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
Requirements
Just a PC with any web browser
Description
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.
Overview
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 21 SELECT DISTINCT
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 106 CONCATENATION
Lecture 107 CONCATENATION in BigQuery
Lecture 108 SUBSTRING
Lecture 109 SUBSTRING
Lecture 110 LIST AGGREGATION
Lecture 111 LIST AGGREGATION
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 123 CURRENT DATE & TIME
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
Section 17: PATTERN (STRING) MATCHING
Lecture 130 PATTERN MATCHING BASICS
Lecture 131 ADVANCE PATTERN MATCHING (REGULAR EXPRESSIONS)
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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