DP-203 : Data Engineering on Microsoft Azure Training

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Multisoft Systems is offering project-driven training on DP-203 : Data Engineering on Microsoft Azure. Ideal for Data architects, Data analysts who are responsible for building Microsoft Azure, Data scientists who work with analytical solutions, and Business intelligence professionals who want to learn data engineering, the offered course tells how to run interactive queries using serverless SQL pools and how to describe big data engineering with Apache Spark in Azure Synapse Analytics. You will get to know the methodologies of creating real-time analytical systems and the technologies that are used to ingest data.

Our offered course demands in-depth knowledge of cloud computing, core data concepts, and experience with data solutions. Multisoft insists you pursue this course after you have earned the AZ-900 - Azure Fundamentals and DP-900 - Microsoft Azure Data Fundamentals courses.

DP-203 Data Engineering on Microsoft Azure Course Objectives:
  • How to run interactive queries using serverless SQL pools?
  • How to transform data with Azure Data Factory or Azure Synapse Pipelines?
  • How to perform real-time Stream Processing with Stream Analytics?
  • How to integrate Data from Notebooks with Azure Synapse Pipelines or Azure Data Factory?
  • How to describe big data engineering with Apache Spark in Azure Synapse Analytics?
  • How to transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics?
  • How to perform data Exploration and Transformation in Azure Databricks?
  • How to create metadata objects in Azure Synapse serverless SQL pools
  • How to secure data and manage users in Azure Synapse serverless SQL pools?
  • How to work with DataFrames advanced methods in Azure Databricks?
  • How to perform end-to-end security with Azure Synapse Analytics?
  • How to ingest and load Data into the Data Warehouse?
DP-203 Data Engineering on Microsoft Azure Online Training
  • 32 Hrs. Instructor-led Online Training
  • Recorded Videos After Training
  • Digital Learning Material
  • Course Completion Certificate
  • Lifetime e-Learning Access
  • 24x7 After Training Support
Target audience
  • Data architects
  • Data professionals
  • Business intelligence professionals who want to learn data engineering
  • Data analysts who are responsible for building Microsoft Azure
  • Data scientists who work with analytical solutions
DP-203 Data Engineering on Microsoft Azure Course Prerequisites
  • You need to have in-depth knowledge of cloud computing to pursue this DP-203: Data Engineering on Microsoft Azure Online Training. Knowing core data concepts and having professional experience with data solutions are necessary for earning this course.
  • AZ-900 - Azure Fundamentals
  • DP-900 - Microsoft Azure Data Fundamentals
DP-203 Data Engineering on Microsoft Azure Course Certification
  • Multisoft Systems will provide you with a training completion certificate after completing the DP-203: Data Engineering on Microsoft Azure Training.

Multisoft Systems is offering project-driven training on DP-203 : Data Engineering on Microsoft Azure. Ideal for Data architects, Data analysts who are responsible for building Microsoft Azure, Data scientists who work with analytical solutions, and Business intelligence professionals who want to learn data engineering, the offered course tells how to run interactive queries using serverless SQL pools and how to describe big data engineering with Apache Spark in Azure Synapse Analytics. You will get to know the methodologies of creating real-time analytical systems and the technologies that are used to ingest data.

Our offered course demands in-depth knowledge of cloud computing, core data concepts, and experience with data solutions. Multisoft insists you pursue this course after you have earned the AZ-900 - Azure Fundamentals and DP-900 - Microsoft Azure Data Fundamentals courses.

