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Mohit Batra

In this course, you'll learn about Delta Lake using Azure Databricks and its ecosystem – Delta Lake Storage, Delta Engine, Delta Architecture, Delta Live Tables, etc. – and how it provides warehouse-like features that you can use to build a Lakehouse.

Delta Lake is an open-source storage layer that brings reliability to Data Lakes, by providing data warehouse-like features, on top of Data Lake.

Read more

In this course, you'll learn about Delta Lake using Azure Databricks and its ecosystem – Delta Lake Storage, Delta Engine, Delta Architecture, Delta Live Tables, etc. – and how it provides warehouse-like features that you can use to build a Lakehouse.

Delta Lake is an open-source storage layer that brings reliability to Data Lakes, by providing data warehouse-like features, on top of Data Lake.

It has a big ecosystem, and there are various tools and architectures based on that - Delta Lake Storage, Delta Engine, Delta Architecture, Delta Live Tables, Delta Sharing, etc. It can also handle Batch and Streaming data seamlessly. And these components and features can you help build an optimized, and well-integrated Lakehouse architecture.

In this course, Delta Lake with Azure Databricks: Deep Dive, you’ll learn how Delta Lake and various components in its ecosystem, allows us to build a Lakehouse architecture. And to do that, we will be using Azure Databricks.

First, you’ll learn what Delta Lake is, and how it works. You’ll also see the different components in its ecosystem. Then, you’ll discover how to work with Delta Lake storage and its various features. Next, you’ll see how to handle streaming data on Delta Lake. After, you’ll explore Delta Engine in Databricks to optimize storage and queries. Followed by this, you’ll see how to build a Lakehouse architecture. And you’ll also see how to build reliable ETL pipelines with Delta Live Tables. Finally, you’ll end with some common use cases, and how to implement them. By the end of this course, you’ll have the knowledge and skills to work with Delta Lake and use its ecosystem components to build an optimized, well-integrated Lakehouse solution.

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What's inside

Syllabus

Course Overview
Getting Started with Delta Lake
Working with Delta Lake Storage
Handling Streaming Data on Delta Lake
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Optimizing with Delta Engine in Databricks
Building a Lakehouse Architecture
Building ETL Pipelines with Delta Live Tables
Implementing Common Use Cases

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops skills and knowledge that are standard in the industry
Taught by experts recognized for their work in the field
Emphasizes project-based learning
Requires significant experience in the field
May require learners to purchase additional materials

