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Data Engineering with Apache Spark, Delta Lake, and Lakehouse

You're reading from  Data Engineering with Apache Spark, Delta Lake, and Lakehouse

Product type Book
Published in Oct 2021
Publisher Packt
ISBN-13 9781801077743
Pages 480 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Manoj Kukreja Manoj Kukreja
Profile icon Manoj Kukreja
LinkedIn
Manoj Kukreja is a Principal Architect at Northbay Solutions who specializes in creating complex Data Lakes and Data Analytics Pipelines for large-scale organizations such as banks, insurance companies, universities, and US/Canadian government agencies. Previously, he worked for Pythian, a large managed service provider where he was leading the MySQL and MongoDB DBA group and supporting large-scale data infrastructure for enterprises across the globe. With over 25 years of IT experience, he has delivered Data Lake solutions using all major cloud providers including AWS, Azure, GCP, and Alibaba Cloud. On weekends, he trains groups of aspiring Data Engineers and Data Scientists on Hadoop, Spark, Kafka and Data Analytics on AWS and Azure Cloud.
See other products by Manoj Kukreja

Table of Contents (17) Chapters

Preface Section 1: Modern Data Engineering and Tools
Chapter 1: The Story of Data Engineering and Analytics Chapter 2: Discovering Storage and Compute Data Lakes Chapter 3: Data Engineering on Microsoft Azure Section 2: Data Pipelines and Stages of Data Engineering
Chapter 4: Understanding Data Pipelines Chapter 5: Data Collection Stage – The Bronze Layer Chapter 6: Understanding Delta Lake Chapter 7: Data Curation Stage – The Silver Layer Chapter 8: Data Aggregation Stage – The Gold Layer Section 3: Data Engineering Challenges and Effective Deployment Strategies
Chapter 9: Deploying and Monitoring Pipelines in Production Chapter 10: Solving Data Engineering Challenges Chapter 11: Infrastructure Provisioning Chapter 12: Continuous Integration and Deployment (CI/CD) of Data Pipelines Other Books You May Enjoy

Opening a free account with Microsoft Azure

In the upcoming chapters, we will be using the services you have just been reading about to build a data lake using the lakehouse architecture. Therefore, it is time to open a free Azure account that gives you 12 months of free services, plus a one-time $260 credit. Please note that not all – but most – services are free. To open a free account and browse through the free services, please visit the following link: https://azure.microsoft.com/en-ca/free/.

Here is some valuable advice:

  • It is always a good idea to remove the compute resources once you've used them.
  • You get 5 GB of locally redundant data (LRS) data for free. There is no need to remove data that's stored during future exercises since we will not be exceeding this limit.
  • While using the free services in Azure, please keep a strict eye on your billing using the following link: https://portal.azure.com/#blade/Microsoft_Azure_Billing/BillingMenuBlade...
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Authors (1)

Profile icon Manoj Kukreja
LinkedIn
Manoj Kukreja is a Principal Architect at Northbay Solutions who specializes in creating complex Data Lakes and Data Analytics Pipelines for large-scale organizations such as banks, insurance companies, universities, and US/Canadian government agencies. Previously, he worked for Pythian, a large managed service provider where he was leading the MySQL and MongoDB DBA group and supporting large-scale data infrastructure for enterprises across the globe. With over 25 years of IT experience, he has delivered Data Lake solutions using all major cloud providers including AWS, Azure, GCP, and Alibaba Cloud. On weekends, he trains groups of aspiring Data Engineers and Data Scientists on Hadoop, Spark, Kafka and Data Analytics on AWS and Azure Cloud.
Read more
See other products by Manoj Kukreja

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