Books > Computing & IT > Social & legal aspects of computing > Human-computer interaction
|
Buy Now
Data Engineering with Python - Work with massive datasets to design data models and automate data pipelines using Python (Paperback)
Loot Price: R1,378
Discovery Miles 13 780
|
|
Data Engineering with Python - Work with massive datasets to design data models and automate data pipelines using Python (Paperback)
Expected to ship within 10 - 15 working days
|
Build, monitor, and manage real-time data pipelines to create data
engineering infrastructure efficiently using open-source Apache
projects Key Features Become well-versed in data architectures,
data preparation, and data optimization skills with the help of
practical examples Design data models and learn how to extract,
transform, and load (ETL) data using Python Schedule, automate, and
monitor complex data pipelines in production Book DescriptionData
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. What you will learn Understand how data engineering
supports data science workflows Discover how to extract data from
files and databases and then clean, transform, and enrich it
Configure processors for handling different file formats as well as
both relational and NoSQL databases Find out how to implement a
data pipeline and dashboard to visualize results Use staging and
validation to check data before landing in the warehouse Build
real-time pipelines with staging areas that perform validation and
handle failures Get to grips with deploying pipelines in the
production environment Who this book is forThis book is for data
analysts, ETL developers, and anyone looking to get started with or
transition to the field of data engineering or refresh their
knowledge of data engineering using Python. This book will also be
useful for students planning to build a career in data engineering
or IT professionals preparing for a transition. No previous
knowledge of data engineering is required.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.