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Vishnu (Lucky) Pamula,
Amanda Moran,
and
Matt Swaffer, PhD
Master big data and develop the skills to work with datasets using Spark, Azure, Data Lakes and Lakehouses. Take the Udacity Big Data Training Course today!
Register for this course and see more details by visiting:
OpenCourser.com/course/6zwjhn/data
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What's inside
Syllabus
In this lesson, you'll learn about the course, including the prerequisites, tools, environment, and course project.
In this lesson, you will learn about the problems that Apache Spark is designed to solve. You'll also learn about the greater Big Data ecosystem and how Spark fits into it.
Read more
Syllabus
In this lesson, you'll learn about the course, including the prerequisites, tools, environment, and course project.
In this lesson, you will learn about the problems that Apache Spark is designed to solve. You'll also learn about the greater Big Data ecosystem and how Spark fits into it.
Read more
In this lesson, we'll dive into how to use Spark for cleaning and aggregating data.
In this lesson, you will learn best practices for debugging and optimizing your Spark applications.
In this lesson, you'll create Spark Clusters and Spark code on the Azure Databricks platform.
In this lesson, you'll create data lakes and Lakehouse architecture on the Azure Databricks platform
In this project, you'll implement Lakehouse architecture on the Azure Databricks platform.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores Spark, Azure, Data Lakes, and Lakehouses, which are prominent in the big data industry
Taught by Vishnu (Lucky) Pamula, Amanda Moran, and Matt Swaffer, PhD, who are recognized for their work in big data and data analytics
Builds a strong foundation for beginners in big data technologies and concepts
Requires experience with programming and data analysis, which may be a caveat for learners new to these fields
Save this course
Save Data lakes and Lakehouses with Spark and Azure Databricks to your list so you can find it easily later:
Save
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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 Data lakes and Lakehouses with Spark and Azure Databricks with these
activities:
Review Apache Spark fundamentals
Show steps
Strengthen your understanding of the fundamental concepts and capabilities of Spark and familiarize yourself with the tools and technologies used with Spark to prepare for the course content.
Browse courses on
Apache Spark
Show steps
-
Read Apache Spark documentation
-
Watch Apache Spark video tutorials
-
Complete Apache Spark online courses
Review Python Basics
Show steps
Enhance your proficiency in Python, the primary language used with Spark, by revisiting its syntax, data structures, and control flow.
Browse courses on
Python
Show steps
-
Review online tutorials or documentation on Python basics.
-
Solve coding challenges or practice exercises to reinforce your understanding.
Refresh Data Management Knowledge
Show steps
By refreshing your knowledge of data management, you provide yourself with a stronger foundation and better chance to understand the more advanced techniques covered in this course.
Browse courses on
Data Management
Show steps
-
Review concepts of data modeling and data warehousing
-
Practice data cleaning and transformation techniques
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Review Data Structures & Algorithms
Show steps
Brush up on the underlying data structures and algorithms used in big data processing, enhancing your understanding of Spark's implementation.
Browse courses on
Data Structures
Show steps
-
Review core data structures such as arrays, linked lists, and hash tables.
-
Examine common sorting and searching algorithms like quicksort and binary search.
Explore the Apache Spark Tutorial
Show steps
Familiarize yourself with Spark's key concepts and functionalities through guided tutorials, strengthening your foundational understanding.
Browse courses on
Apache Spark
Show steps
-
Visit the Apache Spark website and access the official tutorial.
-
Follow the tutorial's instructions to set up Spark and run sample code.
Practice Spark Transformations and Actions
Show steps
Solving problems and implementing solutions in Apache Spark will help you master this technology and become proficient in this course.
Browse courses on
Apache Spark
Show steps
-
Complete the provided coding exercises
-
Create your own Spark examples
Solve Big Data Coding Challenges
Show steps
Engage in practice exercises and coding challenges specific to big data processing, honing your problem-solving abilities in a practical context.
Show steps
-
Join online coding platforms like LeetCode or HackerRank.
-
Search for big data or Spark-related coding challenges.
-
Attempt to solve the challenges, researching and applying appropriate techniques.
Complete Data Lake architecture exercises
Show steps
Practice Data Lake architecture exercises to reinforce your understanding of how to design and implement Data Lake solutions using Azure Databricks.
Browse courses on
Data Lake
Show steps
-
Choose a data lake architecture scenario
-
Design the data lake
-
Implement the data lake
-
Test and evaluate the data lake
Create a Presentation on Big Data Technologies
Show steps
Creating a presentation will help you synthesize and communicate your knowledge of Big Data technologies.
