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DP-203T00: Data Engineering on Microsoft Azure – Exam DP-203 Certification Training Course

DP-203T00: Data Engineering on Microsoft Azure – Exam DP-203 Certification Training Course

DP-203T00: Data Engineering on Microsoft Azure – Exam DP-203 Certification Training Course

The DP-203T00: Data Engineering on Microsoft to Azure instructor-led, hands-on certification training courses. This certification training covers how to interactively explore data stored in files in the data lake.

This course provides information on how to build a real-time analytical framework to create real-time analytical solutions.

Knowledge of below-mentioned courses will be a plus:-

  • AZ-900 – Azure Fundamentals
  • DP-900 – Microsoft Azure Data Fundamentals

DP-203T00: Data Engineering on Microsoft Azure Certification Training Course

Logitrain course material for DP-203T00: Data Engineering on Microsoft Azure provided

  • Explore compute and storage options for data engineering workloads in Azure
  • Run interactive queries using server less SQL pools
  • Perform data Exploration and Transformation in Azure Data bricks
  • Explore, transform, and load data into the Data Warehouse using Apache Spark
  • Ingest and load Data into the Data Warehouse
  • Transform Data with Azure Data Factory or Azure Synapse Pipelines
  • Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines
  • Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
  • Perform end-to-end security with Azure Synapse Analytics
  • Perform real-time Stream Processing with Stream Analytics
  • Create a Stream Processing Solution with Event Hubs and Azure Data bricks
  • Data Professionals and Data Architects and Business intelligence Professionals
  • Data Analysts and Data Scientists
  • 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
  • Combine streaming and batch processing with a single pipeline
  • Organize the data lake into levels of file transformation
  • Index data lake storage for query and workload acceleration
  • 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
  • Query Parquet data with serverless SQL pools
  • Create external tables for Parquet and CSV files
  • Create views with serverless SQL pools
  • Secure access to data in a data lake when using serverless SQL pools
  • Configure data lake security using Role-Based Access Control (RBAC) and Access Control List
  • Describe Azure Databricks
  • Read and write data in Azure Databricks
  • Work with DataFrames in Azure Databricks
  • Work with DataFrames advanced methods in Azure Databricks
  • Use DataFrames in Azure Databricks to explore and filter data
  • Cache a DataFrame for faster subsequent queries
  • Remove duplicate data
  • Manipulate date/time values
  • Remove and rename DataFrame columns
  • Aggregate data stored in a DataFrame
  • 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
  • Perform Data Exploration in Synapse Studio
  • Ingest data with Spark notebooks in Azure Synapse Analytics
  • Transform data with DataFrames in Spark pools in Azure Synapse Analytics
  • Integrate SQL and Spark pools in Azure Synapse Analytics
  • Use data loading best practices in Azure Synapse Analytics
  • Petabyte-scale ingestion with Azure Data Factory
  • Perform petabyte-scale ingestion with Azure Synapse Pipelines
  • Import data with PolyBase and COPY using T-SQL
  • Use data loading best practices in Azure Synapse Analytics
  • Data integration with Azure Data Factory or Azure Synapse Pipelines
  • Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines
  • Execute code-free transformations at scale with Azure Synapse Pipelines
  • Create data pipeline to import poorly formatted CSV files
  • Create Mapping Data Flows
  • Orchestrate data movement and transformation in Azure Data Factory
  • Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines
  • Secure a data warehouse in Azure Synapse Analytics
  • Configure and manage secrets in Azure Key Vault
  • Implement compliance controls for sensitive data
  • Secure Azure Synapse Analytics supporting infrastructure
  • Secure the Azure Synapse Analytics workspace and managed services
  • Secure Azure Synapse Analytics workspace data
  • 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
  • Configure Azure Synapse Link with Azure Cosmos DB
  • Query Azure Cosmos DB with Apache Spark for Synapse Analytics
  • Query Azure Cosmos DB with serverless SQL pool for Azure Synapse Analytics
  • nable 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
  • Use Stream Analytics to process real-time data from Event Hubs
  • Use Stream Analytics windowing functions to build aggregates and output to Synapse Analytics
  • Scale the Azure Stream Analytics job to increase throughput through partitioning
  • Repartition the stream input to optimize parallelization
  • Process streaming data with Azure Databricks structured streaming
  • Explore key features and uses of Structured Streaming
  • Stream data from a file and write it out to a distributed file system
  • Use sliding windows to aggregate over chunks of data rather than all data
  • Apply watermarking to remove stale data
  • Connect to Event Hubs read and write streams
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What is included with the DP-203T00: Data Engineering on Microsoft Azure – Exam DP-203 Certification Training Course?
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