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DP 203: Data Engineering on Microsoft Azure
DP 203: Data Engineering on Microsoft Azure
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Why enroll for DP 203: Data Engineering on Microsoft Azure?
Azure Data Engineering Training Benefits
The world of data has evolved and the advent of cloud technologies is providing new opportunities for businesses to explore. Azure data engineering is one of the most sought-after and fastest-growing technologies in the market today. As per Microsoft, 95% of Fortune 500 firms use Azure cloud services, and as a result, there is an increasing need for Microsoft-certified experts who can use Azure and manage massive volumes of data. The best way to land you a good job with a handsome salary in this domain is to get an Azure Data Engineer Certification.
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Why DP 203: Data Engineering on Microsoft Azure from edureka
Live Interactive Learning
- World-Class Instructors
- Expert-Led Mentoring Sessions
- Instant doubt clearing
Lifetime Access
- Course Access Never Expires
- Free Access to Future Updates
- Unlimited Access to Course Content
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
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About your DP 203: Data Engineering on Microsoft Azure
Azure Data Engineering Skills
- Design data storage solutions
- Analyze data using SQL and Spark
- Design and implement data security
- Monitor data storage and data processing
- Optimize data storage and data processing
- Create and manage data pipelines
Tools Covered
Azure Data Engineering Certification Curriculum
Curriculum Designed by Experts
Introduction to Microsoft Azure and its Services
7 Topics
Topics:
- Azure Subscriptions
- Azure Resources
- Azure Free Tier Account
- Azure Resource Manager
- Azure Resource Manager Template
- Azure Storage
- Types of Azure Storage
Hands-on:
- Create a free tier Azure account
- Create a web app service using Azure Portal
- Create and Deploy ARM templates
- Manage Azure Storage account
- Manage Azure Cost and Billing
Skills You will Learn:
- Creating ARM templates
- Accessing Azure Storage Service
- Azure Cost and Billing Services
Introduction To Azure Data Engineering
14 Topics
Topics:
- Understand the evolving world of data
- Data abundance
- Understanding the Data Engineering Problem
- Understand job responsibilities
- Understanding Data Engineering Processing - Extract Transform and Load
- Overview of Azure Data Engineering Services
- Understand data storage in Azure Storage
- Understand data storage in Azure Data Lake Storage
- Understand Azure Cosmos DB
- Understand Azure SQL Database
- Understand Azure Synapse Analytics
- Understand Azure Stream Analytics
- Understand Azure HDInsight
- Understand other Azure data services
Hands-on:
- Navigating through Azure data engineering services
Skills You will Learn:
- Analyzing Data Engineering Process
- Understanding Azure Services
Storing Data in Azure
13 Topics
Topics:
- How to choose an Azure Storage Service in Azure
- Create an Azure Storage Account
- Connect an app to Azure Storage API
- Connect to your Azure storage account
- Explore Azure Storage security features
- Understand storage account keys
- Understand shared access signatures
- Control network access to your storage account
- Understand Advanced Threat Protection for Azure Storage
- Explore Azure Data Lake Storage security features
- Introduction to Blob storage
- What are blobs?