Browse courses on
Big Data Technologies
Show steps
-
Choose a specific topic related to the course
-
Research and gather information on the topic
-
Create slides and organize the presentation
-
Practice delivering the presentation
Explore the Azure Databricks Documentation
Show steps
Familiarize yourself with the Azure Databricks platform, its features, and best practices, enhancing your ability to utilize it effectively for big data processing.
Browse courses on
Azure Databricks
Show steps
-
Visit the Azure Databricks website and access the documentation.
-
Explore the tutorials and guides to understand the platform's capabilities.
Implement a Mini Big Data Pipeline
Show steps
Undertake a hands-on project to design and implement a scaled-down big data pipeline, applying the principles and techniques learned in the course.
Browse courses on
Data Engineering
Show steps
-
Choose a dataset and define a data processing workflow.
-
Set up a Spark environment and develop code to read, transform, and analyze the data.
-
Evaluate the results and iterate on the pipeline to optimize performance.
Create a data visualization
Show steps
Create a data visualization to reinforce your understanding of data visualization techniques and how to use Apache Spark to process and analyze big data.
Browse courses on
Apache Spark
Show steps
-
Gather data and prepare it for analysis
-
Use Apache Spark to process and analyze the data
-
Choose a data visualization tool
-
Create the data visualization
Follow tutorials on advanced Spark techniques
Show steps
Expand your knowledge and skills by following tutorials on advanced Apache Spark techniques to reinforce your understanding of the capabilities of Spark and how to use it effectively.
Browse courses on
Apache Spark
Show steps
-
Find tutorials on advanced Spark techniques
-
Select a tutorial
-
Follow the tutorial
-
Practice the techniques
Explore Advanced Azure Databricks Features
Show steps
Expanding your knowledge of Azure Databricks beyond the course materials will help you gain a deeper understanding of its capabilities and how it can be used to solve real-world problems.
Browse courses on
Azure Databricks
Show steps
-
Review Azure Databricks documentation
-
Complete additional Azure Databricks tutorials
-
Experiment with advanced Azure Databricks features
Participate in a Big Data Hackathon
Show steps
Immerse yourself in a team-based challenge to solve a real-world big data problem, enhancing your collaboration and problem-solving skills.
Show steps
-
Identify and register for relevant hackathons or competitions.
-
Form a team with diverse expertise.
-
Brainstorm and develop innovative solutions using big data technologies and approaches.
Implement a Lakehouse architecture on the Azure Databricks platform
Show steps
Develop your practical skills and deepen your understanding by implementing a Lakehouse architecture on the Azure Databricks platform to consolidate your knowledge of big data storage and processing techniques.
Browse courses on
Azure Databricks
Show steps
-
Define the project requirements
-
Design the Lakehouse architecture
-
Implement the Lakehouse architecture
-
Test and evaluate the Lakehouse architecture
Implement Lakehouse Architecture on Azure Databricks
Show steps
Implementing a full-fledged project will test your understanding and help you become more proficient in building Big Data solutions on Azure Databricks.
Browse courses on
Azure Databricks
Show steps
-
Design a data lake and Lakehouse architecture
-
Provision and configure Azure Databricks resources
-
Implement data ingestion and processing pipelines
-
Build data analytics and visualization applications
Review Apache Spark fundamentals
Show steps
Strengthen your understanding of the fundamental concepts and capabilities of Spark and familiarize yourself with the tools and technologies used with Spark to prepare for the course content.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Read Apache Spark documentation
- Watch Apache Spark video tutorials
- Complete Apache Spark online courses
Review Python Basics
Show steps
Enhance your proficiency in Python, the primary language used with Spark, by revisiting its syntax, data structures, and control flow.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review online tutorials or documentation on Python basics.
- Solve coding challenges or practice exercises to reinforce your understanding.
Refresh Data Management Knowledge
Show steps
By refreshing your knowledge of data management, you provide yourself with a stronger foundation and better chance to understand the more advanced techniques covered in this course.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Review concepts of data modeling and data warehousing
- Practice data cleaning and transformation techniques
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Review Data Structures & Algorithms
Show steps
Brush up on the underlying data structures and algorithms used in big data processing, enhancing your understanding of Spark's implementation.
Browse courses on
Data Structures
Show steps
Show steps
Show steps
- Review core data structures such as arrays, linked lists, and hash tables.
- Examine common sorting and searching algorithms like quicksort and binary search.
