Snowflake – Build & Architect Data pipelines using AWS

Data engineering and architecting pipelines using snowflake & AWS cloud

Snowflake is the next big thing and it is becoming a full blown data eco-system . With the level of scalability & efficiency in handling massive volumes of data and also with a number of 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 .

What you’ll learn

  • Snowflake as a data-warehouse along with other important features.
  • Build Automated Pipelines with Snowflake.
  • Use AWS Cloud with Snowflake as a data-warehouse.
  • Integrating real time streaming data and data orchestration with Airflow and Snowflake.

Course Content

  • Introduction –> 4 lectures • 7min.
  • Introduction to Snowflake and AWS –> 9 lectures • 47min.
  • Snowflake – Tables –> 6 lectures • 30min.
  • Snowflake – Partitioning , Clustering and Performance Optimization –> 9 lectures • 1hr 12min.
  • Snowflake – Data Loading/Ingestion and Extraction –> 9 lectures • 54min.
  • Snowflake – Tasks and Query Scheduling –> 4 lectures • 15min.
  • Snowflake – Streams and Change Data Capture –> 11 lectures • 58min.
  • Snowflake – User Defined Functions –> 7 lectures • 36min.
  • Snowflake – External Functions –> 6 lectures • 28min.
  • Snowflake with Python,Spark and Airflow on AWS –> 12 lectures • 52min.
  • Real Time Streaming with Kafka and Snowflake –> 6 lectures • 32min.
  • Snowflake – Data Protection and Governance –> 7 lectures • 24min.

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Requirements

Snowflake is the next big thing and it is becoming a full blown data eco-system . With the level of scalability & efficiency in handling massive volumes of data and also with a number of 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 .

Anyone who has a basic understanding of cloud and belong to one of the below backgrounds can benefit from this course :

– Data Scientists / Analysts

– Data Engineers / Software Developers

– SQL Programmers or DBA’s

– Aspiring Data analysts and scientists who are learning SQL and Python

 

This Course covers : 

 

  • What is Snowflake
  • Most Crucial Aspects of Snowflake in a very practical manner
  • Writing Python/Spark Jobs in AWS Glue Jobs for data transformation
  • Real Time Streaming using Kafka and Snowflake
  • Interacting with External Functions & use cases
  • Security Features in Snowflake

Prerequisites for this course are : 

 

  • Knowing SQL or at least some prior knowledge in writing queries
  • Scripting in Python (or any language )
  • Willingness to explore ,learn and put in the extra effort to succeed
  • An active AWS Account & know-how of basic cloud fundamentals

Important Note –  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 .

 

Some Tips : 

  • Try to watch the videos at 1.2X speed
  • Read the reference links and the official documentation of Snowflake as much as possible

 

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