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Microsoft Certified Azure Data Engineer

EXAM CODE DP-200 & DP-201

About

Azure Data Engineers design and implement the management, monitoring, security, and privacy of data using the full stack of Azure data services to satisfy business needs.

Who should take this exam?

Candidates for this exam are Microsoft Azure data engineers who collaborate with business stakeholders to identify and meet the data requirements to implement data solutions that use Azure data services.

Azure data engineers are responsible for data-related tasks that include provisioning data storage services, ingesting streaming and batch data, transforming data, implementing security requirements, implementing data retention policies, identifying performance bottlenecks, and accessing external data sources.

Candidates for this exam must be able to implement data solutions that use the following Azure services: Azure Cosmos DB, Azure SQL Database, Azure SQL Data Warehouse, Azure Data Lake Storage, Azure Data Factory, Azure Stream Analytics, Azure Databricks, and Azure Blob storage.

Benefits of training with us

  • Intuitive and rewarding online training resources

  • 24/7 access to our unique course materials

  • Custom built practical tasks and challenges
  • Official mock examinations to fully prepare you for any final exams
  • Career advice and CV support once training has been completed
  • Full printable course materials, allowing you take your learning offline at your own convenience

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Notice of planned skills update
Exam DP-200 Update Summary
  • This exam has been refocused to differentiate the data engineer from a database administrator, emphasizing the data engineer's proficiency in implementing solutions for data storage in varying forms, structures, and purpose.
Updated content areas (effective June 21, 2019)
  • Reorganized implementation of data storage solutions to two key categories: relational and non-relational data stores

  • Removed focus on HDInsight

  • Merged monitoring and optimization

  • Reduced focus on Hybrid data scenarios

  • Removed Azure DevOps pipelines

  • Referenced authentication and authorization as applicable

  • Referenced data policies and standards as applicable

  • Referenced notifications as applicable

Implement data storage solutions (40-45%)
Implement non-relational data stores
  • Referenced data policies and standards as applicable

  • implement data distribution and partitions

  • implement a consistency model in CosmosDB

  • provision a non-relational data store

  • provide access to data to meet security requirements

  • implement for high availability, disaster recovery, and global distribution
Implement relational data stores
  • configure elastic pools

  • configure geo-replication

  • provide access to data to meet security requirements

  • implement for high availability, disaster recovery, and global distribution

  • implement data distribution and partitions for SQL Data Warehouse

  • Implement PolyBase
Manage data security
  • implement data masking

  • encrypt data at rest and in motion

Manage and develop data processing (25-30%)
Develop batch processing solutions
  • develop batch processing solutions by using Data Factory and Azure Databricks

  • ingest data by using PolyBase

  • implement the integration runtime for Data Factory

  • create linked services and datasets

  • create pipelines and activities

  • create and schedule triggers

  • implement Azure Databricks clusters, notebooks, jobs, and autoscaling

  • ingest data into Azure Databricks
Develop streaming solutions
  • configure input and output

  • select the appropriate windowing functions

  • implement event processing using Stream Analytics

Monitor and optimize data solutions (30-35%)
Monitor data storage
  • monitor relational and non-relational data sources

  • implement BLOB storage monitoring

  • implement Data Lake Store monitoring

  • implement SQL Database monitoring

  • implement SQL Data Warehouse monitoring

  • implement Cosmos DB monitoring

  • configure Azure Monitor alerts

  • implement auditing by using Azure Log Analytics
Monitor data processing
  • design and implement Data Factory monitoring

  • monitor Azure Databricks

  • monitor HDInsight processing

  • monitor stream analytics
Optimize Azure data solutions
  • troubleshoot data partitioning bottlenecks

  • optimize Data Lake Storage

  • optimize Stream Analytics

  • optimize SQL Data Warehouse

  • optimize SQL Database

  • manage data life cycle

  • Official Microsoft DP-200 & DP-201 Exam

  • Online or classroom training

  • Interactive mock exams

  • Live Lab (access to LIVE software)

  • Free Phone Support

  • Online & Email Support

  • World wide Recognised Qualification

  • Unlimited access for 12 months
  • Data Engineer

  • Research Data Science Engineer

  • Premier Field Engineer

  • Support Engineer

  • Azure Data & AI Specialist

  • Specialist - Data/AI Solutions

  • + More

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