Explore the Apache Spark Tutorial
Show steps
Familiarize yourself with Spark's key concepts and functionalities through guided tutorials, strengthening your foundational understanding.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Visit the Apache Spark website and access the official tutorial.
- Follow the tutorial's instructions to set up Spark and run sample code.
Practice Spark Transformations and Actions
Show steps
Solving problems and implementing solutions in Apache Spark will help you master this technology and become proficient in this course.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Complete the provided coding exercises
- Create your own Spark examples
Solve Big Data Coding Challenges
Show steps
Engage in practice exercises and coding challenges specific to big data processing, honing your problem-solving abilities in a practical context.
Show steps
Show steps
Show steps
- Join online coding platforms like LeetCode or HackerRank.
- Search for big data or Spark-related coding challenges.
- Attempt to solve the challenges, researching and applying appropriate techniques.
Complete Data Lake architecture exercises
Show steps
Practice Data Lake architecture exercises to reinforce your understanding of how to design and implement Data Lake solutions using Azure Databricks.
Browse courses on
Data Lake
Show steps
Show steps
Show steps
- Choose a data lake architecture scenario
- Design the data lake
- Implement the data lake
- Test and evaluate the data lake
Create a Presentation on Big Data Technologies
Show steps
Creating a presentation will help you synthesize and communicate your knowledge of Big Data technologies.
Browse courses on
Big Data Technologies
Show steps
Show steps
Show steps
- Choose a specific topic related to the course
- Research and gather information on the topic
- Create slides and organize the presentation
- Practice delivering the presentation
Explore the Azure Databricks Documentation
Show steps
Familiarize yourself with the Azure Databricks platform, its features, and best practices, enhancing your ability to utilize it effectively for big data processing.
Browse courses on
Azure Databricks
Show steps
Show steps
Show steps
- Visit the Azure Databricks website and access the documentation.
- Explore the tutorials and guides to understand the platform's capabilities.
Implement a Mini Big Data Pipeline
Show steps
Undertake a hands-on project to design and implement a scaled-down big data pipeline, applying the principles and techniques learned in the course.
Browse courses on
Data Engineering
Show steps
Show steps
Show steps
- Choose a dataset and define a data processing workflow.
- Set up a Spark environment and develop code to read, transform, and analyze the data.
- Evaluate the results and iterate on the pipeline to optimize performance.
Create a data visualization
Show steps
Create a data visualization to reinforce your understanding of data visualization techniques and how to use Apache Spark to process and analyze big data.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Gather data and prepare it for analysis
- Use Apache Spark to process and analyze the data
- Choose a data visualization tool
- Create the data visualization
Follow tutorials on advanced Spark techniques
Show steps
Expand your knowledge and skills by following tutorials on advanced Apache Spark techniques to reinforce your understanding of the capabilities of Spark and how to use it effectively.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Find tutorials on advanced Spark techniques
- Select a tutorial
- Follow the tutorial
- Practice the techniques
Explore Advanced Azure Databricks Features
Show steps
Expanding your knowledge of Azure Databricks beyond the course materials will help you gain a deeper understanding of its capabilities and how it can be used to solve real-world problems.
Browse courses on
Azure Databricks
Show steps
Show steps
Show steps
- Review Azure Databricks documentation
- Complete additional Azure Databricks tutorials
- Experiment with advanced Azure Databricks features
Participate in a Big Data Hackathon
Show steps
Immerse yourself in a team-based challenge to solve a real-world big data problem, enhancing your collaboration and problem-solving skills.
Show steps
Show steps
Show steps
- Identify and register for relevant hackathons or competitions.
- Form a team with diverse expertise.
- Brainstorm and develop innovative solutions using big data technologies and approaches.
Implement a Lakehouse architecture on the Azure Databricks platform
Show steps
Develop your practical skills and deepen your understanding by implementing a Lakehouse architecture on the Azure Databricks platform to consolidate your knowledge of big data storage and processing techniques.
Browse courses on
Azure Databricks
Show steps
Show steps
Show steps
- Define the project requirements
- Design the Lakehouse architecture
- Implement the Lakehouse architecture
- Test and evaluate the Lakehouse architecture
Implement Lakehouse Architecture on Azure Databricks
Show steps
Implementing a full-fledged project will test your understanding and help you become more proficient in building Big Data solutions on Azure Databricks.
