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Microsoft Certified Azure Data Engineer Associate Course in Dubai

Overview of Microsoft Certified Azure Data Engineer Associate Course

Microsoft Certified Azure Data Engineer Associate Course, a candidate for the Azure Data Designer Affiliate qualification ought to have subject knowledge integrating, changing, and settling data from various structured and disorganized data systems into structures that appropriate for building analytics options.


Responsibilities for this role include assisting stakeholders understand the data via exploration, structure and also keeping safe and secure and also compliant data processing pipelines by utilizing various tools as well as methods. These expert usages various Azure data solutions and languages to keep as well as generate cleansed and improved datasets for analysis.


An Azure Information Designer also helps ensure that data pipelines, as well as data stores, are high-performing, reliable, organized, and also dependable, provided a particular set of service requirements as well as restraints. This professional deals with unanticipated concerns quickly as well as minimizes data loss. An Azure Data Engineer also develops, applies, monitors, as well as optimizes data platforms to satisfy the data pipe needs.


A prospect for this accreditation should have solid expertise of data processing languages, such as SQL, Python, or SCALA, and also they need to recognize parallel handling and information architecture patterns.

You will earn this certification if you complete one of the following options:

  • Pass DP-200 and DP-201 (retiring on June 30, 2021) or
  • Pass DP-203 (beta released February 23, 2021)

Job role: Data Engineer

Required exams: DP-203

Microsoft Certified Azure Data Engineer Associate Course Certification details

Exam DP-203: Data Engineering on Microsoft Azure

Languages: English

This exam gauges your capacity to complete the following technical jobs: layout and implement data storage space; design and establish data handling; design and also execute information security; and also keep track of as well as maximize information storage space and information handling.

Azure Information Engineers integrate, transform, and settle data from numerous organized as well as disorganized information systems right into structures that are suitable for building analytics remedies.
Candidates for Examination DP-203: Data Design on Microsoft Azure must have solid understanding of data handling languages, such as SQL, Python, or Scala, and they need to recognize parallel handling and also information design patterns.

Part of the requirements for: Microsoft Certified Azure Data Engineer Associate Course

Microsoft Certified Azure Data Engineer Associate Course Skills measured

  • Style and also implement data storage space
  • Design and also establish information handling
  • Layout as well as execute data protection
  • Display and also maximize information storage space and also information processing

Microsoft Certified Azure Data Engineer Associate

Microsoft Certified Azure Data Engineer Associate Course content

Exam DP-203: Data Engineering on Microsoft Azure

Design and Implement Data Storage (40-45%)

Design a data storage structure

  • style an Azure Information Lake solution
  • advise file types for storage
  • recommend documents kinds for analytical questions
  • style for effective querying
  • style for information pruning
  • layout a folder structure that represents the levels of data transformation
  • style a distribution method
  • style an information archiving solution

Design a partition strategy

  • design a dividers technique for files
  • style a dividers technique for analytical workloads
  • design a dividers strategy for efficiency/performance
  • style a dividers method for Azure Synapse Analytics
  • determine when partitioning is needed in Azure Data Lake Storage Space Gen2

Design the serving layer

  • style celebrity schemas
  • style slowly altering dimensions
  • design a dimensional hierarchy
  • layout a service for temporal information
  • style for step-by-step loading
  • design analytical stores
  • style megastores in Azure Synapse Analytics as well as Azure Information blocks

Implement physical data storage structures

  • execute compression
  • execute partitioning
  • execute sharing
  • carry out different table geometries with Azure Synapse Analytics pools
  • implement information redundancy
  • carry out distributions
  • carry out information archiving

Implement logical data structures

  • develop a temporal information service
  • build a gradually altering dimension
  • develop a rational folder structure
  • construct outside tables
  • execute documents as well as folder structures for effective quizzing and also data pruning

Implement the serving layer

  • provide data in a relational celebrity schema
  • deliver data in Parquet files
  • maintain metadata
  • apply a dimensional power structure

Design and Develop Data Processing (25-30%)