- Design a storage organization strategy
Hands-on:
- Add the storage client library to your app
- Add Azure Storage configuration to your app
- Connect your application to your Azure Storage account
- Create Azure storage resources
- Configure and initialize the client library
- Get blob references
- Blob uploads and downloads
Skills You will Learn:
- Working with Azure Storage
- Configuring Security in Azure Storage
- Storing blob data in Azure Storage
Azure Data Factory - I
15 Topics
Topics:
- Integrate data with Azure Data Factory or Azure Synapse Pipeline
- Understand Azure Data Factory
- Describe data integration patterns
- Explain the data factory process
- Understand Azure Data Factory components
- Azure Data Factory security
- Set-up Azure Data Factory
- Create linked services
- Create datasets
- Create data factory activities and pipelines
- Manage integration runtimes
- Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
- List the data factory ingestion methods
- Describe data factory connectors
- Understand data ingestion security considerations
Hands-on:
- Use the data factory copy activity
- Manage the self hosted integration runtime
- Setup the Azure integration runtime
Skills You will Learn:
- Working with Azure Data Factory
- Integrating Azure Data Factory
- Azure Data Factory security
- Implementing Data Factory connectors
Azure Data Factory - II
22 Topics
Topics:
- Explain Data Factory transformation methods
- Describe Data Factory transformation types
- Debug mapping data flow
- Describe slowly changing dimensions
- Choose between slowly changing dimension types
- Understand data factory control flow
- Work with data factory pipelines
- Debug data factory pipelines
- Add parameters to data factory components
- Execute data factory packages
- Describe SQL Server Integration Services
- Understand the Azure-SIS integration runtime
- Set-up Azure-SIS integration runtime
- Run SSIS packages in Azure Data Factory
- Migrate SSIS packages to Azure Data Factory
- Configure a git repository with a development factory
- Create and merge a feature branch
- Deploy a release pipeline
- Visually monitor pipeline runs
- Integrate with Azure Monitor
- Set up alerts
- Rerun pipeline runs
Hands-on:
- Author an Azure Data Factory mapping data flow
- Use Data Factory wrangling data
- Use compute transformations within Data Factory
- Integrate SQL Server Integration Services packages within Data Factory
- Design and implement a Type 1 slowly changing dimension with mapping data flows
- Integrate a Notebook within Azure Synapse Pipelines
Skills You will Learn:
- Implementing Data Factory transformations
- Implementing slowly changing dimensions
- Working with SQL server integration
- Configuring a git repository
- Integrating Azure monitor and set up alerts
Azure Synapse Analytics - I
10 Topics
Topics:
- What is Azure Synapse Analytics
- How Azure Synapse Analytics works
- When to use Azure Synapse Analytics
- Create Azure Synapse Analytics workspace
- Describe Azure Synapse Analytics SQL
- Explain Apache Spark in Azure Synapse Analytics
- Orchestrate data integration with Azure Synapse pipelines
- Visualize your analytics with Power BI
- Understand hybrid transactional analytical processing with Azure Synapse Link
- Use Azure Synapse Studio
Hands-on:
- Explore Azure Synapse Analytics
- Create pools in Azure Synapse Analytics
- Identifying Azure Synapse pipeline components
Skills You will Learn:
- Working with Azure Synapse Analytics
- Managing Azure Synapse Analytics workspace
- Querying data and Visualizing analytics
- Working with Azure Synapse pipeline components
Azure Synapse Analytics - II
6 Topics
Topics:
- Understand the Azure Synapse Analytical processes
- Explore the Data hub
- Explore the Develop hub
- Explore the Integrate hub
- Explore the Monitor hub
- Explore the Manage hub
Hands-on:
- Create a new data flow or dataset, and manage the file
- Use the Monitor hub to view pipeline and trigger runs, view the status of the various integration runtimes
Skills You will Learn:
- Designing the new data flow or dataset
- Working with various types of hubs
Data Warehouses using Azure Synapse Analytics - I
7 Topics
Topics:
- Describe a modern data warehouse
- Define a modern data warehouse architecture
- Exercise - Identify modern data warehouse architecture components
- Design ingestion patterns for a modern data warehouse
- Understand data storage for a modern data warehouse
- Understand file formats and structure for a modern data warehouse
- Prepare and transform data with Azure Synapse Analytics
Hands-on:
- Serve data for analysis with Azure Synapse Analytics
- Design a data warehouse schema
- Create data warehouse tables
- Load data warehouse tables
- Query a data warehouse
Skills You will Learn:
- Designing a Modern Data Warehouse Architecture
- Building a Data Warehouse
- Working with different file formats
- Preparing and transforming data
Data Warehouses using Azure Synapse Analytics - II
8 Topics
Topics:
- Understand data load design goals
- Explain load methods into Azure Synapse Analytics
- Manage source data files
- Manage singleton updates
- Set-up dedicated data load accounts
- Implement workload management
- Simplify ingestion with the Copy Activity
- Understand performance issues related to tables
Hands-on:
- Data Loading in Azure Synapse Analytics
- Data Ingestion using Copy Activity
- Implement workload management
- Understand performance issues related to tables
Skills You will Learn:
- Loading data using Azure Synapse Analytics
- Implementing workload management
Optimizing Data Queries in Azure
14 Topics
Topics:
- Understand table distribution design
- Use indexes to improve query performance
- Understand query plans
- Create statistics to improve query performance
- Improve query performance with materialized views
- Use read committed snapshot for data consistency
- How does statistics affect a query plan?
