Data Engineering with Snowflake and AWS

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Cassio Alessandro de Bolba

4:23:37

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1 - 1 Introduction

1 - 11 Introduction Check this before starting.html

2 - 12 What is a Modern Data Platform.mp4

12:12

3 - 13 Introduction to Snowflake.mp4

12:32

4 - 14 Snowflake Architecture.mp4

09:40

5 - 15 Costs.mp4

09:33

6 - 16 Instance Types.mp4

05:41

2 - 2 Understanding the Snowflake Environment

7 - 21 Creating a free Account.mp4

06:45

8 - 22 Exploring the Menus.mp4

11:57

9 - 23 Exploring Worksheets.mp4

11:21

10 - 24 Snowflake Clusters Virtual Warehouses.mp4

14:00

11 - 25 Default Roles.mp4

10:08

3 - 3 Data Ingestion 1 COPY command

12 - 30 Snowflake Ingestion Methods.mp4

10:02

13 - 31 Open Data for Ingestion.mp4

07:07

14 - 32 Stage Types.mp4

07:39

15 - 33 Configuring an External Stage.mp4

09:42

16 - 34 Ingesting Data to Snowflake.mp4

13:21

17 - 35 File Formats.mp4

06:55

18 - 36 Using FLATTEN command.mp4

10:25

4 - 4 Integrate AWS and Snowflake

19 - 41 Creating the Storage Integration.mp4

12:41

20 - 42 Loading JSON to Snowflake.mp4

12:00

21 - 43 SemiStructured Data 1.mp4

07:37

22 - 44 SemiStructured Data 2.mp4

08:42

23 - 45 Code Versioning.mp4

04:11

24 - 46 SemiStructured Data 3.mp4

09:36

25 - 47 Inserting Data into a Table.mp4

08:42

5 - 5 Data Ingestion 2 SNOWPIPE Microbatches

26 - 51 Ingesting with SNOWPIPE.mp4

03:03

27 - 52 Creating a PIPE.mp4

08:28

28 - 53 Configuring SQS and Testing the PIPE.mp4

08:26

29 - 54 How to check Erros in PIPES.mp4

11:11

Description

Deploy a production ready pipeline to ingest data from Snowflake to AWS

What You'll Learn?

Tasks of a Data Engineer in Snowflake
How Snowflake platform can support engineers
Some custom SQL Snowflake code
Extraction, Transformation and Data Loading
What you need in AWS to integrate Snowflake
ETL
Create Amazon S3, IAM Role and Policies, SNS topics

Who is this for?

Data Engineers

Data Analysts

Database Administrators

Analytics Engineers

Cloud Engineers

Software Engineers

Database Developers

Python Developers

Data Managers

Data Leaders

What You Need to Know?

Familiarity with SQL is recommended but not mandatory

Familiarity with AWS is recommended but not mandatory

More details

Description
Snowflake course for data engineers
This comprehensive Snowflake course is designed for data engineers who want to improve their ability to efficiently and scalably manage data in the cloud. With a hands-on focus, participants will be guided from the basics to advanced concepts of the Snowflake platform, which provides a modern and fully managed data warehouse architecture.

Benefits of using Snowflake for data engineering:
Elastic scalability: one of the key benefits of Snowflake is its cloud data storage architecture, which allows for elastic scalability. This means that data engineers can easily scale resources on demand to efficiently handle variable workloads and ensure consistent performance regardless of data volume.
Simplified data sharing: Snowflake offers a unique approach to sharing data across departments and teams. Using the concept of secure and controlled data sharing, data engineers can create a single data source that promotes efficient collaboration and consistent data analysis across the organisation.
Seamless integration with analytics tools: Snowflake is designed to integrate seamlessly with a variety of data analytics tools, allowing data engineers to create complete ecosystems for advanced data analysis. Compatibility with standard SQL makes it easy to migrate to the platform, while interoperability with popular tools such as Tableau and Power BI expands options for data visualisation and exploration.

In this course we deal with:
Snowflake basics
Platform architecture
Virtual warehouses - the clusters
Working with semi-structured data
Integrating Snowflake with AWS
Using Stages, Storage Integration, and Snowpipes
Using AWS S3, SQS, IAM
Automatic ingestion of data in near real time
Who this course is for:
Data Engineers
Data Analysts
Database Administrators
Analytics Engineers
Cloud Engineers
Software Engineers
Database Developers
Python Developers
Data Managers
Data Leaders

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I'm self taught Senior Data Engineer and content creator. Migrated from a machine operator at my 30's to the Data IT Industry. Can help early professionals to drive their path to become data professionals as well as give some great advices for those who wish to live abroad and achieve a sponsorship visa.My current stack:Data Integration / Processing -> Databricks | Dataflow | AWS Lambdas | Datafusion | DataFactoryAutomation -> Power Platform | Power Automate | Power AppsDatabases -> Snowflake | Big Query | SQL ServerData Transformation -> DBTVersioning / Repository -> Git | Azure DevOpsProgramming -> SQL | Python | PySparkCloud Providers -> Azure | GCP | AWS Task / Data Orchestration -> AirflowBI -> Power BI | Qlik Sense CI / CD -> Git Lab CIContainers -> Docker

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