Ingest and transform data

  • change data by utilizing Apache Flicker
  • change information by using Transact-SQL
  • change information by using Information Manufacturing facility
  • change data by using Azure Synapse Pipelines
  • change information by utilizing Stream Analytics
  • cleanse data
  • split information
  • shred JSON
  • inscribe and also decode information
  • set up mistake dealing with for the improvement
  • normalize as well as denormalize values
  • transform information by utilizing Scala
  • carry out information exploratory evaluation

Design and develop a batch processing solution

  • create set handling services by using Information Manufacturing facility, Information Lake, Flicker, Azure Synapse Pipelines, PolyBase, and also Azure Data blocks
  • produce data pipes
  • layout and implement incremental data lots
  • design and also establish gradually changing dimensions
  • take care of safety and conformity requirements
  • scale resources
  • configure the batch dimension
  • style as well as produce tests for data pipelines
  • integrate Jupyter/IPython note pads into an information pipeline
  • manage duplicate information
  • manage missing out on information
  • deal with late-arriving data
  • insert information
  • regress to a previous state
  • layout as well as configure exception handling
  • configure set retention
  • layout a batch processing remedy
  • debug Flicker work by using the Glow UI

Design and develop a stream processing solution

  • establish a stream handling solution by using Stream Analytics, Azure Databricks, as well as Azure Event Hubs
  • process information by utilizing Flicker organized streaming
  • display for efficiency and useful regressions
  • design and develop windowed accumulations
  • handle schema drift
  • procedure time collection information
  • process throughout dividings
  • procedure within one partition
  • configure checkpoints/watermarking during processing
  • range resources
  • design and also develop tests for information pipes
  • optimize pipes for logical or transactional objectives
  • handle interruptions
  • style and set up exemption handling
  • insert information
  • replay archived stream information
  • style a stream processing remedy

Manage batches and pipelines

  • trigger batches
  • handle fell short batch lots
  • confirm batch tons
  • take care of information pipelines in Information Factory/Synapse Pipelines
  • timetable information pipelines in Information Factory/Synapse Pipelines
  • implement version control for pipe artifacts
  • handle Flicker work in a pipeline

Design and Implement Data Security (10-15%)

Design security for data policies and standards

  • design data security for information at rest and in transit
  • design a data bookkeeping method
  • layout an information masking strategy
  • layout for data personal privacy
  • design a data retention policy
  • style to purge data based on business needs
  • style Azure role-based gain access to control (Azure RBAC) and also
  • POSIX-like Accessibility Control List (ACL) for Data Lake Storage Gen2
  • design row-level and column-level protection

Implement data security

  • execute data covering up
  • encrypt information at rest as well as in motion
  • apply row-level and column-level safety and security
  • execute Azure RBAC
  • execute POSIX-like ACLs for Data Lake Storage Gen2
  • apply an information retention policy
  • execute an information bookkeeping approach
  • take care of identities, tricks, and also secrets across different data

Platform innovations

  • Implement protected endpoints (private and also public).
  • Carry out resource tokens in Azure Information bricks.
  • Load a Data Structure with sensitive info.
  • Create encrypted information to tables or Parquet data.
  • Take care of sensitive details.

Monitor and Optimize Data Storage and Data Processing (10-15%)

Monitor data storage and data processing

  • implement logging made use of by Azure Display
  • set up keeping track of solutions
  • step efficiency of data activity
  • monitor as well as upgrade data about information across a system
  • monitor data pipeline efficiency
  • procedure question performance
  • screen cluster efficiency
  • comprehend custom logging alternatives
  • schedule and monitor pipe tests
  • analyze Azure Screen metrics and logs
  • Translate a Spark directed acyclic chart (DAG).

Optimize and troubleshoot data storage and data processing

  • compact small documents
  • Revise user-defined features (UDFs).
  • Take care of skew in data.
  • Manage data spill.
  • Song shuffle partitions.
  • Find shuffling in a pipeline.
  • Maximize source monitoring.
  • tune queries by utilizing indexers
  • tune questions by using cache
  • enhance pipelines for logical or transactional objectives
  • maximize pipe for detailed versus logical workloads
  • repair a failed stimulate task
  • fix an unsuccessful pipe run

To know more on the Microsoft Certified Azure Data Engineer Associate Course official site, click here.

To know more about other courses in IT Academy, click here.

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