- Describe the integration methods between SQL and spark pools in Azure Synapse Analytics
- Understand the use-cases for SQL and spark pools integration
- Exercise: Integrate SQL and spark pools in Azure Synapse Analytics
- Externalize the use of spark pools within Azure Synapse Workspace
- Transfer data outside the synapse workspace using the PySpark connector
- Explore the development tools for Azure Synapse Analytics
- Understand transact-SQL language capabilities for Azure Synapse Analytics
Hands-on:
- Use table distribution and indexes to improve performance
- Optimize common queries with result-set caching
- Work with windowing functions
- Work with approximate execution
- Work with JSON data in SQL pools
- Encapsulate transact-SQL logic with stored procedures
- Authenticate in Azure Synapse Analytics
- Transfer data between SQL and spark pool in Azure Synapse Analytics
- Authenticate between spark and SQL pool in Azure Synapse Analytics
Skills You will Learn:
- Optimizing data queries in Azure
- Authenticating in Azure Synapse Analytics
- Working with SQL and Spark pool
Managing Workloads in Azure Synapse Analytics
12 Topics
Topics:
- Scale compute resources in Azure Synapse Analytics
- Pause compute in Azure Synapse Analytics
- Manage workloads in Azure Synapse Analytics
- Use Azure Advisor to review recommendations
- Use dynamic management views to identify and troubleshoot query performance
- Understand skewed data and space usage
- Understand network security options for Azure Synapse Analytics
- Configure Conditional Access
- Configure authentication
- Manage authorization through column and row level security
- Manage sensitive data with Dynamic Data Masking
- Implement encryption in Azure Synapse Analytics
Hands-on:
- Manage authorization through column and row level security
Skills You will Learn:
- Managing workloads in Azure Synapse Analytics
- Authentication and authorization in Azure Synapse Analytics
- Implementing encryption in Azure Synapse Analytics
Deep Dive into Azure Databricks
19 Topics
Topics:
- Get started with Azure Databricks
- Identify Azure Databricks workloads
- Understand key concepts
- Use Apache Spark in Azure Databricks
- Create a Spark cluster
- Use Spark in notebooks
- Use Spark to work with data files
- Visualize data
- Get Started with Delta Lake
- Create Delta Lake tables
- Create and query catalog tables
- Use Delta Lake for streaming data
- Get started with SQL Warehouses
- Create databases and tables
- Create queries and dashboards
- Understand Azure Databricks notebooks and pipelines
- Create a linked service for Azure Databricks
- Use a Notebook activity in a pipeline
- Use parameters in a notebook
Hands-on:
- Explore Azure Databricks
- Run an Azure Databricks Notebook with Azure Data Factory
- Use a SQL Warehouse in Azure Databricks
- Use Delta Lake in Azure Databricks
- Use Spark in Azure Databricks
Skills You will Learn:
- Working with Azure Databricks
- Running interactive and scheduled data analysis workloads
Capstone Project
3 Topics
Topics:
- In this project, you will design a secure, analytical, data ingestion, scalable, build and deploy data pipeline solution which you have learned as a part of this certification course
- Documentation and presentation: Develop detailed documentation outlining the design and implementation of the Azure data solution, and effectively present the solution and its outcomes to business
- Design and implement an Azure Data Solution
Integrating Azure Data Solutions with Other Services (Self-paced)
4 Topics
Topics:
- Integrating Azure Data Solutions with Azure Synapse Analytics
- Integrating Azure Data Solutions with Power BI
- Integrating Azure Data Solutions with Azure Logic Apps
- Best Practices for Integrating Azure Data Solutions with Other Services
Hands-on:
- Working with the Azure Data Solutions with Azure Synapse Analytics
- Build and deploy Azure Data Solutions with Power BI
Skills You will Learn:
- Using Azure Data Solutions with Power BI
- Designing the Azure Data Solutions
- Best practices for integrating Azure Data Solutions
Security and Compliance (Self-paced)
4 Topics
Topics:
- Overview of Azure Security Features
- Implementing Security for Azure Data Storage Solutions
- Implementing Security for Azure Data Processing Solutions
- Best Practices for Securing Data Solutions in Azure
Hands-on:
- To demonstrate the practical implementation of security and compliance measures in Azure data engineering to safeguard the organization's data
- To demonstrate the practical implementation of compliance measures in Azure data engineering to ensure adherence to regulatory requirements
Skills You will Learn:
- Securing the Azure Data Storage Solutions
- Implementing Security for Data Processing Solutions
Monitoring and Optimizing Data Solutions (Self-paced)
4 Topics
Topics:
- Monitoring and Alerting Strategies for Azure Data Solutions
