| 11.More Transformations and Actions using PySpark.mp4 | 74.2 MB | ||
| 12-Resources | |||
| 12.Doing the Transformations in Scala.mp4 | 59.5 MB | ||
| 13-Resources | |||
| 13.Python Scala crash course.mp4 | 32.9 MB | ||
| 14-Resources | |||
| 14.Spark User Defined Functions (UDF).mp4 | 218.8 MB | ||
| 15-Resources | |||
| 15.Joining Datasets using DataFrame APIs and Spark SQL.mp4 | 213.3 MB | ||
| 16-Resources | |||
| 16.More join operations using Spark.mp4 | 51.5 MB | ||
| 17.Section summary.mp4 | 5.5 MB | ||
| Chapter 4_Dat Lakehouse Delta Lake and Delta Tables deep dive | |||
| 18.Understanding Data Warehouse, Data Lake and Data Lakehouse.mp4 | 21.4 MB | ||
| 19.Databricks Lakehouse Architecture and Delta Lake.mp4 | 13.2 MB | ||
| 20.Delta Tables.mp4 | 3.2 MB | ||
| 21-Resources | |||
| 21.Storing data in a Delta table, Databricks SQL and time travel.mp4 | 147.2 MB | ||
| 22-Resources | |||
| 22.Databricks SQL vs Spark SQL.mp4 | 73.8 MB | ||
| 23-Resources | |||
| 23.Delta Table caching.mp4 | 150.8 MB | ||
| 24-Resources | |||
| 24.Delta Table partitioning.mp4 | 91.3 MB | ||
| 25-Resources | |||
| 25.Delta Table Z-ordering.mp4 | 27.6 MB | ||
| Chapter 5_Databricks Labs on AWS | |||
| 26.AWS Account Creation.mp4 | 29.7 MB | ||
| 27.Setting up Databricks account on AWS.mp4 | 56.8 MB | ||
| 28-Resources | |||
| 28.Running Notebooks Within a Databricks AWS Account.mp4 | 209.1 MB | ||
| 29-Resources | |||
| 29.Building an ETL pipeline with Delta Live Tables.mp4 | 174.1 MB | ||
| Chapter 6_Bonus Section - AWS Data Engineering Labs | |||
| 30.AWS Identity and Access Management (IAM).mp4 | 104 MB | ||
| 31.Understanding AWS Glue.mp4 | 3.8 MB | ||
| 32.Lab - Creating a data catalog in Glue and viewing data in Athena.mp4 | 83.3 MB | ||
| 33.Lab - Running an ETL job using Glue.mp4 | 81.5 MB | ||
| 34.Understanding Amazon EventBridge.mp4 | 7.3 MB | ||
| 35.Lab - Triggering SNS Notification for S3 Upload Event using EventBridge.mp4 | 32.5 MB | ||
| 36.Understanding AWS Step Functions.mp4 | 5.2 MB | ||
| 37.Lab - Orchestrating Lambda functions with Step Functions State Machine.mp4 | 73.5 MB | ||
| 38.Lab - ETL Workflow Orchestration with AWS Glue Lambda EventBridge Step Functions.mp4 | 134.9 MB | ||
| 39.Understanding Kinesis Data Stream.mp4 | 20.7 MB | ||
| 40.Lab - Storing and Retrieving Data from a Kinesis Data Stream Using AWS CLI.mp4 | 87 MB | ||
| 41.Lab - Kinesis Data Stream Python Boto3 Producer & Consumer.mp4 | 76.6 MB | ||
| 42.Lab - Writing simulated weather data from a Kinesis Stream to S3 with AWS Lambda.mp4 | 63.4 MB | ||
| 43.Getting Started with AWS EC2 _ The Foundation for Amazon EMR.mp4 | 51.6 MB | ||
| 44.Lab - Running Spark transformation jobs using Amazon EMR on EC2.mp4 | 59.6 MB | ||
| 45.Understanding Amazon Redshift.mp4 | 2.3 MB | ||
| 46.Lab - Creating a Data Warehouse on S3 data using Amazon Redshift.mp4 | 182.7 MB | ||
| 47.AWS Glue DataBrew_ No-Code Data Transformation.mp4 | 119.2 MB | ||
| Chapter 7_Conclusion and where to go from here_ | |||
| 48-Resources | |||
| other_courses_resources.txt.zip | 1.1 KB | ||
| futurex-dlt-sql-demo.zip | 614.4 B | ||
| aws-labs.zip | 65.4 KB | ||
| delta_table_paritioning_zordering.zip | 13.7 KB | ||
| delta_table_paritioning.zip | 10.8 KB | ||
| delta_table_caching.zip | 7.7 KB | ||
| databricks_sql.zip | 3.6 KB | ||
| spark_transformations_python_sql.zip | 6.5 KB | ||
| spark_joins.zip | 5.2 KB | ||
| store_customers_transactions.zip | 817.4 KB | ||
| spark_joins_1.zip | 5.2 KB | ||
| store_customers_transactions_1.zip | 817.4 KB | ||
| fx_udf.ipynb.zip | 9.8 KB | ||
| python_scala_crash_course.zip | 3.1 KB | ||
| scala_transformations.zip | 614.4 B | ||
| 48.Where to go from here_.mp4 | 8.6 MB | ||
| Chapter 1_Introduction | |||
| 1.Introduction.mp4 | 52.4 MB | ||
| 2.Data Engineering with Spark.mp4 | 12.9 MB | ||
| 3.What is Databricks.mp4 | 7.1 MB | ||
| Chapter 2_Working with Databricks Storage_ DBFS, Volumes, and Delta Tables | |||
| 10.Important_ Interface Differences Between Databricks Editions.mp4 | 16.9 MB | ||
| 4.Getting Started with Databricks Free Edition.mp4 | 26.5 MB | ||
| 5-Resources | |||
| 5.Working with Unity Catalog and Delta Tables.mp4 | 74.4 MB | ||
| 6-Resources | |||
| 6.Exploring DBFS and dbutils - Working with Sample Datasets.mp4 | 59.6 MB | ||
| 7-Resources | |||
| 7.Unity Catalog Volumes - File Storage and Operations.mp4 | 126.8 MB | ||
| 8-Resources | |||
| 8.Using Generative AI in Databricks for Data Transformation and Querying.mp4 | 15 MB | ||
| 9.No-Code Data Engineering with Databricks Generative AI.mp4 | 21.8 MB | ||
| Chapter 3_Data Engineering with Apache Spark | |||
| 11-Resources | |||
| spark_transformations_python.zip | 2.5 KB | ||
| read_from_db_write_to_delta.ipynb | 31.6 KB | ||
| databricks_volume_demo.ipynb | 28.3 KB | ||
| fx-dbfs-demo.ipynb.zip | 538.7 KB | ||
| delta_unity.zip | 6.1 KB |
Requirements:
Some understanding of Database and SQL queries
Description:
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' free edition.
Managing a Delta table by accessing version history, restoring data, and utilizing time travel features.
Unity Catalog Volumes - File Storage and Operations
Optimizing query performance using Delta Cache.
Working with Delta Tables and Databricks File System.
Gaining insights into real-world scenarios from experienced instructors.
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