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  1. Database, Big Data, Machine Learning
DP-203

Data Engineering on Microsoft Azure

Prezzo

€ 1,400.00
(Iva esclusa)

Scheda tecnica

Scarica

Giorni

4 gg

In questo corso illustreremo:

-          i modelli e le pratiche di data engineering per quanto riguarda il lavoro con soluzioni analitiche batch e in tempo reale utilizzando le tecnologie della piattaforma dati Azure. 

-          le tecnologie di calcolo e di archiviazione di base che vengono utilizzate per costruire una soluzione analitica. 

-          come progettare un livello di servizio analitico con considerazioni di data engineering per lavorare con i file di origine. 

-          come esplorare interattivamente i dati memorizzati nei file in un data lake 

-          le varie tecniche di data ingestion che possono essere utilizzate per caricare i dati utilizzando la capacità di Apache Spark presente in Azure Synapse Analytics o Azure Databricks, o utilizzando Azure Data Factory o Azure Synapse pipeline. 

-          i modi in cui possono trasformare i dati utilizzando le stesse tecnologie che vengono utilizzate per importare i dati. 

-          come monitorare e analizzare le prestazioni del sistema analitico in modo da poter ottimizzare le prestazioni dei data loads, o le query che vengono emesse contro i sistemi.

-          come implementare la sicurezza per assicurare che i dati siano protetti at rest o in transit. 

-          come i dati in un sistema analitico possono essere utilizzati per creare dashboard o costruire modelli predittivi in Azure Synapse Analytics.


Questo corso è rivolto a data professionals, data architects e professionisti della business intelligence che vogliono imparare data engineering e la costruzione analytical solutions utilizzando le tecnologie della piattaforma dati che esistono su Microsoft Azure. Inoltre è rivolto a data analysts e data scientists che lavorano con soluzioni analitiche costruite su Microsoft Azure. 



Per partecipare con profitto a questo corso gli allievi dovrebbero aver partecipato ai seguenti corsi oppure possedere competenze equivalenti:


AZ-900 – Azure Fundamentals

DP-900 – Azure Data Fundamentals

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: Design and implement the serving layer

  • Design a multidimensional schema to optimize analytical workloads
  • Code-free transformation at scale with Azure Data Factory
  • Populate slowly changing dimensions in Azure Synapse Analytics pipelines 
  • Module 3: Data engineering considerations for source files
  • Design a Modern Data Warehouse using Azure Synapse Analytics
  • Secure a data warehouse in Azure Synapse Analytics

Module 3: Data engineering considerations for source files

  • Design a Modern Data Warehouse using Azure Synapse Analytics
  • Secure a data warehouse in Azure Synapse Analytics

Module 4: 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 5: 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 6: 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 7: 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 8: 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 9: Orchestrate data movement and transformation in Azure Synapse Pipelines

  • Orchestrate data movement and transformation in Azure Data Factory

Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse

  • Optimize data warehouse query performance in Azure Synapse Analytics
  • Understand data warehouse developer features of Azure Synapse Analytics

Module 11: Analyze and Optimize Data Warehouse Storage

  • Analyze and optimize data warehouse storage in Azure Synapse Analytics

Module 12: 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 13: 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 14: 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 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks

  • Process streaming data with Azure Databricks structured streaming

Module 16: Build reports using Power BI integration with Azure Synpase Analytics

  • Create reports with Power BI using its integration with Azure Synapse Analytics

Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics

  • Use the integrated machine learning process in Azure Synapse Analytics


Sede Data P
Virtual 03/07/2023
Virtual 16/10/2023