Serverless Data Analysis with Big Query on Google's Cloud
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Serverless Data Analysis with Big Query on Google's Cloud

The Third Course in a Series for Attaining the Google Certified Data Engineer
3.7 (3 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
23 students enrolled
Created by Mike West
Last updated 7/2017
English
Current price: $10 Original price: $25 Discount: 60% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 1 hour on-demand video
  • 7 Articles
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • At the end of this course you'll understand serverless data analysis and architecture.
  • At the end of this course you'll be one third of the way there, course wise, in preparing for the Google Certified Data Engineering Exam.
  • You'll be able to import data sets and use SQL to explore them with BigQuery.
  • When you've completed the course you'll be able to explain in detail why BigQuery is the fastest data warehouse in the world.
View Curriculum
Requirements
  • You should have taken the first two courses in the series for attaining the Google Certified Data Engineer.
  • You should be very comfortable with SQL. (any flavor)
  • It will be very helpful if you come from a data background.
Description

Welcome to Serverless Data Analysis with Big Query on Google's Cloud This is the second course in a series of courses designed to help you attain the coveted Google Certified Data Engineer. 

Additionally, the series of courses is going to show you the role of the data engineer on the Google Cloud Platform

At this juncture the Google Certified Data Engineer is the only real world certification for data and machine learning engineers.

Note: This is not a programmers course on BigQuery. The goal of this course and the entire series of courses is to provide students with the foundation of the services you'll need to know for the Google Certified Data Engineering Exam. 

Because SQL is a prerequisite for the course this course is mostly lecture. Don't let that lull to sleep though, this service is heavily covered on the exam

BigQuery is Google's fully managed, petabyte scale, low cost enterprise data warehouse for analytics. BigQuery is serverless. There is no infrastructure to manage and you don't need a database administrator, so you can focus on analyzing data to find meaningful insights using familiar SQL. 

We are in a data revolution. Data used to be viewed as a simple necessity and lower on the totem pole. Now it is more widely recognized as the source of truth. As we move into more complex systems of data management, the role of the data engineer becomes extremely important as a bridge between the DBA, developer and the data consumer. Beyond the ubiquitous spreadsheet, graduating from RDBMS (which will always have a place in the data stack), we now work with NoSQL and Big Data technologies.

Most cloud computing vendors are moving to a serverless architecture. What's serverless?  Serverless is about abstracting users away from servers, infrastructure, and having to deal with low-level configuration or the core operating system. Instead, developers make use of single purpose services to execute code.

Imagine for a second being able to upload data into a storage bucket and then run SQL like queries against it. Many data analysts call this the grail to data analysis. With BigQuery, that's exactly what you do. There's no spinning up or configuring anything. You upload data in the form of a csv or json file and an query against it. I don't mean a hundred thousand rows. I mean a billion. 

                                                           *Five Reasons to take this Course.*

1) You Want to be a Data Engineer 

It's the number one job in the world. (not just within the computer space) The growth potential career wise is second to none. You want the freedom to move anywhere you'd like. You want to be compensated for your efforts. You want to be able to work remotely. The list of benefits goes on. 

2) The Google Certified Data Engineer 

Google is always ahead of the game. If you were to look back at at timeline of their accomplishments in the data space you might believe they have a crystal ball. They've been a decade ahead of everyone.  Now, they are the first and the only cloud vendor to have a data engineering certification. With their track record I'll go with Google. 

3) The Growth of Data is Insane 

Ninety percent of all the world's data has been created in the last two years. Business around the world generate approximately 450 billions transactions a day. The amount of data collected by all organizations is approximately 2.5 Exabytes a day. That number doubles every month. 

4) The Data Revolution is Here

We are in a data revolution. Data used to be viewed as a simple necessity and lower on the totem pole. Now it is more widely recognized as the source of truth. As we move into more complex systems of data management, the role of the data engineer becomes extremely important as a bridge between the DBA and the data consumer.

5) You want to be ahead of the Curve 

The data engineer role is fairly new.  While your learning, building your skills and becoming certified you are also the first to be part of this burgeoning field.  You know that the first to be certified means the first to be hired and first to receive the top compensation package. 

Thank you for your interest in Serverless Data Analysis with Big Query on Google's Cloud and we will see you in the course!!

Who is the target audience?
  • If you following along and are ready to tackle the third course in this series then this course is for you.
  • You want to be a Google Certified Data Engineer.
  • You need to know how to use BigQuery.
Students Who Viewed This Course Also Viewed
Curriculum For This Course
42 Lectures
01:13:43
+
Introduction
6 Lectures 11:07

In this lesson let's high level what this course is about. 

This is the same video as the course preview. 

Preview 01:33

Let's talk about what you are going to learn in the course. 

This course is all about one cloud service in Google's cloud called BigQuery. 

Preview 02:11

In this lesson I'll try to answer some questions that are specific about the course. 

Preview 01:38

In this lesson let's define the data engineer. 

What do they do all day? 

How can you become one? 

Preview 03:13

Serverless simply means that the hardware is abstracted away from us. 

With BigQuery, this means all we do is log into the console, upload some data and write a SQL query. 

There's no hardware we have to configure. 

