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Spark, Hadoop, and Snowflake for Data Engineering

Noah Gift, Kennedy Behrman, and Matt Harrison

e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programmingGain the skills for building efficient and scalable data pipelines. Explore essential data engineering platforms (Hadoop, Spark, and Snowflake) as well as learn how to optimize and manage them. Delve into Databricks, a powerful platform for executing data analytics and machine learning tasks, while honing your Python data science skills with PySpark. Finally, discover the key concepts of MLflow, an open-source platform for managing the end-to-end machine learning lifecycle, and learn how to integrate it with Databricks.

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e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programmingGain the skills for building efficient and scalable data pipelines. Explore essential data engineering platforms (Hadoop, Spark, and Snowflake) as well as learn how to optimize and manage them. Delve into Databricks, a powerful platform for executing data analytics and machine learning tasks, while honing your Python data science skills with PySpark. Finally, discover the key concepts of MLflow, an open-source platform for managing the end-to-end machine learning lifecycle, and learn how to integrate it with Databricks.

This course is designed for learners who want to pursue or advance their career in data science or data engineering, or for software developers or engineers who want to grow their data management skill set. In addition to the technologies you will learn, you will also gain methodologies to help you hone your project management and workflow skills for data engineering, including applying Kaizen, DevOps, and Data Ops methodologies and best practices.

With quizzes to test your knowledge throughout, this comprehensive course will help guide your learning journey to become a proficient data engineer, ready to tackle the challenges of today's data-driven world.

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What's inside

Syllabus

Overview and Introduction to PySpark
This week, you will learn how to work with different data engineering platforms, such as Hadoop and Spark, and apply their concepts to real-world scenarios. First, you will explore the fundamentals of Hadoop to store and process big data. Next, you will delve into Spark concepts, distributed computing, deferred execution, and Spark SQL. By the end of the week, you will gain hands-on experience with PySpark DataFrames, DataFrame methods, and deferred execution strategies.
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Snowflake
This week, you will explore the Snowflake platform, gaining insights into its architecture and key concepts. Through hands-on practice in the Snowflake Web UI, you'll learn to create tables, manage warehouses, and use the Snowflake Python Connector to interact with tables. By the end of this week, you'll solidify your understanding of Snowflake's architecture and practical applications, emerging with the ability to effectively navigate and leverage the platform for data management and analysis.
Azure Databricks and MLFLow
This week, you will practice the essential skills for seamlessly managing machine learning workflows using Databricks and MLFlow. First, you will create a Databricks workspace and configure a cluster, setting the stage for efficient data analysis. Next, you will load a sample dataset into the Databricks workspace using the power of PySpark, enabling data manipulation and exploration. Finally, you will install MLFlow either locally or within the Databricks environment, gaining the ability to orchestrate the entire machine learning lifecycle. By the end of this week, you will be able to craft, track, and manage machine learning experiments within Databricks, ensuring precision, reproducibility, and optimal decision-making throughout your data-driven journey.
DataOps and Operations Methodologies
This week, you will explore the concepts of Kaizen, DevOps, and DataOps and how these methodologies synergistically contribute to efficient and seamless data engineering workflows. Through practical examples, you will learn how Kaizen's continuous improvement philosophy, DevOps' collaborative practices, and DataOps' focus on data quality and integration converge to enhance the development, deployment, and management of data engineering platforms. By the end of this week, you will have the knowledge and perspective needed to optimize data engineering processes and deliver scalable, reliable, and high-quality solutions.

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Know what's good
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, and possible dealbreakers
Primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming
Teaches essential data engineering platforms (Hadoop, Spark, and Snowflake) and how to optimize and manage them
Develops Python data science skills with PySpark
Covers key concepts of MLflow, an open-source platform for managing the end-to-end machine learning lifecycle
Teaches methodologies to help hone project management and workflow skills for data engineering, including applying Kaizen, DevOps, and Data Ops methodologies and best practices

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Career center

Learners who complete Spark, Hadoop, and Snowflake for Data Engineering will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers design, build, and maintain data pipelines. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Engineer.
Data Architect
Data Architects design, build, and maintain data systems. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Architect.
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Machine Learning Engineer.
Big Data Architect
Big Data Architects design, build, and maintain big data systems. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Big Data Architect.
Data Scientist
Data Scientists use data to build models that can predict future outcomes. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Scientist.
Data Analyst
Data Analysts use data to identify trends and patterns, and to develop insights that can help businesses make better decisions. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Analyst.
Data Quality Analyst
Data Quality Analysts are responsible for the assessment and improvement of data quality. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Quality Analyst.
Business Analyst
Business Analysts use data to identify problems and opportunities, and to develop solutions that can help businesses achieve their goals. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Business Analyst.
Data Governance Analyst
Data Governance Analysts are responsible for the development and implementation of data governance policies and procedures. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Governance Analyst.
Cloud Architect
Cloud Architects design, build, and maintain cloud-based applications. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Cloud Architect.
Product Manager
Product Managers are responsible for the development and management of products. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Product Manager.
Database Administrator
Database Administrators are responsible for the installation, configuration, and maintenance of databases. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Database Administrator.
Project Manager
Project Managers are responsible for the planning, execution, and management of projects. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Project Manager.
Systems Administrator
Systems Administrators are responsible for the installation, configuration, and maintenance of computer systems. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Systems Administrator.
Software Developer
Software Developers design, build, and maintain software applications. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Software Developer.

Reading list

We've selected 11 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 Spark, Hadoop, and Snowflake for Data Engineering.
Delves deeper into the internal workings of Spark, covering topics such as cluster management, fault tolerance, and performance tuning.
Provides valuable insights into designing data-intensive applications. [fit_score: 85, difficulty_score: 75]
Provides a detailed overview of the Hadoop ecosystem, including HDFS, MapReduce, and YARN, making it an excellent foundation for understanding the concepts covered in the course.
Explores DevOps practices in the context of data engineering, providing insights into collaboration, automation, and continuous delivery, which are covered in the course's methodologies section.
Provides hands-on examples and case studies of Spark in action, helping you apply the concepts covered in the course to real-world scenarios.
Is considered a classic in the data warehousing field. [fit_score: 80, difficulty_score: 75]
Provides a comprehensive overview of data management with MongoDB. [fit_score: 75, difficulty_score: 65]
Provides a foundation for understanding big data analytics with Java. [fit_score: 70, difficulty_score: 65]

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