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Snowflake Cookbook

You're reading from Snowflake Cookbook Techniques for building modern cloud data warehousing solutions

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781800560611

Length 330 pages

Edition 1st Edition

Languages

Python

Tools

Cloud Foundry

Concepts

Data Science

Authors (2):

Hamid Mahmood Qureshi

Hammad Sharif

View More author details

Table of Contents (12) Chapters

Preface

1. Chapter 1: Getting Started with Snowflake

2. Chapter 2: Managing the Data Life Cycle FREE CHAPTER

3. Chapter 3: Loading and Extracting Data into and out of Snowflake

4. Chapter 4: Building Data Pipelines in Snowflake

5. Chapter 5: Data Protection and Security in Snowflake

6. Chapter 6: Performance and Cost Optimization

7. Chapter 7: Secure Data Sharing

8. Chapter 8: Back to the Future with Time Travel

9. Chapter 9: Advanced SQL Techniques

10. Chapter 10: Extending Snowflake Capabilities

11. Other Books You May Enjoy

Chapter 3: Loading and Extracting Data into and out of Snowflake

For any modern data warehouse system, getting data into the system and extracting data out of the system are key activities. This chapter provides a set of recipes that will guide you through the various nuances of loading data into Snowflake. The chapter talks about techniques for loading bulk data from on-premises systems and cloud storage and provides insights into the steps required to load streaming data into Snowflake by using Snowpipe.

The following recipes are included in this chapter:

Configuring Snowflake access to private S3 buckets
Loading delimited bulk data into Snowflake from cloud storage
Loading delimited bulk data into Snowflake from your local machine
Loading Parquet files into Snowflake
Making sense of JSON semi-structured data and transforming to a relational view
Processing Newline-Delimited JSON (or NDJSON) into a Snowflake table
Processing near real-time data...

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Authors (2)

Hamid Mahmood Qureshi

Hamid Mahmood Qureshi

Hamid Qureshi is a senior cloud and data warehouse professional with almost two decades of total experience, having architected, designed, and led the implementation of several data warehouse and business intelligence solutions. He has extensive experience and certifications across various data analytics platforms, ranging from Teradata, Oracle, and Hadoop to modern, cloud-based tools such as Snowflake. Having worked extensively with traditional technologies, combined with his knowledge of modern platforms, he has accumulated substantial practical expertise in data warehousing and analytics in Snowflake, which he has subsequently captured in his publications.

See other products by Hamid Mahmood Qureshi

Hammad Sharif

Hammad Sharif

Hammad Sharif is an experienced data architect with more than a decade of experience in the information domain, covering governance, warehousing, data lakes, streaming data, and machine learning. He has worked with a leading data warehouse vendor for a decade as part of a professional services organization, advising customers in telco, retail, life sciences, and financial industries located in Asia, Europe, and Australia during presales and post-sales implementation cycles. Hammad holds an MSc. in computer science and has published conference papers in the domains of machine learning, sensor networks, software engineering, and remote sensing.

See other products by Hammad Sharif

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