Become BigQuery expert by mastering Google BigQuery for data analysis. Cover all SQL qureies in PostgeSQL & Big Query.
This course includes:
- 11 hours on-demand video
- 3 articles
- 3 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of completion
6 Reasons why you should choose this PostgreSQL and BigQuery course
- Carefully designed curriculum teaching you everything in SQL and Google BigQuery that you will need for Data analysis in businesses
- Comprehensive – covers basic and advanced SQL statements in both PostgreSQL and Google BigQuery
- Business related examples and case studies on SQL and Google BigQuery
- Ample practice exercises on Google BigQuery because SQL and Google BigQuery require practice
- Downloadable resources on SQL and Google BigQuery
- Your queries will be responded by the Instructor himself
A 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! – Sikiru
Very insightful, learning very nifty tricks and enough detail to make it stick in your mind. – Armand
Teaching 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 Assignments
With 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.
Why 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 money
How 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 topics
- Practice 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.