Azure Data Engineer Associate

سرفصل های دوره

01 Introduction

001 Course Introduction

001 Study Guide.pdf

002 About the Training Architect

003 About the Exam

004 Programming Background Needed

004 database administration and sql language basics.zip

004 introduction to python scripting.zip

004 sql deep dive.zip

02 Data Engineering Crash Course

001 Section Introduction

002 The View from Mars Data Engineering at a Glance

003 What Does Azure Have to Offer

004 Introduction to Data Lakes

005 Introduction to Azure Data Factory

005 what is azure data factory.zip

006 Introduction to Azure Synapse Analytics

006 what is azure synapse analytics.zip

007 Introduction to Azure Stream Analytics

008 Introduction to Azure Databricks

008 what is azure databricks.zip

009 Section Recap

03 Data Storage

001 Section Introduction

002 Using Azure Data Lakes

003 Getting the Folder Structure Right

004 Understanding File Types

005 Partitioning Data

006 Partitioning Best Practices Part 1

007 Partitioning Best Practices Part 2

008 Distributing Data

009 Archiving Data

011 Pruning Data

012 Compressing Data

013 Sharding Data

014 Implementing Data Redundancy

016 Section Recap

04 Data Ingestion and Transformation

001 Section Introduction

002 Meeting the Tools of the Trade Azure Data Factory

003 Meeting the Tools of the Trade Transact-SQL

004 Meeting the Tools of the Trade Azure Synapse Pipelines

004 data integration in azure synapse analytics versus azure data factory.zip

005 Meeting the Tools of the Trade Scala

005 introduction to dataframes - scala.zip

006 Meeting the Tools of the Trade Apache Spark

007 Creating Data Pipelines

008 Designing and Creating Tests for Data Pipelines

009 Integrating JupyterPython Notebooks into a Data Pipeline

010 Cleansing Data

011 Splitting Data

012 Shredding JSON

013 Encoding and Decoding Data

014 Configuring Error Handling for Transformations

015 Normalizing and Denormalizing Values

016 Performing Data Exploratory Analysis

018 Section Recap

05 Batch Processing Solutions

001 Section Introduction

002 Identifying Azure Services for Batch Processing

004 Designing and Implementing Incremental Data Loads

005 Designing and Implementing Incremental Data Loads Part 2

006 Introduction to Data Factory Flow

007 Handling Schema Drift

008 Handling Duplicate and Missing Data with Data Flow

008 sample data flow scripts.zip

009 Upserting Data with Data Flow

010 Designing and Configuring Exception Handling

011 Triggering Batches

012 Implementing Azure Databricks

013 Managing Data Pipelines

014 Implementing Version Control for Pipeline Artifacts

015 Managing Spark Jobs in a Pipeline

016 Section Recap

06 Stream Processing Solutions

001 Section Introduction

002 Identifying Azure Services for Stream Processing

003 Designing a Stream Processing Solution

005 Processing Time Series Data

006 Handling Late-Arriving Data

007 Designing and Creating Windowed Aggregates Part 1

007 introduction to stream analytics windowing functions.zip

008 Designing and Creating Windowed Aggregates Part 2

009 Processing Data by Using Spark Structured Streaming

010 Monitoring for Performance and Functional Regressions

011 Processing 1 or More Partitions (Repartitioning)

012 Handling Interruptions

013 Designing and Configuring Exception Handling

014 Upserting Data

015 Replaying Archived Stream Data

016 Section Recap

07 Data Serving Layer

001 Section Introduction

002 Understanding Schema and Table Design

003 Understanding Dimensions

004 Building External Tables

005 Designing Analytical Stores

006 Designing Metastores

007 Maintaining Metadata

008 Section Recap

08 Configuring Security and Compliance

001 Section Introduction

002 Understanding Data Protection

003 Implementing Data Protection with Data Masking

004 Auditing Data

005 Configuring Data Retention

006 Purging Data Based on Business Requirements

007 Securing Azure Data Lake Through RBAC and ACLs

008 Managing Identities Keys and Secrets

009 Implementing Secure Endpoints

011 Implementing Resource Tokens in Azure Databricks

012 Managing Sensitive Information

013 Loading a DataFrame with Sensitive Information

014 Section Recap

09 Monitoring Data Storage and Data Processing

001 Section Introduction

002 Configuring Monitoring Services

003 Measuring Performance of Data Movement

004 Monitoring and Updating Statistics about Data across a System

004 more example syntax to update statistics.zip

005 Measuring Query Performance

006 Monitoring Cluster Performance

007 Understanding Custom Logging Options

008 Interpreting a Spark Directed Acyclic Graph (DAG)

009 Section Recap

10 Optimizing and Troubleshooting Data Storage and Processing

001 Section Introduction

002 Compacting Small Files

003 Rewriting User-Defined Functions

004 Handling Skew in Data

005 Handling Data Spill

006 Finding Shuffling in a Pipeline

007 Tuning Shuffle Partitions

008 Optimizing Resource Management

009 Tuning Queries by Using Cache

010 Troubleshooting a Failed Spark Job

011 Debugging Spark Jobs by Using the Spark UI

012 Optimizing Pipelines for Analytical or Transactional Purposes

014 Troubleshooting a Failed Pipeline Run

014 troubleshoot pipeline orchestration and triggers in azure data factory.zip

015 Section Recap

11 Conclusion

001 Bringing It All Together

002 Exam Tips

003 Final Notes

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تولید کننده: A Cloud Guru