Data Engineering with Google BigQuery & Google Cloud

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Timotius Pamungkas

6:15:27

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1 - Introduction

1 - Welcome to This Course.mp4

00:55

2 - How To Get Maximum Value From This Course.mp4

05:56

3 - Course Structure & Coverage.mp4

02:24

4 - Technology In This Course.mp4

01:55

2 - Introducing Data Warehouse & BigQuery

5 - Data Warehouse.mp4

06:55

6 - Start With BigQuery.mp4

04:46

7 - BigQuery Web User Interface.mp4

03:42

3 - First Exploration

8 - First Data.mp4

04:03

9 - Basic Exploration.mp4

15:56

10 - Functions.mp4

14:04

11 - Common Data Types.mp4

06:50

12 - Different Query.mp4

01:06

13 - Exploring Common Data Types.mp4

25:04

14 - Converting Data Types.mp4

07:09

4 - Data Flow Basic

15 - Data Quality.mp4

05:41

16 - Clean & Transform.mp4

12:46

17 - Store Data.mp4

05:37

18 - Upgrading From Sandbox Account.mp4

00:59

19 - Clean & Transform With Dataprep.mp4

25:21

20 - Scheduled Query.mp4

03:34

21 - Analyze Data.mp4

04:35

22 - Data Visualization.mp4

06:21

5 - Diving Into BigQuery

23 - Essential BigQuery.mp4

14:39

24 - Load Data Into BigQuery Part 1 The Basic.mp4

35:54

25 - Tip Mock Data.mp4

00:57

26 - Load Data Into BigQuery Part 2 Handling Errors.mp4

22:04

27 - Load Data Into BigQuery Part 3 Efficient Load.mp4

13:57

28 - Load Data Into BigQuery Part 4 From Your Data to BigQuery.mp4

22:39

29 - Load Data Into BigQuery Part 5 In Microservice Architecture.mp4

19:41

30 - Tip Message Broker Overview.mp4

07:33

31 - Load Data Into BigQuery Part 6 Recurring Load.mp4

11:44

6 - Virtual Data using View

32 - BigQuery View.mp4

05:45

7 - Data Visualization

33 - What We Will Learn.mp4

01:13

34 - Google Sheets & BigQuery.mp4

10:28

35 - Google Data Studio.mp4

12:30

8 - Intermediate Query

36 - Using Join Theory.mp4

04:00

37 - Using Join Hands On.mp4

16:21

38 - Union & Intersect.mp4

05:57

39 - Basic Statistical Functions.mp4

04:26

9 - Resource & Reference

40 - Resource & Reference for The Course Scripts Links etc.html

41 - Bonus & Other Courses.html

Description

Building data pipeline with BigQuery, Data Studio, and other Google Cloud. Learn basic BigQuery sql & techniques.

What You'll Learn?

Google BigQuery Introduction
Building data pipeline using Google BigQuery from various sources (file, database, API, message broker)
Various techniques & tools for loading data into Google BigQuery
Overview of data cleansing & preparation
Overview of data visualization using Google Sheets & Data Studio

Who is this for?

Software engineers, data analyst, everyone who interested on data engineering

Technical architect that want to know how Google platform can fit into overall data & application architecture

More details

Description
A data warehouse is a repository of historical data that is queried to answer questions, gain insight from data, and make business decisions. BigQuery is Googleâ€™s product for data warehouse. It is designed to store and query terabytes, even petabytes of data without we need to setup and manage any infrastructure. It is not a transactional database for day-to-day operation.
BigQuery supports standard SQL, so if you ever develop with relational database like Oracle, PostgreSQL, MySQL, Microsoft SQL Server, etc, it is easy to familiarize yourself with BigQuery. There are a few BigQuery functions to support modern-day requirements, and learning about them will make your job easier.
There is no infrastructure required. We donâ€™t need to worry about the size of storage, number of processors, or memory allocation for processing query. BigQuery scales automatically to run query, and then release the resource when it is done. We don't even charged for memory or processor allocation.
Google provides sample database for practice and trial.

This course has several topics:
an introduction, where we will see what this course about
what is data warehouse and in which part BigQuery take roles
how we can create a simple data pipeline, including data input, data cleansing, and data visualization
tools and methods that can be used for data engineering, particularly on data ingestion from various sources to BigQuery
data visualization using Google Sheets & Data Studio

This course is for people with basic technical knowledge on SQL.
This course is not basic SQL course, so we will not learn the meaning of basic sql such as SELECT, FROM, WHERE, GROUP BY, ORDER BY
See the preview video Technology in This Course for SQL keyword that we will not discuss on detail
However, we will still learn some of modern SQL syntax that can be used in BigQuery

In this course we will also learn how to fetch data from several sources, so this is a good course if you are an engineer that responsible for creating data pipeline.

Who this course is for:
Software engineers, data analyst, everyone who interested on data engineering
Technical architect that want to know how Google platform can fit into overall data & application architecture

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Timotius Pamungkas came from small Indonesian city but now working on it's capital : Jakarta. He's been in software engineering job for years. His first job was in the large consumer finance in Indonesia. Then he took a role as Engineering Manager on Indonesian unicorn. Few moments after, he moved back to another large Indonesian consumer finance and take a role on Engineering & Architect Head.Taking the role as Head, he get more time to coach his team members about software engineering practice.With more than 5 years experience as Java developer, and for the last few years handle enterprise complexity as Engineering Manager & Enterprise Architect, he will be glad to deliver high quality courses containing information of various technologies and software architecture design skills that he has acquired through his professional experience.His goal is to deliver courses that not only good in theory, but also applicable in real-life use cases. His courses give the concept, and the hand-coding experience. He will also provide various resources, including source code to hands-on coding. Other than his daily job, I also like researching new tech and get his hands into keyboard for writing codes. But he does like share what he learnt. His first teaching experience was back years ago when he was still in the college and teach juniors about algorithm. Some says he is a natural teacher, and he hope that he can share his knowledge by publishing courses into Udemy.

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