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Terminy kursów:

22.11.2021 - 25.11.2021

Oficjalny konspekt Microsoft Pozostałe szkolenia

DP-203 Data Engineering on Microsoft Azure

Czas trwania kursu: 4 dni
Cena: 2899 zł netto

CERTYFIKACJE ZAWODOWE

Certyfikacja podstawowa CertyfIkacja specjalistyczna Certyfikacja ekspercka
FUNDAMENTALS ASSOCIATE EXPERT

 


POZIOM SZKOLENIA

podstawowy średniozaawansowany zaawansowany ekspercki
100 200 300 400

 

TEMATYKA ZAJĘĆ

  • 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
    Lab : Explore compute and storage options for data engineering workloads

 

  • 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
    Lab: Run interactive queries using 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
    Lab: Data Exploration and Transformation 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
    Lab: Explore, transform, and load data into the Data Warehouse using Apache Spark

 

  • 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
    Lab: Ingest and load Data into the Data Warehouse

 

  • 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
    Lab: Transform Data 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
    Lab: Orchestrate data movement and transformation in Azure Synapse Pipelines

 

  • 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
    Lab: End-to-end security with Azure Synapse Analytics

 

  • 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
    Lab: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link

 

  • 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
    Lab: Real-time Stream Processing with Stream Analytics

 

  • Module 11: Create a Stream Processing Solution with Event Hubs and Azure Databricks
    Process streaming data with Azure Databricks structured streaming
    Lab : Create a Stream Processing Solution with Event Hubs and Azure Databricks