Snowflake - Build and Architect Data Pipelines Using AWS: Data engineering and architecting pipelines using Snowflake and AWS cloud

Siddharth Raghunath

$69.99

5 (1 Ratings)

Video May 2023 8hrs 39mins 1st Edition

Siddharth Raghunath

$69.99

5 (1 Ratings)

Video May 2023 8hrs 39mins 1st Edition

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Key benefits

Learn from an easy-to-understand and step-by-step course, divided into 85+ videos along with detailed resource files
Integrate real-time streaming data and data orchestration with Airflow and Snowflake
Highly practical explanations and lab exercises to help you grasp the most out of the course

Description

Snowflake is the next big thing, and it is becoming a full-blown data ecosystem. With the level of scalability and efficiency in handling massive volumes of data and also with several new concepts in it, this is the right time to wrap your head around Snowflake and have it in your toolkit. This course not only covers the core features of Snowflake but also teaches you how to deploy Python/PySpark jobs in AWS Glue and Airflow that communicate with Snowflake, which is one of the most important aspects of building pipelines. In this course, you will look at Snowflake, and then the most crucial aspects of Snowflake in an efficient manner. You will be writing Python/Spark Jobs in AWS Glue Jobs for data transformation and seeing real-time streaming using Kafka and Snowflake. You will be interacting with external functions and use cases, and see the security features in Snowflake. Finally, you will look at Snowpark and explore how it can be used for data pipelines and data science. By the end of this course, you will have learned about Snowflake and Snowpark, and learned how to build and architect data pipelines using AWS. You need to have an active AWS account in order to perform the sections related to Python and PySpark. For the rest of the course, a free trial Snowflake account should suffice.

Who is this book for?

This course is ideal for software engineers, aspiring data engineers or data analysts, and data scientists who want to excel in their careers in the IT domain. Apart from them, this course is also good for programmers and database administrators with experience in writing SQL queries. Prior programming experience in SQL or at least some prior knowledge in writing queries and Python is a must. You should have a basic experience or understanding of cloud services such as AWS along with an active AWS account.

What you will learn

Learn about Snowflake and its basics before getting started with labs
Check the crucial aspects of Snowflake in a very practical manner
Write Python/Spark jobs in AWS Glue Jobs for data transformation
Execute real-time streaming using Kafka and Snowflake
Interact with external functions and use cases
Learn and explore the Snowpark library

What do you get with a video?

Download this video in MP4 format

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Dulguun Mar 25, 2024

Hello, I'm trying to do The lab with Views, and it says Unsupported feature 'MATERIALIZED VIEWS'. So this feedback is kind of a question. I searched it on google and it states that Materialized views are a feature that is available on enterprise and above versions. Is it because I'm using the trial version of the Snowflake that giving me this error? If so please fix it and state it on the videos. Cheers

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Snowflake - Build and Architect Data Pipelines Using AWS: Data engineering and architecting pipelines using Snowflake and AWS cloud

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Snowflake - Build and Architect Data Pipelines Using AWS: Data engineering and architecting pipelines using Snowflake and AWS cloud

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