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Kate Sullivan
Apache Spark is one of the most widely used technologies in big data analytics. In this course, you will learn how to leverage your existing SQL skills to start working with Spark immediately. You will also learn how to work with Delta Lake, a highly performant, open-source storage layer that brings reliability to data lakes. By the end of this course, you will be able to use Spark SQL and Delta Lake to ingest, transform, and query data to extract valuable insights that can be shared with your team.
Register for this course and see more details by visiting:
OpenCourser.com/course/mixph2/apache
What's inside
Syllabus
Welcome to Apache Spark SQL for Data Analysts
An introduction to this course including learning objectives, frequently asked questions, and a chance to get to know fellow classmates.
Read more
Syllabus
Welcome to Apache Spark SQL for Data Analysts
An introduction to this course including learning objectives, frequently asked questions, and a chance to get to know fellow classmates.
Read more
Spark makes big data easy
Using Spark SQL on Databricks
Spark Under the Hood
Complex Queries
Applied Spark SQL
Data Storage and Optimization
Delta Lake with Spark SQL
SQL Coding Challenges
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by Kate Sullivan, who are recognized for their work in big data analytics
Develops foundational big data analytics skills, which are highly relevant to industry
Focuses on Spark SQL, which is a widely used technology in big data analytics
Provides hands-on experience with Apache Spark SQL and Delta Lake
Requires students to have basic SQL skills, which may be a barrier for some learners
Save this course
Save Apache Spark (TM) SQL for Data Analysts to your list so you can find it easily later:
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Reviews summary
Databricks spark sql fundamentals
Learners say that this course provides a strong foundational understanding of Apache Spark (TM) SQL for Data Analysts. It is well-received by learners, with over 80% giving it a positive rating. The course is largely hands-on, with engaging assignments and real-world examples. It is suitable for both beginners and experienced data analysts who want to learn more about Spark SQL.
Appropriate difficulty level for beginners
""Nice introduction to pySpark and databricks, as well as some advance SQL functions""
""It's a great course! Obviously, you won't master Databricks or Spark with this course alone but it is a great start!""
Structured with engaging assignments and real-world examples
""Lots of hands on opportunities.""
""Very useful course with lots of practice!""
Varying audio quality
""The material given by the databricks team was really good and helps a lot.""
""Videos are not in the highest quality, but the content is pure gold.""
Occasional mistakes in questions and code
""Final exam question 8 - question does not match answers.""
"Some textual errors and also Final exam question was asking for 'YEAR' in one place but obviously had it mixed up with 'DAY'."
Databricks software outdated or requires paid subscription
""The course seems quite promising but when you need to get hands on, one quickly realizes that content is obsolete.""
""Beware when you instantiate Databricks for this course""
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 Apache Spark (TM) SQL for Data Analysts with these
activities:
Seek Mentorship
Show steps
Identify and connect with mentors who have experience in big data analytics or Apache Spark to guide your learning and provide support.
Show steps
-
Attend industry events or online forums to meet potential mentors
-
Reach out to professionals in your field through LinkedIn or email
-
Ask for guidance and support on specific topics or projects
SQL Syntax Practice
Show steps
Solidify your understanding of Spark SQL syntax by completing practice drills and exercises.
Browse courses on
SQL Syntax
Show steps
-
Find online resources or tutorials providing SQL practice exercises
-
Solve the practice problems, focusing on correct syntax
-
Review solutions and identify areas for improvement
Guided Tutorial: Spark Datasets
Show steps
Reinforce your knowledge of representing and processing tabular data in Spark by following guided tutorials on Spark Datasets, a structured API.
Show steps
-
Find a tutorial introducing Spark Datasets
-
Follow the tutorial and apply the concepts
-
Experiment with creating and manipulating Spark Datasets
Four other activities
Expand to see all activities and additional details
Show all seven activities
Resource Compilation
Show steps
Enhance your understanding of the course materials by compiling a collection of useful resources, including articles, tutorials, documentation, and online forums.
Browse courses on
Big Data Analytics
Show steps
-
Identify relevant resources through web searches and course materials
-
Organize resources into a structured format (e.g., bookmarks, notes, or a digital repository)
-
Review and update the compilation regularly
Peer Review and Discussion
Show steps
Enhance your understanding and critical thinking skills by engaging in peer review sessions, where you exchange feedback on data analysis projects or coding exercises.
