Data Engineering with Spark Databricks Delta Lake Lakehouse

Data Engineering with Spark Databricks Delta Lake Lakehouse, available at $44.99, has an average rating of 4.35, with 28 lectures, based on 192 reviews, and has 2225 subscribers.

You will learn about Acquiring the necessary skills to qualify for an entry-level Data Engineering position Developing a practical comprehension of Data Lakehouse concepts through hands-on experience Learning to operate a Delta table by accessing its version history, recovering data, and utilizing time travel functionality Optimizing a delta table with various techniques like caching, partitioning, and z-ordering for faster analytics Obtaining practical knowledge in constructing a data pipeline through the usage of Apache Spark on the Databricks platform Doin analytics within a Databricks AWS Account This course is ideal for individuals who are Data Engineering beginners It is particularly useful for Data Engineering beginners.

Enroll now: Data Engineering with Spark Databricks Delta Lake Lakehouse

Summary

Title: Data Engineering with Spark Databricks Delta Lake Lakehouse

Price: $44.99

Average Rating: 4.35

Number of Lectures: 28

Number of Published Lectures: 28

Number of Curriculum Items: 28

Number of Published Curriculum Objects: 28

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Acquiring the necessary skills to qualify for an entry-level Data Engineering position

Developing a practical comprehension of Data Lakehouse concepts through hands-on experience

Learning to operate a Delta table by accessing its version history, recovering data, and utilizing time travel functionality

Optimizing a delta table with various techniques like caching, partitioning, and z-ordering for faster analytics

Obtaining practical knowledge in constructing a data pipeline through the usage of Apache Spark on the Databricks platform

Doin analytics within a Databricks AWS Account

Who Should Attend

Data Engineering beginners

Target Audiences

Data Engineering beginners

Data Engineering is a vital component of modern data-driven businesses. The ability to process, manage, and analyze large-scale data sets is a core requirement for organizations that want to stay competitive. In this course, you will learn how to build a data pipeline using Apache Spark on Databricks’ Lakehouse architecture. This will give you practical experience in working with Spark and Lakehouse concepts, as well as the skills needed to excel as a Data Engineer in a real-world environment.

Throughout the Course, You Will Learn:

Conducting analytics using Python and Scala with Spark.

Applying Spark SQL and Databricks SQL for analytics.

Developing a data pipeline with Apache Spark.

Becoming proficient in Databricks’ community edition.

Managing a Delta table by accessing version history, restoring data, and utilizing time travel features.

Optimizing query performance using Delta Cache.

Working with Delta Tables and Databricks File System.

Gaining insights into real-world scenarios from experienced instructors.

Course Structure:

Beginning with familiarizing yourself with Databricks’ community edition and creating a basic pipeline using Spark.

Progressing to more complex topics after gaining comfort with the platform.

Learning analytics with Spark using Python and Scala, including Spark transformations, actions, joins, Spark SQL, and DataFrame APIs.

Acquiring the knowledge and skills to operate a Delta table, including accessing its version history, restoring data, and utilizing time travel functionality using Spark and Databricks SQL.

Understanding how to use Delta Cache to optimize query performance.

Optional Lectures on AWS Integration:

‘Setting up Databricks Account on AWS’ and ‘Running Notebooks Within a Databricks AWS Account.’

Building an ETL pipeline with Delta Live Tables

Providing additional opportunities to explore Databricks within the AWS ecosystem.

This course is designed for Data Engineering beginners with no prior knowledge of Python and Scala required. However, some familiarity with databases and SQL is necessary to succeed in this course. Upon completion, you will have the skills and knowledge required to succeed in a real-world Data Engineer role.

Throughout the course, you will work with hands-on examples and real-world scenarios to apply the concepts you learn. By the end of the course, you will have the practical experience and skills required to understand Spark and Lakehouse concepts, and to build a scalable and reliable data pipeline using Apache Spark on Databricks’ Lakehouse architecture.

Course Curriculum

Chapter 1: Introduction and building a simple pipeline

Lecture 1: Introduction

Lecture 2: Data Engineering with Spark

Lecture 3: What is Databricks

Lecture 4: Creating a Databricks Community Edition account

Lecture 5: Building a basic data pipeline

Lecture 6: Reading data from DBFS and Delta Tables

Lecture 7: Writing data to DBFS and Delta tables

Lecture 8: Exporting and importing Notebooks

Lecture 9: Revisiting the basic data pipeline

Chapter 2: Data Engineering with Apache Spark

Lecture 1: More Transformations and Actions using PySpark

Lecture 2: Doing the Transformations in Scala

Lecture 3: Python Scala crash course

Lecture 4: Spark User Defined Functions (UDF)

Lecture 5: Joining Datasets using DataFrame APIs and Spark SQL

Lecture 6: More join operations using Spark

Lecture 7: Section summary

Chapter 3: Dat Lakehouse Delta Lake and Delta Tables deep dive

Lecture 1: Understanding Data Warehouse, Data Lake and Data Lakehouse

Lecture 2: Databricks Lakehouse Architecture and Delta Lake

Lecture 3: Delta Tables

Lecture 4: Storing data in a Delta table, Databricks SQL and time travel

Lecture 5: Databricks SQL vs Spark SQL

Lecture 6: Delta Table caching

Lecture 7: Delta Table partitioning

Lecture 8: Delta Table Z-ordering

Chapter 4: Databricks Labs on AWS and Conclusion

Lecture 1: Setting up Databricks account on AWS

Lecture 2: Running Notebooks Within a Databricks AWS Account

Lecture 3: Building an ETL pipeline with Delta Live Tables

Lecture 4: Cancelling Databricks 14-day free trial on AWS

Instructors

FutureX Skills
Empowering Data Engineers and Data Scientists

Rating Distribution

1 stars: 2 votes

2 stars: 3 votes

3 stars: 21 votes

4 stars: 73 votes

5 stars: 93 votes

Frequently Asked Questions

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