DP-203 Data Engineering on Microsoft Azure Course Objectives:
  • How to run interactive queries using serverless SQL pools?
  • How to transform data with Azure Data Factory or Azure Synapse Pipelines?
  • How to perform real-time Stream Processing with Stream Analytics?
  • How to integrate Data from Notebooks with Azure Synapse Pipelines or Azure Data Factory?
  • How to describe big data engineering with Apache Spark in Azure Synapse Analytics?
  • How to transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics?
  • How to perform data Exploration and Transformation in Azure Databricks?
  • How to create metadata objects in Azure Synapse serverless SQL pools
  • How to secure data and manage users in Azure Synapse serverless SQL pools?
  • How to work with DataFrames advanced methods in Azure Databricks?
  • How to perform end-to-end security with Azure Synapse Analytics?
  • How to ingest and load Data into the Data Warehouse?
DP-203 Data Engineering on Microsoft Azure Online Training
  • 32 Hrs. Instructor-led Online Training
  • Recorded Videos After Training
  • Digital Learning Material
  • Course Completion Certificate
  • Lifetime e-Learning Access
  • 24x7 After Training Support
Target audience
  • Data architects
  • Data professionals
  • Business intelligence professionals who want to learn data engineering
  • Data analysts who are responsible for building Microsoft Azure
  • Data scientists who work with analytical solutions
DP-203 Data Engineering on Microsoft Azure Course Prerequisites
  • You need to have in-depth knowledge of cloud computing to pursue this DP-203: Data Engineering on Microsoft Azure Online Training. Knowing core data concepts and having professional experience with data solutions are necessary for earning this course.
  • AZ-900 - Azure Fundamentals
  • DP-900 - Microsoft Azure Data Fundamentals
DP-203 Data Engineering on Microsoft Azure Course Certification
  • Multisoft Systems will provide you with a training completion certificate after completing the DP-203: Data Engineering on Microsoft Azure Training.

DP-203 : Data Engineering on Microsoft Azure Training Course Content

Module 1: Explore compute and storage options for data engineering workloads 

  • Introduction to Azure Synapse Analytics
  • Describe Azure Databricks
  • Introduction to Azure Data Lake storage
  • Describe Delta Lake architecture
  • Work with data streams by using Azure Stream Analytics 

Module 2: Run interactive queries using Azure Synapse Analytics serverless SQL pools 

  • Explore Azure Synapse serverless SQL pools capabilities
  • Query data in the lake using Azure Synapse serverless SQL pools
  • Create metadata objects in Azure Synapse serverless SQL pools
  • Secure data and manage users in Azure Synapse serverless SQL pools 

Module 3: Data exploration and transformation in Azure Databricks 

  • Describe Azure Databricks
  • Read and write data in Azure Databricks
  • Work with DataFrames in Azure Databricks
  • Work with DataFrames advanced methods in Azure Databricks 

Module 4: Explore, transform, and load data into the Data Warehouse using Apache Spark 

  • Understand big data engineering with Apache Spark in Azure Synapse Analytics
  • Ingest data with Apache Spark notebooks in Azure Synapse Analytics
  • Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
  • Integrate SQL and Apache Spark pools in Azure Synapse Analytics 

Module 5: Ingest and load data into the data warehouse 

  • Use data loading best practices in Azure Synapse Analytics
  • Petabyte-scale ingestion with Azure Data Factory 

Module 6: Transform data with Azure Data Factory or Azure Synapse Pipelines

  • Data integration with Azure Data Factory or Azure Synapse Pipelines
  • Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines 

Module 7: Orchestrate data movement and transformation in Azure Synapse Pipelines 

  • Orchestrate data movement and transformation in Azure Data Factory 

Module 8: End-to-end security with Azure Synapse Analytics 

  • Secure a data warehouse in Azure Synapse Analytics
  • Configure and manage secrets in Azure Key Vault
  • Implement compliance controls for sensitive data 

Module 9: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link 

  • Design hybrid transactional and analytical processing using Azure Synapse Analytics
  • Configure Azure Synapse Link with Azure Cosmos DB
  • Query Azure Cosmos DB with Apache Spark pools
  • Query Azure Cosmos DB with serverless SQL pools 

Module 10: Real-time Stream Processing with Stream Analytics 

  • Enable reliable messaging for Big Data applications using Azure Event Hubs
  • Work with data streams by using Azure Stream Analytics
  • Ingest data streams with Azure Stream Analytics 

Module 11: Create a Stream Processing Solution with Event Hubs and Azure Databricks 

  • Process streaming data with Azure Databricks structured streaming 
     

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