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[ DevCourseWeb com ] PluralSight - Building Batch Data Pipelines on Google Cloud (2023)
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03. Executing Spark on Dataproc
01. Optimizing Dataproc.mp4
01. Optimizing Dataproc.vtt
02. The Hadoop ecosystem.mp4
02. The Hadoop ecosystem.vtt
03. Optimizing Dataproc monitoring.mp4
03. Optimizing Dataproc monitoring.vtt
04. Running Hadoop on Dataproc.mp4
04. Running Hadoop on Dataproc.vtt
05. Pluralsight - Getting Started with GCP and Qwiklabs.mp4
05. Pluralsight - Getting Started with GCP and Qwiklabs.vtt
07. Cloud Storage instead of HDFS.mp4
07. Cloud Storage instead of HDFS.vtt
08. Lab Intro - Running Apache Spark jobs on Dataproc.mp4
08. Lab Intro - Running Apache Spark jobs on Dataproc.vtt
09. Optimizing Dataproc storage.mp4
09. Optimizing Dataproc storage.vtt
10. Optimizing Dataproc templates and autoscaling.mp4
10. Optimizing Dataproc templates and autoscaling.vtt
11. Module introduction.mp4
11. Module introduction.vtt
12. Summary.mp4
12. Summary.vtt
04. Serverless Data Processing with Dataflow
01. Creating and re-using pipeline templates.mp4
01. Creating and re-using pipeline templates.vtt
02. Module introduction.mp4
02. Module introduction.vtt
03. Aggregate with GroupByKey and Combine.mp4
03. Aggregate with GroupByKey and Combine.vtt
07. Lab Intro - MapReduce in Beam.mp4
07. Lab Intro - MapReduce in Beam.vtt
08. Summary.mp4
08. Summary.vtt
09. Lab Intro - Building a Simple Dataflow Pipeline.mp4
09. Lab Intro - Building a Simple Dataflow Pipeline.vtt
10. Why customers value Dataflow.mp4
10. Why customers value Dataflow.vtt
11. Introduction to Dataflow.mp4
11. Introduction to Dataflow.vtt
12. Side inputs and windows of data.mp4
12. Side inputs and windows of data.vtt
13. Lab Intro - Practicing Pipeline Side Inputs.mp4
13. Lab Intro - Practicing Pipeline Side Inputs.vtt
14. Key considerations with designing pipelines.mp4
14. Key considerations with designing pipelines.vtt
15. Building Dataflow pipelines in code.mp4
15. Building Dataflow pipelines in code.vtt
16. Transforming data with PTransforms.mp4
16. Transforming data with PTransforms.vtt
05. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer
01. Module introduction.mp4
01. Module introduction.vtt
02. Orchestrate work between Google Cloud services with Cloud Co.mp4
02. Orchestrate work between Google Cloud services with Cloud Co.vtt
03. Apache Airflow environment.mp4
03. Apache Airflow environment.vtt
04. Lab Intro - Building and executing a pipeline graph in Cloud.mp4
04. Lab Intro - Building and executing a pipeline graph in Cloud.vtt
05. Monitoring and Logging.mp4
05. Monitoring and Logging.vtt
06. DAGs and Operators.mp4
06. DAGs and Operators.vtt
07. Cloud Data Fusion UI.mp4
07. Cloud Data Fusion UI.vtt
08. Explore data using wrangler.mp4
08. Explore data using wrangler.vtt
09. Lab Intro - An Introduction to Cloud Composer.mp4
09. Lab Intro - An Introduction to Cloud Composer.vtt
10. Components of Cloud Data Fusion.mp4
10. Components of Cloud Data Fusion.vtt
11. Introduction to Cloud Data Fusion.mp4
11. Introduction to Cloud Data Fusion.vtt
14. Build a pipeline.mp4
14. Build a pipeline.vtt
15. Workflow scheduling.mp4
15. Workflow scheduling.vtt
1. Introduction
1. Course Introduction.mp4
1. Course Introduction.vtt
2. Introduction to Building Batch Data Pipelines
1. Quality considerations.mp4
1. Quality considerations.vtt
2. Module introduction.mp4
2. Module introduction.vtt
3. How to carry out operations in BigQuery.mp4
3. How to carry out operations in BigQuery.vtt
4. EL, ELT, ETL.mp4
4. EL, ELT, ETL.vtt
5. Shortcomings.mp4
5. Shortcomings.vtt
6. ETL to solve data quality issues.mp4
6. ETL to solve data quality issues.vtt
6. Course Summary
1. Course Summary.mp4
1. Course Summary.vtt
Bonus Resources.txt
playlist.m3u
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