- Optimizing Data Processing Solutions for Performance and Cost
- Using Azure Monitor to Monitor Data Solutions
- Best Practices for Monitoring and Optimizing Azure Data Solutions
Hands-on:
- To demonstrate the practical implementation of monitoring measures in Azure data engineering solutions to ensure efficient system operation
- Implementation of optimization measures in Azure data engineering solutions to ensure better system performance, reduce costs, and increase productivity
Skills You will Learn:
- Enhancing Data for Performance and Cost
- Setting up the Azure Monitor
Industrial Case Studies (Self-paced)
3 Topics
Topics:
- Case Studies on Implementing Azure Data Solutions
- Emerging Trends and Technologies in Azure Data Engineering
- Best Practices for Keeping Up with Industry Trends in Azure Data Engineering
Use Cases:
- Case Studies on Mitsubishi Heavy Industries (MHI) Group
- Case Studies on Bayer AG
- Case Studies on fischer
- Case Studies on New York City Department of Education
- Case Studies on Amadeus
Scenario Based Exam Dumps
1 Topics
Topics:
- Scenario Based Dumps Set -1,2,3,4,5,6,7
DP-203 Certification: Practice Exam
2 Topics
Topics:
- Practise Exam Set 1,2,3
- 3 practise exams with a minimum passing score of 700 will allow you to gauge your level of preparation
Azure Data Engineering Interview Preparation
1 Topics
Topics:
- Interview preparation material to assist you in getting ready for the upcoming interviews
Reference Material
2 Topics
Topics:
- Whitepapers
- Reference Documents
Bonus Content
2 Topics
- Additional Resources (Part 1)
- Additional Resources (Part 2)
Free Career Counselling
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Azure Data Engineering Certification Course Details
About Azure Data Engineering Certification Course
Edureka's Azure Data Engineering Certification Course is the best choice for learners seeking to design, implement, monitor, and optimize high-performing and reliable data pipelines and data stores on the Microsoft Azure platform. With experienced instructors, real-world case studies, and flexible learning options, this course provides learners with practical skills and knowledge for identifying and troubleshooting operational and data quality issues. The key features of this course include:
- Comprehensive coverage of key topics such as- Azure Cosmo DB, Azure Synapse, Azure Databricks, Azure Stream Analytics, Azure HDInsight, and Azure Data Factory.
- Assignments and quizzes in each module
- Practice projects to hone your skills
- 7+ exam dumps containing 100 scenario based exam questions each to help you prepare for the certification exam
- 3 simulation exams to let you assess your preparation
- Certification guide for DP:203
- Interview preparation material to help you prepare for the interviews
- Bonus and additional content for further knowledge enhancement
- 3 capstone projects to bolster your resume
Hurry up and join our Azure Data Engineering Certification Course today to propel your career to greater heights.
What are the prerequisites for this Azure Data Engineering Course?
You don’t need to possess any predefined skills or expertise to enroll in this course. However, any prior knowledge of Linux, Python, SQL, and Scala would be appreciated.
Why should you become a certified Azure Data Engineer?
Learning an Azure Data Engineering Certification Course can provide several benefits, such as:
- Career Growth: With the increasing demand for data engineering skills, certified Azure Data Engineers are highly sought after by top companies worldwide. This opens up a plethora of career opportunities for professionals in this field.
- Future Demand: The demand for skilled data engineers is projected to increase in the future, with the adoption of cloud computing, big data analytics, and machine learning. This makes it an ideal time to gain certification in Azure Data Engineering.
- Skills: The certification provides a comprehensive understanding of Azure data services, data modeling, ingestion, transformation, processing, analysis, visualization, monitoring, and optimization. This enables professionals to develop and deploy high-performing and reliable data pipelines and data stores.
- Salary Growth: Certified Azure Data Engineers can expect to receive higher salaries compared to non-certified professionals. The certification is an excellent way to demonstrate expertise and experience in this field, which can lead to higher paying job opportunities.
- Hands-on Experience: The certification course provides hands-on experience with real-world case studies and industry projects, enabling learners to apply their skills in a practical setting.
- Industry Project Exposure: Learners gain exposure to industry best practices and the latest tools and technologies used in data engineering. This enhances their knowledge and skills, making them more competitive in the job market.