Browse courses on
Azure Databricks
Show steps
Show steps
Show steps
- Design a data lake and Lakehouse architecture
- Provision and configure Azure Databricks resources
- Implement data ingestion and processing pipelines
- Build data analytics and visualization applications
Career center
Learners who complete Data lakes and Lakehouses with Spark and Azure Databricks will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
As a Data Engineer, you would be responsible for designing, building, and maintaining data pipelines and infrastructure. This course would be beneficial to you as it provides hands-on experience with Azure Databricks, a leading platform for data engineering.
Data Analyst
Data Analyst
As a Data Analyst, you would be responsible for collecting, cleaning, and analyzing data to provide insights to businesses. This course would be beneficial to you as it provides a comprehensive overview of data lakes, data lakehouses, and Apache Spark, a powerful tool for processing big data.
Data Scientist
Data Scientist
As a Data Scientist, you would be responsible for developing and applying machine learning and artificial intelligence models to solve business problems. This course would be beneficial to you as it provides a foundation in data engineering and big data processing, which are essential skills for Data Scientists.
Data Architect
Data Architect
As a Data Architect, you would be responsible for designing and managing data systems. This course may be useful to you if you are interested in specializing in big data architecture or data engineering.
Machine Learning Engineer
Machine Learning Engineer
As a Machine Learning Engineer, you would be responsible for developing and deploying machine learning models. This course may be useful to you if you are interested in specializing in big data machine learning.
Data Visualization Analyst
Data Visualization Analyst
As a Data Visualization Analyst, you would be responsible for creating and communicating data visualizations. This course may be useful to you if you are interested in specializing in big data visualization.
Cloud Architect
Cloud Architect
As a Cloud Architect, you would be responsible for designing and managing cloud computing systems. This course may be useful to you if you are interested in specializing in big data cloud computing.
Data Management Consultant
Data Management Consultant
As a Data Management Consultant, you would be responsible for advising clients on data management strategies. This course may be useful to you as it provides an overview of data management best practices.
Data Integration Specialist
Data Integration Specialist
As a Data Integration Specialist, you would be responsible for integrating data from different sources. This course may be useful to you as it provides an overview of data integration techniques.
Data Quality Analyst
Data Quality Analyst
As a Data Quality Analyst, you would be responsible for ensuring the quality of data. This course may be useful to you as it provides an overview of data cleaning and data quality management.
Business Analyst
Business Analyst
As a Business Analyst, you would be responsible for analyzing business requirements and developing solutions to improve business processes. This course may be useful to you if you are interested in specializing in data analysis or business intelligence.
Research Scientist
Research Scientist
As a Research Scientist, you would be responsible for conducting research and developing new technologies. This course may be useful to you if you are interested in specializing in big data research.
Database Administrator
Database Administrator
As a Database Administrator, you would be responsible for managing and maintaining databases. This course may be useful to you if you are interested in specializing in big data management.
Software Engineer
Software Engineer
As a Software Engineer, you would be responsible for designing, developing, and maintaining software applications. This course may be useful to you if you are interested in specializing in big data engineering or data science.
Data Governance Analyst
Data Governance Analyst
As a Data Governance Analyst, you would be responsible for developing and implementing data governance policies. This course may be helpful to you as it provides an overview of data management and governance.
For more career information including salaries, visit:
OpenCourser.com/course/6zwjhn/data
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
Data lakes and Lakehouses with Spark and Azure Databricks.
Provides a comprehensive overview of Spark. It valuable resource for anyone who wants to learn more about Spark and how to use it to solve big data problems.
Save
Great introduction to Apache Spark for beginners. It covers the basics of Spark and how to use it for data processing.
Save
Provides a comprehensive overview of Apache Spark. It covers the basics of Spark, as well as advanced topics like machine learning and graph processing.
Provides a comprehensive guide to building a data lake. It covers the steps involved in creating a data lake, from data ingestion to data processing.
Provides a non-technical introduction to data lakes. It explains what data lakes are, why they are important, and how to use them to your advantage.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/6zwjhn/data
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Effort
4 weeks
Level
Advanced
Via
Udacity
Instructors
Vishnu (Lucky) Pamula
Amanda Moran
Matt Swaffer, PhD
Language
English
Good to know
Explores Spark, Azure, Data Lakes, and Lakehouses, which are prominent in the big data industry
Taught by Vishnu (Lucky) Pamula, Amanda Moran, and Matt Swaffer, PhD, who are recognized for their work in big data and data analytics
Builds a strong foundation for beginners in big data technologies and concepts
Requires experience with programming and data analysis, which may be a caveat for learners new to these fields
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