Snowflake - Datawarehouse and Datalake solutions using AWS
Data engineering and architecting pipelines using snowflake & AWS cloud
Development ,Data Science,Big Data
Lectures -97
Resources -12
Duration -8.5 hours
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Course Description
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 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.
Anyone who has a basic understanding of the cloud and belongs to one of the below backgrounds can benefit from this course :
- Data Scientists / Analysts
- Data Engineers / Software Developers
- SQL Programmers or DBAs
- 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
Important Note - You need to have an active AWS Account to perform tasks in sections related to Python and PySpark. This course will help you with Snowpro certifications as well
Goals
- Snowflake as a data warehouse & automated pipelines within the Snowflake ecosystem
- Use AWS Cloud with Snowflake as a Data-warehouse/Data lake
- Integrating real-time Streaming Data and Data orchestration with Airflow and Snowflake
- Enough Knowledge to clear SnowPro Certification
Prerequisites
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
Prior programming experience in SQL and Python is a must.
Prior basic experience or understanding of cloud services like AWS is important

Curriculum
Check out the detailed breakdown of what’s inside the course
Course Introduction
3 Lectures
-
Course Roadmap 02:54 02:54
-
Prerequisites and How to Success in this course 02:51 02:51
-
Repo for the Course
Introduction to Snowflake and AWS
9 Lectures

Snowflake - Tables
6 Lectures

Snowflake - Partitioning , Clustering and Performance Optimization
9 Lectures

Snowflake - Data Loading/Ingestion and Extraction
9 Lectures

Snowflake - Tasks and Query Scheduling
4 Lectures

Snowflake - Streams and Change Data Capture
11 Lectures

Snowflake - User Defined Functions
7 Lectures

Snowflake - External Functions
7 Lectures

Snowflake with Python,Spark and Airflow on AWS
12 Lectures

Real Time Streaming with Kafka and Snowflake
6 Lectures

Snowpark - For Data Pipelines and Data Science
8 Lectures

Snowflake - Data Protection and Governance
6 Lectures

Instructor Details

siddharth raghunath
I am a Business oriented Data Architect with a vast experience in the field of Software Development,Distributed processing and data engineering on cloud . I have worked on different cloud platforms such as AWS & GCP and also with on-prem hadoop clusters. I also give seminars on Distributed processing using Spark , real time streaming and analytics and best practices for ETL and data governance.I am also a passionate coder ,love writing and building optimal data pipelines for robust data processing and streaming solutions .
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