DP-203 Data Engineering on Microsoft Azure (DP-203T00)

Seminarinformationen

Seminar - Ziel

In this course, the student will learn about the data engineering as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how to create a real-time analytical system to create real-time analytical solutions.

Teilnehmer - Zielgruppe

The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course data analysts and data scientists who work with analytical solutions built on Microsoft Azure.

Kurs - Voraussetzungen

Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.

Specifically completing:

  • AZ-900 - Azure Fundamentals

  • DP-900 - Microsoft Azure Data Fundamentals

Seminardauer

  • 4 Tage
  • 09:00 Uhr bis 17:00 Uhr

Schulungsunterlagen

  • nach Absprache

Seminar-Inhalt / Agenda

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

Explore compute and storage options for data engineering workloads

  • 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

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

Run interactive queries using 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

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

Data Exploration and Transformation 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

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

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

  • 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

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

Ingest and load Data into the Data Warehouse

  • 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

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

Transform Data 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

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

  • Orchestrate data movement and transformation in Azure Data Factory

Orchestrate data movement and transformation in Azure Synapse Pipelines

  • Integrate Data from Notebooks with Azure Data Factory or 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

End-to-end security with Azure Synapse Analytics

  • 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

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

Real-time Stream Processing with 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

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

  • Process streaming data with Azure Databricks structured streaming

Create a Stream Processing Solution with Event Hubs and Azure Databricks

  • 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

Weitere Schulungen zu Thema Microsoft Azure

AZ-010 Azure Administration for AWS SysOps (AZ-010T00)

- u.a. in Nürnberg, Berlin, Stuttgart, München, Köln

This two-day course is designed for AWS Sysops administrators interested in learning how Azure is different from AWS, and how Azure is administered. The workshops main topics are Azure Administration, Azure Networking, Azure Compute, Azure Storage, and Azure Governance. This ...

AZ-020 Microsoft Azure solutions for AWS developers (AZ-020T00)

- u.a. in Nürnberg, Berlin, Stuttgart, München, Köln

A three-day course designed to teach AWS (Amazon Web Services) developers how to prepare end-to-end solutions in Microsoft Azure. In this course you will construct Azure App Service Web App solutions and Azure Functions, use blob or Cosmos DB storage in solutions, implement ...

AZ-120 Planning and Administering Microsoft Azure for SAP Workloads (AZ-120T00)

- u.a. in Berlin, Paderborn, Düsseldorf, Darmstadt, Freiburg

This course teaches IT Professionals experienced in SAP solutions how to leverage Azure resources that include deployment and configuration of virtual machines, virtual networks, storage accounts, and Azure AD that includes implementing and managing hybrid identities. Students ...

AZ-720 Azure Support Engineer Troubleshooting Azure Connectivity (AZ-720T00)

- u.a. in Berlin, Frankfurt am Main, Stuttgart, Essen, Koblenz

Networking is essential, particularly when you have cloud-based assets. This course covers the different connectivity issues that a network engineer will typically encounter, and the troubleshooting steps to resolve these issues.