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Creating Reusable Pipelines in Cloud Data Fusion

Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will learn how to build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Builds a foundational understanding of data pipelines in Google Cloud
Uses Google Cloud's scalable infrastructure for data storage
Develops a reusable pipeline for data processing and quality checks
Hands-on labs provide practical experience with Google Cloud
Assumes learners have some familiarity with Google Cloud concepts
Self-paced learning requires strong self-motivation and time management

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Creating Reusable Pipelines in Cloud Data Fusion with these activities:
Create a Course Material Compilation
Organize and review course materials
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  • Gather all of the course materials.
  • Organize the materials into a logical structure.
Review Data Engineering Concepts
Refresh your understanding of data engineering concepts
Browse courses on Data Engineering
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  • Review the different stages of the data pipeline.
  • Review the different tools and technologies used in data engineering.
Review Python Programming
Strengthen your Python skills
Browse courses on Python
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  • Review the basics of Python syntax.
  • Practice writing Python code.
Four other activities
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Practice Guided Tutorials on Google AI Platform
Help familiarize yourself with Google AI Platform
Browse courses on Google AI Platform
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  • Identify a tutorial that covers a topic relevant to the course.
  • Follow the steps in the tutorial to complete the exercises.
  • Review the concepts covered in the tutorial and apply them to your own projects.
Practice Data Cleaning Drills
Improve your data cleaning skills
Show steps
  • Find a dataset that contains dirty data.
  • Use data cleaning techniques to clean the data.
  • Verify that the data is clean.
Read a Book on Cloud Computing
Reviewing a book on cloud computing will help you understand the fundamentals of the technology and how it can be used to solve business problems.
Show steps
  • Choose a book on cloud computing.
  • Read the book.
  • Take notes on the key concepts.
  • Discuss the book with other classmates or colleagues.
Create a Data Pipeline Project
Gain hands-on experience building a data pipeline
Show steps
  • Design a data pipeline that meets a specific need.
  • Implement the data pipeline using Google Cloud services.
  • Test and validate the data pipeline.

Career center

Learners who complete Creating Reusable Pipelines in Cloud Data Fusion will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers design architectures and implement data pipelines for collecting, storing, cleaning, and securing data assets. The course will teach you the fundamentals of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This hands-on experience will give you a valuable foundation for a successful career as a Data Engineer.
Data Analyst
Data Analysts clean, process, and model data to derive insights and support decision-making. The course will teach you the basics of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This knowledge will be essential for a successful career as a Data Analyst, enabling you to effectively manage and analyze large datasets.
Data Scientist
Data Scientists develop, evaluate, and implement predictive models and algorithms to extract knowledge from data. The course will teach you the fundamentals of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This hands-on experience will give you a strong foundation for a successful career as a Data Scientist.
Cloud Architect
Cloud Architects design, build, and manage cloud infrastructure and services. The course will teach you the basics of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This knowledge will be beneficial for a Cloud Architect, enabling them to design and implement scalable and reliable data pipelines in the cloud.
Software Engineer
Software Engineers design, develop, and maintain software applications. The course will teach you the fundamentals of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This hands-on experience will give you a strong foundation for a successful career as a Software Engineer, enabling you to develop and implement data-driven applications.
Business Analyst
Business Analysts gather and analyze business requirements to develop solutions that meet organizational needs. The course will teach you the basics of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This knowledge will be valuable for a Business Analyst, enabling them to effectively analyze data and make informed recommendations for business improvements.
Database Administrator
Database Administrators manage and maintain database systems to ensure data integrity and performance. The course will teach you the basics of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This knowledge will be beneficial for a Database Administrator, enabling them to design and implement scalable and reliable data pipelines for data storage and management.
Data Integration Specialist
Data Integration Specialists design and implement solutions for integrating data from multiple sources into a single, cohesive system. The course will teach you the fundamentals of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This hands-on experience will give you a strong foundation for a successful career as a Data Integration Specialist.
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models and algorithms to solve business problems. The course will teach you the basics of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This knowledge will be valuable for a Machine Learning Engineer, enabling them to effectively manage and analyze data for machine learning model development and deployment.
Data Warehouse Engineer
Data Warehouse Engineers design, build, and maintain data warehouses to store and manage large volumes of data. The course will teach you the fundamentals of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This hands-on experience will give you a strong foundation for a successful career as a Data Warehouse Engineer.
ETL Developer
ETL Developers design, build, and maintain extract, transform, and load (ETL) processes to move data from source systems to target systems. The course will teach you the fundamentals of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This hands-on experience will give you a strong foundation for a successful career as an ETL Developer.
Data Governance Analyst
Data Governance Analysts develop and implement policies and procedures to ensure the quality and integrity of data. The course will teach you the basics of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This knowledge will be valuable for a Data Governance Analyst, enabling them to effectively assess and manage data quality and compliance.
Data Quality Analyst
Data Quality Analysts analyze data to identify and correct errors and inconsistencies. The course will teach you the basics of data pipelines and help you build a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage. This hands-on experience will give you a strong foundation for a successful career as a Data Quality Analyst.

Reading list

We've selected nine 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 Creating Reusable Pipelines in Cloud Data Fusion.
Provides a comprehensive guide to building data pipelines with Spark. It covers everything from the basics of Spark to advanced topics such as streaming and machine learning.
Provides a comprehensive guide to building data pipelines with Hadoop. It covers everything from the basics of Hadoop to advanced topics such as YARN and MapReduce.
Provides a comprehensive guide to building data pipelines with Pig. It covers everything from the basics of Pig to advanced topics such as UDFs and UDAFs.
Provides a practical guide to building data pipelines with Apache Kafka. It covers everything from installation to deployment, and it includes a number of case studies and examples.
Provides a practical guide to building data pipelines with Presto. It covers everything from installation to deployment, and it includes a number of case studies and examples.
Provides a practical guide to building data pipelines with Hive. It covers everything from installation to deployment, and it includes a number of case studies and examples.
Provides a deep dive into the principles of data-intensive application design. It covers topics such as data modeling, data storage, data processing, and data analytics.
Provides a comprehensive guide to building data pipelines in R. It covers all aspects of data pipelines, from data ingestion and transformation to data storage and analysis.

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