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Data Engineering with Python

Data Engineering with Python

By : Paul Crickard
2.6 (24)
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Data Engineering with Python

Data Engineering with Python

2.6 (24)
By: Paul Crickard

Overview of this book

Data engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.
Table of Contents (21 chapters)
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1
Section 1: Building Data Pipelines – Extract Transform, and Load
8
Section 2:Deploying Data Pipelines in Production
14
Section 3:Beyond Batch – Building Real-Time Data Pipelines

Creating a test and production environment

In this chapter, we will return to using PostgreSQL for both the extraction and loading of data. The data pipeline will require a test and production environment, each of which will have a staging and a warehouse table. To create the databases and tables, you will use PgAdmin4.

Creating the databases

To use PgAdmin4, perform the following steps:

  1. Browse to http://localhostw/pgadmin4/l, enter your username and password, and then click the Login button. Once logged in, expand the server icon in the left panel.
  2. To create the databases, right-click on the databases icon and select Create | Database. Name the database test.
  3. Next, you will need to add the tables. To create the staging table, right-click on Tables | Create | Table. On the General tab, name the table staging. Then, select the Columns tab. Using the plus sign, create the fields shown in the following screenshot:

    Figure 11.1 – The columns used in the staging...

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Data Engineering with Python
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