Preview 02:10

Summary
00:22

Quiz
5 questions
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BigQuery Overivew
10 Lectures 13:50

What prompted Google to create BigQuery? 

Let's learn the why in this lesson. 

Why BigQuery?
01:03

BigQuery uses SQL. 

Let's discuss SQL in this lesson. 

SQL on BigQuery
01:52

Data in BigQuery is not stored in rows but in columns. 

Let's take a look at columnar storage. 

Columnar Storage
00:46

BigQuery is a structured data store. 

Let's talk about that structure in this lesson. 

Structured Data Storage
02:02

There are three core approaches to loading data into BigQuery. 

Let's learn about them in this lesson. 

Getting Data into BigQuery
01:52

BigQuery isn't a scaled up architecture. 

It's a scaled out architecture. 

Let's learn about scale in this lesson. 

Massively Parallel
01:23

BigQuery uses a global namespace. 

Let's learn what that is in this lesson. 

Global Namespace
00:58

Jobs in BigQuery run asynchronously. 

Let's learn about job basics in this lesson. 

Asynchronous Job Manager
01:10

In this lesson let's learn what BigQuery is not. 

What BigQuery Isn't
01:34

Summary
01:10

Quiz
10 questions
+
BigQuery Basics
12 Lectures 18:36

If you haven't taken the introductory course on Google's Cloud there will be knowledge gaps. 

This lesson reinforces the importance of taking the courses in order. 

Section Assumptions
00:24

This brief lesson will help define BigQuery visually. 

We always need to keep in mind that in GCP everything is created within the confines of a project. 

BigQuery Abstraction Model
01:02

The graphical user interface for BigQuery is a Web interface. 

Let's cover the very basics in this lesson. 

Query Editor Overview
02:06

Let's learn how to execute and save a query in this lesson. 

Running and Saving Our Queries
02:17

As the query author you decide who receives access to it. 

In this lesson let's show you have to gran access to users on a project. 

Query Visibility
01:40

In this lesson let's upload a dataset from our computer. 

Upload Customer Dataset
02:31

In this lesson let's learn the hierarchy naming convention for Queries in BigQuery. 

Naming Conventions
01:55

In this short lesson let's learn how to export data via the cloud shell. 

It's very straightforward. 

Export Data with Cloud Shell
01:18

In this lesson let's learn how pricing in BigQuery works. 

3 Categories of BigQuery Pricing
01:41

In this lesson let's learn about data durability specific to BigQuery. 

BigQuery Data Durability
02:04

You can rent your won dremel clusters. 

Let's find out exactly what that means in this lesson. 

Reserved Capacity
01:08

Summary
00:30

Quiz
5 questions
+
Queries on BigQuery
8 Lectures 16:51

In this lesson let's learn the basic structure of a BigQuery query. 

Simple Query
01:42

In this lesson let's learn about the anatomy of a BigQuery Query. 

We will step line be line through the code. 

Query Anatomy
04:00

In this lesson let's learn how craft a simple join in BigQuery. 

Simple Join
03:27

In this lesson let's cover the basics of the inner join in BigQuery. 

Inner Join
01:11

In this lesson let's learn how to us order and group by in BigQuery. 

Aggregations
02:39

In this lesson let's the learn the basics of the subquery in BigQuery. 

Subqueries
00:56

We can easily join tables in BigQuery. 

In this lesson let's learn how to do that. 

Cross Table Field Joins
02:21

Summary
00:35

Quiz
5 questions
+
Advanced Features
6 Lectures 12:57

In this lesson let's walk through a more advanced subquery. 

Advanced Subquery
02:28

Instead of using LIKE let's take a look at CONTAINS in BigQuery is this brief lesson. 

Using Contains
01:26

Used infrequently but power never the less, let's learn about windowing functions in this lesson. 

Windowing Functions
04:17

The typical GROUP BY clause with a slight twist. 

Let's learn about the EACH keyword in this lesson. 

GROUP EACH BY
02:30

This is quite different than traditional SQL. 

Let's learn about this clause in this lesson. 

COUNT DISTINCT Behavior
01:54

Summary
00:22
About the Instructor
Mike West
4.1 Average rating
2,597 Reviews
42,853 Students
40 Courses
SQL Server and Machine Learning Evangelist

I've been a production SQL Server DBA most of my career.

I've worked with databases for over two decades. I've worked for or consulted with over 50 different companies as a full time employee or consultant. Fortune 500 as well as several small to mid-size companies. Some include: Georgia Pacific, SunTrust, Reed Construction Data, Building Systems Design, NetCertainty, The Home Shopping Network, SwingVote, Atlanta Gas and Light and Northrup Grumman.

Experience, education and passion

I learn something almost every day. I work with insanely smart people. I'm a voracious learner of all things SQL Server and I'm passionate about sharing what I've learned. My area of concentration is performance tuning. SQL Server is like an exotic sports car, it will run just fine in anyone's hands but put it in the hands of skilled tuner and it will perform like a race car.

Certifications

Certifications are like college degrees, they are a great starting points to begin learning. I'm a Microsoft Certified Database Administrator (MCDBA), Microsoft Certified System Engineer (MCSE) and Microsoft Certified Trainer (MCT).

Personal

Born in Ohio, raised and educated in Pennsylvania, I currently reside in Atlanta with my wife and two children.