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Pipeline Creation

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May 1, 2024 3 minute read
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Pipeline Creation is a crucial aspect of data management and workflow automation. It involves designing and constructing pipelines that orchestrate data flows, transforming raw data into valuable insights or automated actions. Pipelines enable organizations to streamline complex processes, increase efficiency, and make data-driven decisions.

Why Learn Pipeline Creation?

There are several compelling reasons to learn about Pipeline Creation:

Path to Pipeline Creation

Take the first step.
We've curated two courses to help you on your path to Pipeline Creation. Use these to develop your skills, build background knowledge, and put what you learn to practice.
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Reading list

We've selected five books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Pipeline Creation.
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Designing Data-Intensive Applications
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This classic work covers the principles and techniques for designing data-intensive applications, including data pipeline architectures, data modeling, and data processing algorithms.
Designing Data-Intensive Applications: The Big...
Paperback
$$
Designing Data-Intensive Applications: The Big...
Kindle Edition
$$
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Data Pipelines with Apache Airflow
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Guides readers through the process of designing, building, and operating scalable, reliable, and maintainable data pipelines using Apache Airflow, a popular open-source workflow management platform.
Data Pipelines with Apache Airflow
Paperback
$$
Data Pipelines with Apache Airflow
Kindle Edition
$$
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Advanced Analytics with Spark
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This practical guide focuses on the real-world challenges of building and maintaining data pipelines, including data quality, data security, and operational considerations.
Advanced Analytics with Spark
Paperback
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Advanced Analytics with Spark
Kindle Edition
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Data Pipelines Pocket Reference
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This concise reference provides a quick and easy way to understand the fundamentals of data pipelines, including design principles, common challenges, and best practices.
Data Pipelines Pocket Reference: Moving and...
Paperback
$$
Data Pipelines Pocket Reference: Moving and...
Kindle Edition
$$
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Scala: Guide for Data Science Professionals
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Focuses on the specific challenges of building data pipelines for machine learning, covering data preparation, feature engineering, and model training.
Scala: Guide for Data Science Professionals
Kindle Edition
$$$
Relevant careers
Data Engineer
Data Analyst
Data Scientist
Cloud Engineer
Machine Learning Engineer
Software Engineer
Business Analyst
Related topics
Cloud Computing
AutoML
Data Engineering
Workflow Management
Machine Learning
Big Data
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