What are the objectives of our Azure Data Engineering Certification Course?
Our Azure Data Engineering Certification Course is designed as per industry standards and help learners in designing, implementing, and maintaining secure and compliant data processing pipelines using Azure data services and frameworks. The exam assesses the candidate's ability to integrate, transform, and consolidate data from various structured, unstructured, and streaming data systems into a suitable schema for building analytics solutions.
Candidates are expected to be proficient in using Azure Data Factory, Azure Synapse Analytics, Azure Stream Analytics, Azure Event Hubs, Azure Data Lake Storage, and Azure Databricks to create data processing solutions. The exam also tests the candidate's ability to design, implement, monitor, and optimize data platforms to meet the data pipelines, ensuring that the operationalization of data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints. Additionally, candidates should be able to troubleshoot operational and data quality issues and design data stores with different architecture patterns based on business requirements.
What are the skills of a certified Azure Data Engineer?
Certified Azure Data Engineers ideally possesses the following skills:
- Expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems into a suitable schema for building analytics solutions.
- Ability to help stakeholders understand the data through exploration, and build and maintain secure and compliant data processing pipelines using different tools and techniques.
- Knowledge of various Azure data services and frameworks to store and produce cleansed and enhanced datasets for analysis. Ability to design data stores with different architecture patterns based on business requirements, including modern data warehouse (MDW), big data, or lakehouse architecture.
- Ability to ensure that the operationalization of data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints. Ability to identify and troubleshoot operational and data quality issues.
- Ability to design, implement, monitor, and optimize data platforms to meet the data pipelines.
- Solid knowledge of data processing languages, including SQL, Python, and Scala, and understanding of parallel processing and data architecture patterns.
- Proficiency in using Azure Data Factory, Azure Synapse Analytics, Azure Stream Analytics, Azure Event Hubs, Azure Data Lake Storage, and Azure Databricks to create data processing solutions.
Who should go for this Azure Data Engineering Training?
Anyone with a zeal to learn and who wants to become a Data Engineer or Data Architect can join this training.
What are the system requirements for this Azure Data Engineer Certification Training?
You need a basic configuration with a minimum of 4GB RAM and i3 processor, with a good internet connection.
How will I execute practicals in this Azure Data Engineer Certification Training?
You will be using Azure Free Tier Account to execute the practicals. The detailed step by step installation guides are available on the LMS. Edureka's 24*7 technical support team is always available to promptly assist you with your queries.
Azure Data Engineering Projects
Data-Driven Decision-Making to Optimize Online Retail Customer Experience and Increase Sales
The retail company recognizes the importance of online sales and the customer experience in today's digital age. To stay competitive, they understand that they need to use data-d....Enhancing Data Processing and Analysis Capabilities for Advertising Analytics Company
An advertisement analytics company is looking to improve their data processing and analysis capabilities. They receive large amounts of data on a daily basis from various sour....
Developing a Real-Time Predictive Maintenance Solution for Industrial Equipment Using Machine Learning
An AI analytics company is developing a predictive maintenance solution for industrial equipment, using machine learning to predict equipment failures and schedule maintenance....
Azure Data Engineering Certification
An Azure Data Engineer is a professional who is responsible for designing and implementing modern data solutions on the Microsoft Azure cloud platform. Their primary focus is on building and managing data pipelines, data lakes, and big data solutions using various Azure data services and technologies. The role of an Azure Data Engineer is to develop scalable and secure data solutions that can handle large volumes of data, process it efficiently, and provide valuable insights to business stakeholders. In addition, Azure Data Engineers are responsible for implementing data security and compliance solutions. They also monitor and troubleshoot Azure data solutions.
Exam DP-203: Data Engineering on Microsoft Azure is a certification exam offered by Microsoft that validates the skills and knowledge of professionals in building and designing modern data solutions on the Microsoft Azure cloud platform. The DP-203 exam measures a candidate's proficiency in various areas of data engineering on Azure, including designing and implementing Azure data storage solutions, data integration and transformation solutions, data processing solutions, and data security and compliance solutions. It also covers topics such as monitoring and troubleshooting Azure data solutions, designing and implementing solutions for data governance, data quality, and data lineage, and implementing machine learning and artificial intelligence solutions on Azure.
This is an online exam and the cost for the exam is $165 USD ( Price based on the country or region in which the exam is proctored).
