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Data Engineering on Microsoft Azure
Description
Data Engineering on Microsoft Azure (DP-203) Introduction
Welcome to our in-depth training course, “Data Engineering on Microsoft Azure (DP-203),” tailored for professionals who aspire to master the art of handling and analyzing data using Azure’s extensive cloud platform. This course is specifically designed for data architects, business intelligence professionals, data analysts, and data scientists who aim to deepen their understanding of data engineering concepts.
You will be guided through a variety of topics that cover both theoretical and practical aspects of data engineering, ensuring a well-rounded educational experience.
Throughout this course, you will explore the nuances of constructing both batch and real-time analytical solutions, leveraging the powerful tools and services offered by Microsoft Azure. Key components of Azure’s data platform, such as Azure Synapse Analytics, Azure Databricks, and Azure Data Factory, will be focal points of study.
By the end of this course, you will have gained comprehensive insights and practical skills to efficiently engineer and manage data solutions, enabling you to deliver impactful results in your data-driven projects using the Azure cloud infrastructure.
Prerequisites
Before enrolling in this course, it is recommended that students have:
- Knowledge of cloud computing concepts.
- Familiarity with core data concepts.
- Professional experience with data solutions.
Audience
This course is ideal for:
- Data professionals
- Data architects
- Business intelligence professionals
- Data analysts
- Data scientists
- Anyone interested in building analytical solutions using Microsoft Azure data platform technologies.
Data Engineering on Microsoft Azure (DP-203) Outline
Explore Compute and Storage Options for Data Engineering Workloads
- Introduction to Azure Synapse Analytics
- Understanding Azure Databricks
- Azure Data Lake Storage Overview
- Delta Lake Architecture
- Working with Data Streams in Azure Stream Analytics
Design and Implement the Serving Layer
- Designing a Multidimensional Schema for Analytical Workloads
- Code-Free Transformation with Azure Data Factory
- Populating Slowly Changing Dimensions in Azure Synapse Analytics Pipelines
Data Engineering Considerations for Source Files
- Designing a Modern Data Warehouse Using Azure Synapse Analytics
- Securing Data in Azure Synapse Analytics
Run Interactive Queries Using Azure Synapse Analytics Serverless SQL Pools
- Exploring Azure Synapse Serverless SQL Pools
- Querying Data in Azure Data Lake Using Serverless SQL Pools
- Creating Metadata Objects in Azure Synapse Serverless SQL Pools
- Securing Data and Managing Users
Explore, Transform, and Load Data into the Data Warehouse Using Apache Spark
- Big Data Engineering with Apache Spark in Azure Synapse Analytics
- Ingesting Data with Apache Spark Notebooks
- Transforming Data with DataFrames
- Integrating SQL and Apache Spark Pools
Data Exploration and Transformation in Azure Databricks
- Overview of Azure Databricks
- Reading and Writing Data in Azure Databricks
- Working with DataFrames
- Advanced-Data Transformation Techniques
Ingest and Load Data into the Data Warehouse
- Data Loading Best Practices
- Petabyte-Scale Ingestion with Azure Data Factory
- Hands-On Lab
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
- Hands-On Lab
Orchestrate Data Movement and Transformation in Azure Synapse Pipelines
- Orchestrating Data Movement and Transformation
- Hands-On Lab
Optimize Query Performance with Dedicated SQL Pools in Azure Synapse
- Strategies for Optimizing Data Storage and Processing
- Developer Features
- Query Performance Optimization
- Hands-On Lab
Analyze and Optimize Data Warehouse Storage
- Analyzing and Optimizing Data Storage
- Hands-On Lab
Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
- Designing Hybrid Transactional and Analytical Processing
- Configuring Azure Synapse Link
- Querying Azure Cosmos DB
- Hands-On Lab
End-To-End Security with Azure Synapse Analytics
- Securing a Data Warehouse
- Managing Secrets with Azure Key Vault
- Compliance Controls for Sensitive Data
- Hands-On Lab
Real-Time Stream Processing with Stream Analytics
- Reliable Messaging with Azure Event Hubs
- Working with Data Streams
- Ingesting Data Streams with Azure Stream Analytics
- Hands-On Lab
Create a Stream Processing Solution with Event Hubs and Azure Databricks
- Processing Streaming Data with Azure Databricks
- Key Features of Structured Streaming
- Implementing Sliding Windows and Watermarking
- Hands-On Lab
Build Reports Using Power BI Integration with Azure Synapse Analytics
- Creating Reports with Power BI
- Improving Query Performance
- Visualizing Data with Power BI
- Hands-On Lab
Perform Integrated Machine Learning Processes in Azure Synapse Analytics
- Integrated Machine Learning in Azure Synapse Analytics
- Hands-On Lab
$2395.00
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4 Days Course |