Modernizing Data Lakes and Data Warehouses with GCP

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Google Cloud

3:34:35

9 View

01 - Introduction

01 - Course Introduction.mp4

01:48

02 - Getting started with GCP and Qwiklabs.mp4

03:48

02 - Introduction to Data Engineering

03 - Explore the role of a data engineer.mp4

06:59

04 - Analyze data engineering challenges.mp4

08:59

05 - Intro to BigQuery.mp4

03:22

06 - Data Lakes and Data Warehouses.mp4

05:59

07 - Demo -Federated Queries with BigQuery.mp4

06:50

08 - Transactional Databases vs Data Warehouses.mp4

04:53

09 - Partner effectively with other data teams.mp4

06:21

10 - Manage data access and governance.mp4

02:12

11 - Demo -Finding PII in your dataset with DLP API.mp4

01:57

12 - Build production-ready pipelines.mp4

02:08

13 - Review GCP customer case study.mp4

03:55

14 - Recap.mp4

01:24

15 - Lab Intro -Using BigQuery to do Analysis.mp4

00:17

16 - Using BigQuery to do Analysis.mp4

00:10

03 - Building a Data Lake

17 - Introduction to Data Lakes.mp4

10:51

18 - Data Storage and ETL options on GCP.mp4

04:54

19 - Building a Data Lake using Cloud Storage.mp4

10:36

20 - Demo -Optimizing cost with Google Cloud Storage classes and Cloud Functions.mp4

07:11

21 - Securing Cloud Storage.mp4

05:50

22 - Storing All Sorts of Data Types.mp4

05:00

23 - Demo -Running federated queries on Parquet and ORC files in BigQuery.mp4

04:20

24 - Storing Relational Data in the Cloud.mp4

01:16

25 - Cloud SQL as a relational Data Lake.mp4

07:38

26 - Lab -Loading Taxi Data into Cloud SQL.mp4

00:27

27 - Loading Taxi Data into Google Cloud SQL.mp4

00:10

04 - Building a data warehouse

28 - The Modern Data Warehouse.mp4

03:35

29 - Intro to BigQuery.mp4

01:04

30 - Demo -Querying TB of Data in seconds.mp4

07:05

31 - Getting Started.mp4

09:14

32 - Loading Data.mp4

11:04

33 - Lab Intro -Loading Data into BigQuery.mp4

00:21

34 - Loading data into BigQuery.mp4

00:10

35 - Exploring Schemas.mp4

00:24

36 - Demo -Exploring Schemas.mp4

10:25

37 - Schema Design.mp4

03:08

38 - Nested and Repeated Fields.mp4

08:05

39 - Demo -Nested and Repeated Fields.mp4

15:36

40 - Lab Intro -Working with JSON and Array Data in BigQuery.mp4

00:13

41 - Working with JSON and Array data in BigQuery.mp4

00:10

42 - Optimizing with Partitioning and Clustering.mp4

05:11

43 - Demo -Creating Partitioned Tables.mp4

07:25

44 - Demo -Partitioning and Clustering.mp4

06:04

45 - Preview -Transforming Batch and Streaming Data.mp4

02:47

46 - Recap.mp4

01:31

05 - Summary

47 - Course Summary.mp4

01:48

Description

What You'll Learn?

The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud Platform in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.

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Data Science

Big Data

Data Warehouse

Google Cloud

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Google Cloud can help solve your toughest problems and grow your business. With Google Cloud, their infrastructure is your infrastructure. Their tools are your tools. And their innovations are your innovations.

Pluralsight

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.