The Duration of DP-203 Exam is 120 mins (2 hours).
All technical exam scores are reported on a scale of 1 to 1,000. A passing score is 700 or greater. As this is a scaled score, it may not equal 70% of the points. A passing score is based on the knowledge and skills needed to demonstrate competence as well as the difficulty of the questions.
The exam can taken in the following languages: English, Chinese (Simplified), Japanese, Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian, and Indonesian (Indonesia).
The Certification focuses on the skills required to be a successful Azure Data Engineer in the industry today. This includes these general domains and their weightage in the exam:
- Design and implement data storage (15–20%)
- Develop data processing (40–45%)
- Secure, monitor, and optimize data storage and data processing (30–35%)
- If you don’t pass an exam the first time, you must wait 24 hours before retaking it.
- A 14-day waiting period is imposed between all subsequent attempts (up to 5).
- You may not take a given exam more than five times within a 12-month period from the first attempt. If you failed the exam 5 times, you will be eligible to retake it again 12 months from the date of your first attempt.
- You cannot retake an exam you’ve passed unless your certification has expired.
- You must pay to retake the exam (if applicable).
For most exams, you’ll have results within minutes of finishing the exam. You’ll also get a report with your exam score and feedback on your performance. Exams with labs take about 30 minutes to score, so you’ll have to wait a bit longer. Your score will be available in your Learn profile within 24 hours.
There’s no cost to renew your certification, just make sure you pass the online assessment before your certification expires. You can take the renewal assessment any time during your six-month eligibility window, via Microsoft Learn. Once you pass, your certification will be extended one year from the expiration date.
This certificate will be provided by Microsoft to professionals who are able to prove their expertise and knowledge by successfully passing the DP-203 exam.
To unlock Edureka’s Azure Data Engineering Training completion certificate, you must ensure the following:
- Completely participate in this Azure Data Engineering Training Course.
- Evaluation and completion of the quizzes and projects listed.
Data Engineering is a great career option. With the rise of Big Data, businesses are looking for ways to collect, store, and analyze vast amounts of data. Data engineering is a rapidly growing field with excellent job prospects and high earning potential. According to the Bureau of Labor Statistics (BLS), employment of computer and information technology occupations, which includes data engineers, is projected to grow 11% from 2019 to 2029, much faster than the average for all occupations.
Beginners can become familiar with Azure data engineering services easily as it is a user-friendly cloud-based platform. Learning its capabilities and functionality requires appropriate direction and a well-structured training path. Beginners interested in a career in data engineering using Azure can sign up for our training and earn certificates to demonstrate their expertise in this domain.
An Azure Data Engineering Certification is a valuable investment in one's career as it validates skills in Azure Data Engineering, enhances career prospects, and opens up new job opportunities with increased earning potential. The demand for Azure Data Engineering is on the rise, and there are many profitable employment possibilities and positions in tech organizations, making this the ideal time for candidates to enroll and earn certification. Due to the wide range of job options and prospects, learning Azure Data Engineering skills and starting to work straight away is also strongly recommended.
Our Azure Data Engineering Training certification course is designed to develop skills and evaluate candidates' knowledge. Following the completion of this certification, you will have access to a wide range of job possibilities. Some of the most important employment roles include Azure Data Engineer, Azure Architect, Azure Cloud Engineer, Data Architect, Data Analyst, etc.
Please visit the page which will guide you through the Top Azure Data Engineering Interview Questions and Answers.
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Microsoft Azure Data Engineer Certification FAQs
What career options can I look forward to with my Azure Data Engineering skills?
The skills of a Azure data engineer are highly sought-after at present. You could be qualified for jobs such as Azure data engineer or data warehouse manager, database administrator and business intelligence analyst, and even data architect. Start the beginning step of registering for the Azure Data Engineer Online course.
What is the minimum education requirement to become an Azure Data Engineer?
There isn't a specific college degree required to become a Azure Data Engineer. People in this field typically hold a bachelor's or master's degree in physics, computer science, applied math, statistics, or other related fields. Even if you don't possess the educational qualifications, this course will help you start your career.
What is the average Azure Data Engineering Certification Cost?
The average Azure Data Engineering Certification Cost is $165 USD. The Price is based on the country or region in which the exam is proctored.
Is the Azure Data Engineering course hard to master?
