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Data Engineering on Microsoft Azure (DP-203)
Description
Data Engineering on Microsoft Azure (DP-203) Introduction
Welcome to our comprehensive training program, “Data Engineering on Microsoft Azure (DP-203),” meticulously crafted for professionals eager to excel in managing and analyzing data on Azure’s dynamic cloud platform.
Tailored to data architects, business intelligence professionals, data analysts, and data scientists, this course is your gateway to mastering the intricacies of data engineering.
Throughout this course, we dive deep into both theoretical frameworks and hands-on applications, ensuring a holistic learning journey.
You’ll navigate through constructing batch and real-time analytical solutions, harnessing the robust suite of tools and services Azure offers. Central to your exploration are key components like Azure Synapse Analytics, Azure Databricks, and Azure Data Factory, which form the bedrock of Azure’s data platform.
By the course’s conclusion, you’ll emerge equipped with a profound understanding and practical expertise in engineering and managing data solutions effectively.
Armed with these skills, you’ll be primed to deliver impactful results in your data-centric projects, leveraging Azure’s powerful cloud infrastructure to its fullest potential. Dive in and elevate your data engineering prowess with us.
Data Engineering on Microsoft Azure (DP-203) Objectives
- Comprehensive Understanding: Gain a thorough understanding of data engineering principles and practices within the Microsoft Azure ecosystem, empowering you to navigate complex data challenges with confidence.
- Practical Application: Acquire hands-on experience in constructing both batch and real-time analytical solutions using Azure’s robust tools and services, including Azure Synapse Analytics, Azure Databricks, and Azure Data Factory.
- Efficient Data Management: Learn efficient data management techniques to optimize data workflows, storage, and processing, ensuring seamless operations across various stages of data engineering projects.
- Problem-Solving Skills: Develop critical problem-solving skills essential for tackling real-world data engineering challenges, from data ingestion and transformation to analysis and visualization.
- Scalability and Performance: Explore techniques to design scalable and high-performance data solutions, enabling you to meet evolving business needs and handle increasing data volumes effectively.
- Optimized Resource Utilization: Understand how to leverage Azure’s cloud infrastructure efficiently, minimizing costs while maximizing the value derived from data engineering initiatives.
- Project Readiness: Equip yourself with the skills and knowledge necessary to contribute effectively to data-driven projects, from conceptualization to implementation, and deliver tangible results that drive business success.
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 |