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Snowflake - Build and Architect Data Pipelines Using AWS [Video]
Snowflake - Build and Architect Data Pipelines Using AWS [Video]

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

By Siddharth Raghunath
$69.99 $9.99
Video Sep 2022 8 hours 39 minutes 1st Edition
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$69.99 $9.99
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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.

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

Product Details

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Publication date : Sep 27, 2022
Length 8 hours 39 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781804615676

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
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Product Details


Publication date : Sep 27, 2022
Length 8 hours 39 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781804615676

Table of Contents

14 Chapters
1. Introduction to the Course Chevron down icon Chevron up icon
2. Introduction to Snowflake and AWS Chevron down icon Chevron up icon
3. Snowflake - Tables Chevron down icon Chevron up icon
4. Snowflake – Partitioning, Clustering, and Performance Optimization Chevron down icon Chevron up icon
5. Snowflake – Data Loading/Ingestion and Extraction Chevron down icon Chevron up icon
6. Snowflake – Tasks and Query Scheduling Chevron down icon Chevron up icon
7. Snowflake – Streams and Change Data Capture Chevron down icon Chevron up icon
8. Snowflake – User-Defined Functions Chevron down icon Chevron up icon
9. Snowflake – External Functions Chevron down icon Chevron up icon
10. Snowflake with Python, Spark, and Airflow on AWS Chevron down icon Chevron up icon
11. Real-Time Streaming with Kafka and Snowflake Chevron down icon Chevron up icon
12. Snowflake – Data Protection and Governance Chevron down icon Chevron up icon
13. Snowpark – For Data Pipelines and Data Science Chevron down icon Chevron up icon
14. Wrap Up and More Learning Chevron down icon Chevron up icon

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