The difficulty level in the Microsoft Azure Data Engineer Certification depends entirely on the individual's prior experience and commitment to learning the concepts. Our highly trained instructors explain everything in a way that is easy to comprehend. They are also aware of the students' requirements.
Does Azure Data Engineering require coding?
Although not necessary, it is highly recommended that you have a basic understanding of programming before pursuing a job in Azure Data Engineering.
Which is the best language to use for Azure Data Engineering?
Azure Data Engineering supports multiple languages, including Python, SQL, and Java. The best language to use may depend on the specific requirements of your project, but these languages are popular for ETL processes, data analytics, and machine learning tasks in Azure.
What are the criteria for admission to be a candidate for this Azure Data Engineer course?
There is no requirement for eligibility to enroll in our Azure Data Engineering course. Anyone interested in learning about the art of Azure data engineering can join our training course program and begin their journey. But, having a basic understanding of data structures and algorithms, SQL, Programming knowledge of Python and Java, Cloud platforms, distributed systems, and Data pipelines are helpful.
What are the most important skills you require to be a Professional Azure Data Engineer?
As a professional Azure Data Engineer, there are several skills that are essential for success. Here are some of the most important skills you will need:
- Data modeling and database design
- SQL and other query languages
- Data integration and ETL
- Data analysis and visualization
- Azure cloud services
- Programming languages such as Python and Java.
Is it possible for a fresh graduate to find job opportunities after completing the Azure Data Engineering course?
Completing an Azure Data Engineering course can definitely increase your chances of finding job opportunities as a fresh graduate. The demand for skilled data engineers who are proficient in cloud-based technologies like Azure is growing rapidly, as more and more companies are moving their data operations to the cloud.
How long will it take to become an Azure Data Engineer?
Attending the Azure Data Engineer Course Online, which may last anywhere from three to twelve months, can help you become a Professional Azure Data Engineer. The course curriculum, on the other hand, varies based on the degree or certification desired. 3-month courses can provide important Azure Data Engineer experience and internship possibilities, leading to entry-level positions at top businesses.
Why should I take Microsoft Azure Data Engineer Certification Course?
There are several reasons why taking the Microsoft Azure Data Engineer Certification Course can be beneficial for your career:
- High demand for skilled Azure data engineers
- Industry-recognized certification
- Comprehensive coverage of Azure data services
- Career advancement opportunities
- Personal and professional growth
What is the DP 203 Certification?
The DP-203 certification is a Microsoft certification that validates a candidate's skills and knowledge in designing and implementing data solutions using Azure Data Services. Specifically, the certification focuses on Azure Data Engineers who design and implement data storage, data processing, and data security solutions on Microsoft Azure.
What is the average salary of Azure Data Engineer across the countries?
Azure Data engineers are among the most sought-after professions today and earn high salaries globally. The possession of certification will increase their earnings potential.
Mentioned below are the average annual salaries of Azure Data Engineers in popular countries, as per Glassdoor data:
- India - INR 749,000
- UK - £58,549
- Canada - CA $84,505
- US - $1,02,723
Is Azure Certified Data Engineer worth it?
Yes, the Azure Data Engineer certification is an excellent way to demonstrate your skills in data Engineering. This Certification will increase the number of job opportunities, boost employees' pay, and increase career prospects over the long term. :
- Azure certificate expands job opportunities.
- Azure data engineer certification makes you more competitive.
- Azure Data Engineer Course provides better salaries.
- Azure certification helps you prepare to advance in your career.
How do I become an Azure data engineer?
To become an Azure data engineer, you can follow these steps:
- Acquire a strong foundation in data engineering concepts
- Familiarize yourself with cloud computing and Microsoft Azure
- Gain hands-on experience with Azure data services
- Practice and keep learning
Is Azure Data Engineering a good career?
Yes, Azure Data Engineering is a great career choice with plenty of opportunities for growth and advancement. Cloud computing and big data are two rapidly growing fields, and there is a high demand for skilled data engineers who can design, implement and maintain cloud-based data solutions using Microsoft Azure services.
What is the future of Azure Data Engineering?
The future of Azure Data Engineering is promising, with a growing demand for cloud-based data solutions and the adoption of new technologies such as AI, IoT, and blockchain. Here are some of the trends and developments that are shaping the future of Azure Data Engineering:
- Increased adoption of cloud-based data solutions
- Greater integration with AI and machine learning
- Increased emphasis on data security and privacy
- Growing demand for data analytics and visualization
Be future ready, start learning
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