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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 Delta Lake with Azure Databricks: Deep Dive with these activities:
Set up Azure Databricks and Delta Lake environment
Build a solid foundation by setting up your Azure Databricks and Delta Lake environment before starting the course.
Show steps
  • Follow Azure Databricks documentation to create an account and workspace.
  • Install the Delta Lake library and configure it with your Databricks workspace.
  • Create a Delta Lake table and load sample data.
Review Delta Lake Concepts
Revisit the core concepts of Delta Lake to strengthen the foundation for the course.
Browse courses on Data Lakehouse
Show steps
  • Read through the Delta Lake documentation
  • Review online tutorials on Delta Lake basics
Review Data Lake fundamentals
Reinforce your understanding of Data Lake concepts and architectures to prepare for this course's more advanced topics.
Browse courses on Data Lake
Show steps
  • Revisit the concepts of Data Lake and its components.
  • Review the pros and cons of Data Lakes compared to traditional data warehouses.
  • Explore various Data Lake architectures and their applications.
11 other activities
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Join a Delta Lake Study Group
Enhance your learning through discussions and collaboration with peers who are also interested in Delta Lake.
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Show steps
  • Find or create a Delta Lake study group
  • Meet regularly to discuss course materials
  • Share knowledge and assist each other with challenges
Work through Delta Lake code examples
Solidify your understanding of Delta Lake concepts by practicing with code examples.
Show steps
  • Explore the Delta Lake documentation for code examples.
  • Set up a coding environment to experiment with the code examples.
  • Modify and execute the code examples to observe different behaviors.
Practice Delta Lake Commands
Reinforce your understanding of Delta Lake commands through hands-on practice.
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Show steps
  • Create a Delta Lake table using Azure Databricks
  • Execute SQL queries on the Delta Lake table
  • Optimize Delta Lake queries
Summarize Delta Lake storage features
Reinforce your understanding by creating a summary of Delta Lake storage features.
Show steps
  • Review the documentation on Delta Lake storage features.
  • Create a bulleted list or table summarizing the key features.
  • Explain the benefits and use cases of each feature.
Follow Delta Lake Tutorials
Enhance your knowledge of Delta Lake by following structured tutorials and applying the concepts in practice.
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Show steps
  • Find online tutorials that cover advanced Delta Lake topics
  • Follow the tutorials step-by-step and implement the concepts in Azure Databricks
Participate in a Delta Lake discussion group
Connect with other learners and discuss Delta Lake concepts and best practices.
Show steps
  • Join or create a Delta Lake discussion group or forum.
  • Ask questions, share insights, and collaborate on solving problems.
  • Stay active in the group and contribute to the discussions.
Create a Delta Lake Blog Post
Solidify your understanding of Delta Lake by creating a blog post that explains its key concepts and applications.
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Show steps
  • Choose a specific topic related to Delta Lake
  • Research and gather information from credible sources
  • Write a well-structured blog post that covers the topic in depth
  • Publish the blog post on a relevant platform
Build a mini Lakehouse project
Demonstrate your understanding by building a small-scale Lakehouse project that incorporates Delta Lake.
Show steps
  • Design the architecture of your mini Lakehouse.
  • Implement data ingestion, storage, and querying using Delta Lake.
  • Evaluate the performance and scalability of your Lakehouse.
Participate in a Delta Lake Hackathon
Put your Delta Lake skills to the test by participating in a hackathon and solving real-world data challenges.
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Show steps
  • Find a suitable Delta Lake hackathon
  • Form a team or work individually
  • Develop an innovative solution using Delta Lake
  • Submit your project and compete for prizes
Contribute to Delta Lake open-source community
Enhance your understanding of Delta Lake by contributing to its open-source community.
Show steps
  • Explore the Delta Lake GitHub repository.
  • Identify areas where you can contribute, such as bug reporting, documentation improvement, or code contributions.
  • Submit your contributions and engage with the community.
Develop a data analytics solution using Delta Lake
Apply your knowledge by developing a real-world data analytics solution that leverages Delta Lake.
Show steps
  • Identify a business problem or opportunity that can be addressed with data analytics.
  • Design and implement a data analytics solution using Delta Lake for data storage, processing, and analysis.
  • Evaluate the results and identify areas for improvement.

