[Course 3 of 5, Google Cloud Data Analytics Certificate] Hi learner! Tap into your creativity as we dive into the world of advanced principles of data visualization. You'll explore the benefits and challenges of transforming data in the cloud and the common tools and methods used to collect, process, and store data.

To earn this Google Cloud Certificate with a digital credential you can share, hop on over Google Cloud Skills Boost to complete the hands-on labs (available on desktop/laptop only) and graded assessments. There is a monthly subscription cost of $29 USD/month to earn the certificate on Google Cloud Skills Boost. https://goo.gle/4c7T3GB

Jump directly to the topics you want to learn:
00:00 Introduction to course 3
02:00 Alyx: Data analysts help others learn from data
02:33 Welcome to module 1
03:39 Stages of the data journey
06:17 Steps for effective data collection
08:13 The process stage ensures clean and consistent data
10:39 Manual and automated transformation
13:36 Module 1 Wrap-up

14:15 Welcome to module 2
15:13 Data pipelines in the cloud
18:14 Alyssa: Improve systems by collecting data and asking questions
20:49 The difference between ELT and ETL
24:53 Data ingestion methods that suit your needs
29:03 Data mapping helps ensure consistent data
32:47 Introduction to profiling and cleaning data
35:21 Common ways to manipulate data
38:50 Different approaches to loading data
42:19 Overview of data validation strategies and rules
46:04 Module 2 Wrap-up

47:11 Welcome to module 3
48:23 Challenges of data transformation
52:37 Data aggregation can make it easier to extract meaningful insights
55:56 Consequences of duplicate data and how to eliminate it
59:39 Overview of how joins combine data from different tables
1:03:15 Data derivation to combine data and obtain new insights
1:07:21 Module 3 Wrap-up
1:08:13 Lauren: What makes candidates stand out
1:11:41 Lauren and Ela: Interview role play
1:16:19 Course wrap-up

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