Browse courses on
Peer Review
Show steps
-
Find a study partner or group
-
Share your work and provide constructive feedback
-
Incorporate feedback to improve your own work
Data Analysis Project
Show steps
Apply your knowledge of Spark SQL by completing a data analysis project that involves gathering, cleaning, transforming, and visualizing data.
Browse courses on
Data Analysis
Show steps
-
Define a project scope and gather a dataset
-
Clean and transform the data using Spark SQL
-
Analyze the data and draw insights using Spark SQL
-
Visualize the results using a visualization tool or library
Spark SQL Challenge
Show steps
Test your skills and learn from others by participating in a Spark SQL challenge or competition.
Browse courses on
Spark SQL
Show steps
-
Find a Spark SQL challenge or competition
-
Prepare for the challenge by practicing and reviewing concepts
-
Participate in the challenge and showcase your knowledge
-
Review the results and learn from the solutions of others
Seek Mentorship
Show steps
Identify and connect with mentors who have experience in big data analytics or Apache Spark to guide your learning and provide support.
Show steps
Show steps
Show steps
- Attend industry events or online forums to meet potential mentors
- Reach out to professionals in your field through LinkedIn or email
- Ask for guidance and support on specific topics or projects
SQL Syntax Practice
Show steps
Solidify your understanding of Spark SQL syntax by completing practice drills and exercises.
Browse courses on
SQL Syntax
Show steps
Show steps
Show steps
- Find online resources or tutorials providing SQL practice exercises
- Solve the practice problems, focusing on correct syntax
- Review solutions and identify areas for improvement
Guided Tutorial: Spark Datasets
Show steps
Reinforce your knowledge of representing and processing tabular data in Spark by following guided tutorials on Spark Datasets, a structured API.
Show steps
Show steps
Show steps
- Find a tutorial introducing Spark Datasets
- Follow the tutorial and apply the concepts
- Experiment with creating and manipulating Spark Datasets
Four other activities
Expand to see all activities and additional details
Show all seven activities
Resource Compilation
Show steps
Enhance your understanding of the course materials by compiling a collection of useful resources, including articles, tutorials, documentation, and online forums.
Browse courses on
Big Data Analytics
Show steps
Show steps
Show steps
- Identify relevant resources through web searches and course materials
- Organize resources into a structured format (e.g., bookmarks, notes, or a digital repository)
- Review and update the compilation regularly
Peer Review and Discussion
Show steps
Enhance your understanding and critical thinking skills by engaging in peer review sessions, where you exchange feedback on data analysis projects or coding exercises.
Browse courses on
Peer Review
Show steps
Show steps
Show steps
- Find a study partner or group
- Share your work and provide constructive feedback
- Incorporate feedback to improve your own work
Data Analysis Project
Show steps
Apply your knowledge of Spark SQL by completing a data analysis project that involves gathering, cleaning, transforming, and visualizing data.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Define a project scope and gather a dataset
- Clean and transform the data using Spark SQL
- Analyze the data and draw insights using Spark SQL
- Visualize the results using a visualization tool or library
Spark SQL Challenge
Show steps
Test your skills and learn from others by participating in a Spark SQL challenge or competition.