Career center

Learners who complete Delta Lake with Azure Databricks: Deep Dive will develop knowledge and skills that may be useful to these careers:
Data Engineer
A Data Engineer designs and builds data pipelines for a company. They integrate and manage data from various sources, ensuring that it is accurate, consistent, and accessible to end-users. The course 'Delta Lake with Azure Databricks: Deep Dive' provides a comprehensive overview of Delta Lake, an open-source storage layer that brings reliability to Data Lakes. By learning about Delta Lake and its ecosystem components, you will gain the skills and knowledge necessary to build a well-integrated Lakehouse architecture, a key component of modern data engineering. With a fit score of 90, this course is highly recommended for aspiring Data Engineers.
Data Analyst
A Data Analyst is responsible for collecting, analyzing, and interpreting data to derive insights and make recommendations for businesses. The course 'Delta Lake with Azure Databricks: Deep Dive' provides a solid foundation in working with Delta Lake, a technology that enables efficient and reliable data analysis. By learning about Delta Lake Storage and its features, you will gain the skills to handle large datasets and perform complex data transformations. With a fit score of 80, this course is highly recommended for aspiring Data Analysts who want to enhance their data analysis capabilities.
Data Scientist
A Data Scientist leverages data to build models and create solutions that address business problems. The course 'Delta Lake with Azure Databricks: Deep Dive' provides a strong foundation in working with Delta Lake, a technology that simplifies data management and enables scalable data science. By learning about Delta Lake Storage, Delta Engine, and Delta Live Tables, you will gain the skills to handle large and complex datasets, perform efficient data transformations, and build machine learning models. With a fit score of 75, this course is highly recommended for aspiring Data Scientists who want to enhance their data engineering skills.
Data Architect
A Data Architect designs and implements data management solutions that meet the needs of an organization. The course 'Delta Lake with Azure Databricks: Deep Dive' provides a comprehensive overview of Delta Lake, a technology that enables building scalable and reliable data architectures. By learning about Delta Lake Storage, Delta Engine, and Delta Live Tables, you will gain the skills to design and implement data management solutions that leverage the latest technologies. With a fit score of 70, this course is highly recommended for aspiring Data Architects who want to enhance their data architecture skills.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. While the course 'Delta Lake with Azure Databricks: Deep Dive' is not directly focused on software engineering, it may be useful for Software Engineers who want to gain a deeper understanding of data management and data engineering principles. By learning about Delta Lake Storage, Delta Engine, and Delta Live Tables, you will gain the skills to build more efficient and scalable software applications that leverage data. With a fit score of 60, this course may be useful for Software Engineers who want to expand their skillset.
Database Administrator
A Database Administrator manages and maintains databases to ensure that they are running smoothly and efficiently. The course 'Delta Lake with Azure Databricks: Deep Dive' provides a solid foundation in working with Delta Lake, a technology that simplifies database management and enables scalable data storage. By learning about Delta Lake Storage, Delta Engine, and Delta Live Tables, you will gain the skills to manage and maintain databases more efficiently. With a fit score of 50, this course may be helpful for aspiring Database Administrators who want to enhance their data management skills.
Cloud Architect
A Cloud Architect designs and implements cloud computing solutions that meet the needs of an organization. The course 'Delta Lake with Azure Databricks: Deep Dive' provides a solid foundation in working with Delta Lake, a technology that enables building scalable and reliable data architectures in the cloud. By learning about Delta Lake Storage, Delta Engine, and Delta Live Tables, you will gain the skills to design and implement cloud computing solutions that leverage the latest technologies. With a fit score of 40, this course may be useful for aspiring Cloud Architects who want to enhance their data architecture skills.
Business Analyst
A Business Analyst identifies and analyzes business needs and develops solutions to improve business processes. While the course 'Delta Lake with Azure Databricks: Deep Dive' is not directly focused on business analysis, it may be useful for Business Analysts who want to gain a deeper understanding of data management and data analysis principles. By learning about Delta Lake Storage, Delta Engine, and Delta Live Tables, you will gain the skills to analyze data more efficiently and make better recommendations for improving business processes. With a fit score of 30, this course may be useful for Business Analysts who want to expand their skillset.
Data Warehouse Engineer
A Data Warehouse Engineer designs and implements data warehouse solutions that meet the needs of an organization. The course 'Delta Lake with Azure Databricks: Deep Dive' provides a strong foundation in working with Delta Lake, a technology that simplifies data warehouse management and enables scalable data storage. By learning about Delta Lake Storage, Delta Engine, and Delta Live Tables, you will gain the skills to design and implement data warehouse solutions that leverage the latest technologies. With a fit score of 25, this course may be useful for aspiring Data Warehouse Engineers who want to enhance their data management skills.
Data Lake Architect
A Data Lake Architect designs and implements data lake solutions that meet the needs of an organization. The course 'Delta Lake with Azure Databricks: Deep Dive' provides a comprehensive overview of Delta Lake, a technology that enables building scalable and reliable data lakes. By learning about Delta Lake Storage, Delta Engine, and Delta Live Tables, you will gain the skills to design and implement data lake solutions that leverage the latest technologies. With a fit score of 20, this course may be useful for aspiring Data Lake Architects who want to enhance their data architecture skills.

Reading list

We've selected three 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 Delta Lake with Azure Databricks: Deep Dive.
Is the definitive guide to Apache Spark. It provides a comprehensive overview of the Spark ecosystem, including Spark Core, Spark SQL, and Spark Streaming.
Provides a comprehensive overview of data warehousing. It covers all the key concepts, including data modeling, data integration, and data analysis.

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