49 LIMIT

Lecture 50 LIMIT in BigQuery

Lecture 51 Exercise 7: Sorting

Section 7: Alias

Lecture 52 AS

Lecture 53 AS in BigQuery

Section 8: Aggregate Commands

Lecture 54 COUNT

Lecture 55 COUNT in BigQuery

Lecture 56 SUM

Lecture 57 SUM in BigQuery

Lecture 58 AVERAGE

Lecture 59 AVERAGE in BigQuery

Lecture 60 MIN MAX

Lecture 61 MIN MAX in BigQuery

Lecture 62 Exercise 8: Aggregate functions

Section 9: Group By Commands

Lecture 63 GROUP BY

Lecture 64 GROUP BY in BigQuery

Lecture 65 HAVING

Lecture 66 HAVING in BigQuery

Lecture 67 Exercise 9: Group By

Section 10: Conditional Statement

Lecture 68 CASE WHEN

Lecture 69 CASE WHEN in BigQuery

Section 11: JOINS

Lecture 70 Introduction to Joins

Lecture 71 Concepts of Joining and Combining Data

Lecture 72 Preparing the data

Lecture 73 Creating Datasets for Joins in BigQuery

Lecture 74 Inner Join

Lecture 75 INNER JOIN in BigQuery

Lecture 76 Left Join

Lecture 77 LEFT JOIN in BigQuery

Lecture 78 Right Join

Lecture 79 RIGHT JOIN in BigQuery

Lecture 80 Full Outer Join

Lecture 81 FULL OUTER JOIN in BigQuery

Lecture 82 Cross Join

Lecture 83 CROSS JOIN in BigQuery

Lecture 84 Intersect and Intersect ALL

Lecture 85 Except

Lecture 86 EXCEPT in BigQuery

Lecture 87 Union

Lecture 88 UNION in BigQuery

Lecture 89 Exercise 10: Joins

Section 12: SUBQUERIES

Lecture 90 Subqueries

Lecture 91 Subqueries in BigQuery

Lecture 92 Exercise 11: Subqueries

Section 13: Views and Indexes

Lecture 93 Views

Lecture 94 Views in BigQuery

Lecture 95 Index

Lecture 96 Index in BigQuery

Lecture 97 Exercise 12: Views

Section 14: String Functions

Lecture 98 LENGTH

Lecture 99 LENGTH in BigQuery

Lecture 100 UPPER LOWER

Lecture 101 Changing Case in BigQuery

Lecture 102 REPLACE

Lecture 103 REPLACE in BigQuery

Lecture 104 TRIM, LTRIM, RTRIM

Lecture 105 TRIM, LTRIM, RTRIM in BigQuery


Lecture 107 CONCATENATION in BigQuery

Lecture 108 SUBSTRING

Lecture 109 SUBSTRING



Lecture 112 Exercise 13: String Functions

Section 15: Mathematical Functions

Lecture 113 CEIL & FLOOR

Lecture 114 CEIL & FLOOR in BigQuery

Lecture 115 RANDOM

Lecture 116 RANDOM in BigQuery

Lecture 117 SETSEED

Lecture 118 SETSEED in BigQuery

Lecture 119 ROUND

Lecture 120 POWER

Lecture 121 POWER in BigQuery

Lecture 122 Exercise 14: Mathematical Functions

Section 16: Date-Time Functions


Lecture 124 CURRENT DATE & TIME in BigQuery

Lecture 125 AGE

Lecture 126 AGE in BigQuery

Lecture 127 EXTRACT

Lecture 128 EXTRACT in BigQuery

Lecture 129 Exercise 15: Date-time functions




Lecture 132 PATTERN MATCHING in BigQuery

Lecture 133 Exercise 16: Pattern Matching

Section 18: Google Data Studio for visualizing BigQuery Data

Lecture 134 Google Data Studio for visualizing BigQuery Data

Lecture 135 Showcasing SQL Skills with HackerRank Stars

Lecture 136 The final milestone!

Section 19: Congratulations & about your certificate

Lecture 137 Bonus Lecture

Working Professionals beginning their Data journey,Anyone curious to master SQL from beginner to Advanced in short span of time

Course Information:

Udemy | English | 11h 31m | 3.87 GB
Created by: Start-Tech Academy

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