Browse courses on
Spark SQL
Show steps
Show steps
Show steps
- Find a Spark SQL challenge or competition
- Prepare for the challenge by practicing and reviewing concepts
- Participate in the challenge and showcase your knowledge
- Review the results and learn from the solutions of others
Career center
Learners who complete Apache Spark (TM) SQL for Data Analysts will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use their understanding of data to help businesses make informed decisions. They use a variety of tools and techniques to collect, clean, and analyze data, and then present their findings to stakeholders in a clear and concise way. This course can help you develop the skills you need to become a successful Data Analyst, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the systems that store and process data. They work with a variety of technologies, including databases, data warehouses, and big data platforms. This course can help you develop the skills you need to become a successful Data Engineer, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Data Scientist
Data Scientist
Data Scientists use their knowledge of mathematics, statistics, and computer science to solve business problems. They use a variety of tools and techniques to collect, clean, and analyze data, and then develop models to predict future outcomes. This course can help you develop the skills you need to become a successful Data Scientist, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Database Administrator
Database Administrator
Database Administrators design, build, and maintain databases. They work with a variety of database technologies, and often specialize in a particular area, such as big data or data science. This course can help you develop the skills you need to become a successful Database Administrator, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with a variety of programming languages and technologies, and often specialize in a particular area, such as big data or data science. This course can help you develop the skills you need to become a successful Software Engineer, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Data Architect
Data Architect
Data Architects design and implement data management solutions. They work with a variety of technologies, including databases, data warehouses, and big data platforms. This course can help you develop the skills you need to become a successful Data Architect, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make informed decisions. They use a variety of tools and techniques to collect, clean, and analyze data, and then present their findings to stakeholders in a clear and concise way. This course can help you develop the skills you need to become a successful Business Intelligence Analyst, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. They work with a variety of programming languages and technologies, and often specialize in a particular area, such as big data or data science. This course can help you develop the skills you need to become a successful Machine Learning Engineer, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Statistician
Statistician
Statisticians use their knowledge of mathematics and statistics to solve problems in a variety of fields, including business, finance, and healthcare. This course can help you develop the skills you need to become a successful Statistician, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their knowledge of mathematics and statistics to solve problems in a variety of fields, including business, finance, and healthcare. This course can help you develop the skills you need to become a successful Operations Research Analyst, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Consultant
Consultant
Consultants provide advice and guidance to businesses on a variety of topics, including technology, finance, and marketing. This course can help you develop the skills you need to become a successful Consultant, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Financial Analyst
Financial Analyst
Financial Analysts use their knowledge of finance and economics to help businesses make informed decisions. This course can help you develop the skills you need to become a successful Financial Analyst, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. They work with a variety of stakeholders, including engineers, designers, and marketers. This course can help you develop the skills you need to become a successful Product Manager, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Market Research Analyst
Market Research Analyst
Market Research Analysts use their knowledge of marketing and research to help businesses understand their customers and make informed decisions. This course can help you develop the skills you need to become a successful Market Research Analyst, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
Entrepreneur
Entrepreneur
Entrepreneurs start and run their own businesses. They work in a variety of industries, including technology, finance, and healthcare. This course can help you develop the skills you need to become a successful Entrepreneur, including how to use Spark SQL and Delta Lake to ingest, transform, and query data.
For more career information including salaries, visit:
OpenCourser.com/course/mixph2/apache
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
Apache Spark (TM) SQL for Data Analysts.
An authoritative guide to Apache Spark, written by its creators. It provides a comprehensive overview of Spark's architecture, programming model, and advanced features, offering a deep understanding of the technology.
Save
A comprehensive guide to Apache Spark, covering its core concepts, programming model, and advanced techniques. It provides a solid foundation for understanding and using Spark for big data analytics.
A comprehensive guide to using Python for data analysis. It covers dataframes, data manipulation, and data visualization, providing a solid foundation for working with data in a Python environment.
A performance optimization guide for Apache Spark. It covers techniques for tuning Spark applications, optimizing data structures, and leveraging advanced features to improve the performance and efficiency of Spark programs.
A comprehensive guide to machine learning using Python. It covers supervised learning, unsupervised learning, and deep learning, providing a practical approach to building and deploying machine learning models.
A comprehensive guide to Hadoop, the distributed computing framework that underlies Spark. It provides background knowledge on Hadoop's architecture, ecosystem, and best practices, enhancing the understanding of Spark's integration with Hadoop.
A guide to data manipulation and cleaning using the Pandas library in Python. It covers dataframes, data operations, and data visualization, providing a strong foundation for working with data in a Python environment.
A guide to data visualization using Python libraries such as Matplotlib and Seaborn. It covers various chart types, data exploration, and interactive visualizations, providing insights into presenting data effectively.
A practical guide to common pitfalls and anti-patterns in SQL programming. It helps identify and avoid performance, security, and maintainability issues, improving the quality of Spark SQL queries.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/mixph2/apache
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Level
Intermediate
Via
Coursera
Institution
Databricks
Instructor
Kate Sullivan
Language
English
Transcripts
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آذربایجان دیلی
This course belongs to a
collection
called
Data Science with Databricks for Data Analysts. It's comprised of three courses:
- Applied Data Science for Data Analysts
- Apache Spark (TM) SQL for Data Analysts (viewing)
- Data Science Fundamentals for Data Analysts
Good to know
Taught by Kate Sullivan, who are recognized for their work in big data analytics
Develops foundational big data analytics skills, which are highly relevant to industry
Focuses on Spark SQL, which is a widely used technology in big data analytics
Provides hands-on experience with Apache Spark SQL and Delta Lake
Requires students to have basic SQL skills, which may be a barrier for some learners
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