A tanfolyamról
Get started on a transformative journey with our Azure Data Engineering Certification training. Immerse yourself in live, instructor-led sessions, striking the perfect balance between classroom instruction and practical application. Stay ahead with the latest Microsoft-approved curriculum and access a digital library of rich learning resources. Proficiently analyze data on Azure, extracting meaningful insights in the era of Big Data transformation.
Validate your expertise with the Microsoft DP-203 certification, making a transformative impact on your CV. Clear the DP-203 exam with confidence through our comprehensive training, tailored to equip you with practical knowledge, technical skills, and a deep understanding of fundamental concepts.
Upon completing our Microsoft Azure Data Engineer Course, you will gain the following key skills:
- Data Fundamentals: Acquire a comprehensive understanding of fundamental concepts in data, including data storage, Azure storage, and various data formats.
- Data Design and Implementation: Apply analytical skills to design efficient data systems, focusing on the implementation of data storage solutions within the Azure cloud network.
- Data Protection: Utilize state-of-the-art security tools to ensure robust endpoint security for data stored on the Azure platform, enhancing data protection measures.
- Data Loading: Master the efficient loading of data using Azure Synapse Analytics, Databricks, and Azure Data Factory, gaining practical expertise in data loading techniques.
- Data Storage: Implement and manage Azure storage accounts and Data Warehouse, demonstrating proficiency in securely storing diverse forms of data within the Azure environment.
- Data Analysis: Utilize cutting-edge storage technologies to construct analytical solutions for data analysis. Develop the skills to extract meaningful insights from stored data, contributing to informed decision-making.
By covering a variety of topics within the context of an Azure environment, this training equips you with a well-rounded skill set in data engineering on Microsoft Azure. Whether it's understanding data fundamentals, designing and implementing data systems, ensuring data protection, loading data efficiently, managing storage, or conducting data analysis, you'll emerge from the course with practical skills ready for real-world data engineering applications.
Who This Course Is For
- Aspiring Data Engineers
- Cloud Solutions Architects
- Experienced Azure Administrators
- Azure Developers
- IT and DevOps Professionals
- Business Intelligence Professionals
- Machine Learning Professionals
Learning Objectives
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Data Design and Implementation
Apply analytical skills and concepts to design data systems and to store data on cloud network. -
Data Protection
Leverage state-of-the-art security tools to provide endpoint security to data on Azure. -
Data Loading
Use Azure Synapse Analytics, Databricks, and Azure Data Factory to efficiently load data. -
Data Storage
Implement Azure storage accounts and Data warehouse to securely store different forms of data. -
Data Analysis
Use cutting-edge storage technologies to build an analytical solution for Data Analysis. -
Building Analytics Solutions
Integrate, transform, and consolidate data from myriad structures and build analytics
About the exam
The passing score for the exam is 700 out of 1000. You get a time limit of 2 hours and 10 minutes to answer the questions.
We provide this course in English.
Tematika
Curriculum
1. Data Engineering - An Introduction
Learning Objectives
Master fundamental Azure concepts, terminology, and services and develop proficiency in navigating the Azure Portal for resource creation, management, and monitoring.
- Azure Overview
- Fundamental Azure Concepts
- Introduction to Azure Portal
2. Design and Implement Data Storage
Learning Objectives
Acquire expertise in designing and implementing an Azure Data Lake solution, covering efficient querying, data pruning, distribution strategy, archiving, partitioning, and the implementation of physical and logical data structures. Develop skills for creating a robust serving layer, ensuring a holistic understanding of end-to-end data management in Azure.
- Design an Azure Data Lake solution
- Design for Efficient Querying
- Design for Data Pruning
- Design a Distribution Strategy
- Design Data Archiving Solution
- Design a Partition Strategy
- Implement Physical Data Storage Structures
- Implement Logical Data Structure
- Implement the Serving Layer
3. Design and Develop Data Processing
Learning Objectives
Master data ingestion and transformation techniques, design efficient batch processing solutions, implement stream processing solutions for real-time data, and effectively manage data batches and pipelines to ensure seamless data flow in diverse applications.
- Ingest and Transform Data
- Design and Develop a Batch Processing Solution
- Design and Develop a Stream Processing Solution
- Manage Data Batches and Pipelines
4. Design and Implement Data Security
Learning Objectives
Master designing robust security measures for data policies, standards, and proficiently implement data masking techniques to safeguard sensitive information effectively.
- Design Security for Data Policies and Standards
- Implement Data Masking and Security
5. Monitor and Optimize Data Storage and Processing
Learning Objectives
Develop proficiency in configuring data monitoring services, optimizing data storage and processing, and troubleshooting data processing for efficient and reliable data management in diverse IT environments.
- Configure Data Monitoring Services
- Optimize Data Storage and Processing
- Troubleshoot Data Processing
Kinek ajánljuk
Előfeltételek
Prerequisites
- Participants need to have a basic understanding of data formats - CSV, JSON
- Participants should have some basic database knowledge