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Snowflake - Build and Architect Data Pipelines Using AWS

You're reading from   Snowflake - Build and Architect Data Pipelines Using AWS Data engineering and architecting pipelines using Snowflake and AWS cloud

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Product type Video
Published in Sep 2022
Last Updated in May 2023
Publisher Packt
ISBN-13 9781804615676
Length 8hrs 39mins
Edition 1st Edition
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Concepts
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Author (1):
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Siddharth Raghunath Siddharth Raghunath
Author Profile Icon Siddharth Raghunath
Siddharth Raghunath
Siddharth Raghunath is a business-oriented engineering manager with a vast experience in the field of software development, distributed processing, and cloud data engineering. He has worked on different cloud platforms such as AWS and GCP as well as on-premise Hadoop clusters. He conducts seminars on distributed processing using Spark, real-time streaming and analytics, and best practices for ETL and data governance. He is passionate about coding and building optimal data pipelines for robust data processing and streaming solutions.
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Table of Contents (14) Chapters Close

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

Profile icon Siddharth Raghunath
Siddharth Raghunath
Siddharth Raghunath is a business-oriented engineering manager with a vast experience in the field of software development, distributed processing, and cloud data engineering. He has worked on different cloud platforms such as AWS and GCP as well as on-premise Hadoop clusters. He conducts seminars on distributed processing using Spark, real-time streaming and analytics, and best practices for ETL and data governance. He is passionate about coding and building optimal data pipelines for robust data processing and streaming solutions.
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See other products by Siddharth Raghunath
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