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Azure Data Engineer Course Online in Australia
Azure Data Engineer Course Online in Australia
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Why enroll for DP 203: Data Engineering on Microsoft Azure in Australia?
Azure Data Engineering Training Benefits in Australia
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 in-demand and rapidly expanding technologies in the marketplace right now. According to Microsoft, 95% of Fortune 500 firms use Azure cloud services, leading to an increasing demand for Microsoft-certified experts who can leverage Azure and manage massive volumes of data. The best way to secure a good job with a handsome salary in this domain is to obtain an Azure Data Engineer Certification.
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Why DP 203: Data Engineering on Microsoft Azure from edureka in Australia
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 in Australia
Tools Covered in Australia
Azure Data Engineer Certification Course Curriculum in Australia
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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- Navigating through Azure data engineering services
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- Use the data factory copy activity
- Manage the self hosted integration runtime
- Setup the Azure integration runtime
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- Explore Azure Synapse Analytics
- Create pools in Azure Synapse Analytics
- Identifying Azure Synapse pipeline components
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- Data Loading in Azure Synapse Analytics
- Data Ingestion using Copy Activity
- Implement workload management
- Understand performance issues related to tables
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- Manage authorization through column and row level security
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- Working with the Azure Data Solutions with Azure Synapse Analytics
- Build and deploy Azure Data Solutions with Power BI
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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
![skill]( "skill 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
![skill]( "Hands On Experience")
- 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 Engineer Course Description in Australia
Who is an Azure Data Engineer in Australia?
An Azure Data Engineer in Australia is responsible for extracting, transforming, and loading data from various sources into data warehouses.
What are the prerequisites for this Azure Data Engineering Course in Australia?
Basic knowledge of Azure is required, and the course provides free, self-paced videos on Azure Fundamentals.
What are the Azure Data Engineer Skills in Australia?
Azure Data Engineer Course in Australia DP-203 certification exam will test your following skills:
- Azure Databricks
- Azure Data Factory
- Azure Synapse
- Creating ETL Pipelines
- Data Warehousing using Azure SQL
- Azure Storage
- Integration with PySpark, PowerBI and Delta Lakes
Who should go for this Azure Data Engineering Training in Australia?
Anyone in Australia with a passion for learning and aiming to become an Azure Data Engineer or Data Architect can join this training.
Azure Data Engineer Projects in Australia
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....
DP 203 Certification Exam in Australia
Results for the DP-203 exam are typically available within minutes, and detailed feedback is provided within 24 hours.
An Azure Data Engineer in Australia designs and implements data solutions on Microsoft Azure for efficient data processing and valuable business insights.
The DP-203 certification validates skills in designing and implementing data solutions using Azure Data Services.
Candidates in Australia with expertise in integrating, transforming, and consolidating diverse data systems should take the DP-203 exam.
The DP-203 Exam in Australia certifies proficiency in various areas of data engineering on Azure, including storage, integration, processing, security, and compliance.
The cost of the DP-203 exam in Australia is $165, but it may vary depending on the location where the exam is proctored.
The DP-203 Exam duration in Australia is 120 mins (2 hours).
The passing score for the Azure DP-203 certification exam in Australia is 700 out of 1000.
The DP-203 Certification Exam in Australia is available in English and various other languages, including Chinese, Japanese, Korean, German, French, Spanish, and more.
Key topics covered in the Microsoft Azure DP-203 Exam in Australia include data storage, data processing, and securing, monitoring, and optimizing data solutions.
In Australia, you can retake the DP-203 exam up to 5 times within 12 months.
If you fail the DP-203 exam, you must wait 24 hours before retaking it and can access the certification dashboard to reschedule.
If you fail the DP-203 exam, you must wait 24 hours before retaking it, with a 14-day waiting period between subsequent attempts.
The DP-203 certification is valid for one year, with no prior certification required.
There's no cost to renew the DP-203 certification; pass the online assessment before it expires via Microsoft Learn.
Microsoft awards the Azure Data Engineer Certificate in Australia to professionals passing the DP-203 exam.
To unlock Edureka's Azure Data Engineering Training certificate in Australia, fully participate in the DP-203 Course, and complete quizzes and projects.
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Microsoft Data Engineer Course in Australia FAQs
Which companies hire Azure Data Engineers in Australia?
Companies hiring Azure Data Engineers in Australia:
- Microsoft Australia
- Commonwealth Bank of Australia
- ANZ Banking Group
- Westpac Group
- National Australia Bank (NAB)
- Telstra
- Qantas Airways
- Woolworths Group
- SEEK Limited
- Australia and New Zealand Banking Group Limited (ANZ)
Who benefits from Microsoft Azure Data Engineer Certification in Australia?
This certification helps design secure data processes and explore data using Azure tools.
What career options can I explore with Data Engineering skills in Australia?
Career options in Australia include roles such as data engineer, data warehouse manager, database administrator, business intelligence analyst, and data architect.
What's the minimum education requirement to become a Data Engineer in Australia?
There isn't a specific college degree required to become a 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 Data Engineer course will help you start your career.
How much does the average Azure Data Engineer Certification cost in Australia?
Data engineers are paid an average salary that is more than 830k annually for India and $116K for those in the U.S. With the addition of relevant experience and getting an industry-respected certification, such as Edureka'sData Engineer Certification in Australia, there is no reason to believe that you won't make more money.
Does Data Engineering require coding skills?
The difficulty level in the Microsoft Data Engineer Certification in Australia 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.
What are the Azure Data Engineer job opportunities in Australia?
Although not necessary, it is highly recommended that you have a basic understanding of programming before pursuing a job in Data Engineering.
Which is the best language to use for Data Engineering?
Java, Python, R, SQL, and Scala are the most widely utilized languages in the area of Data Engineering
What are the essential skills needed to be a Data Engineer in Australia?
Azure Data Engineer job opportunities in Australia:
- Azure Data Engineer
- Data Engineer (Azure)
- Big Data Engineer (Azure)
- Data Platform Engineer (Azure)
- Cloud Data Engineer (Azure)
- Data Warehouse Engineer (Azure)
- Data Integration Engineer (Azure)
- Business Intelligence Engineer (Azure)
- ETL Developer (Azure)
- Data Analytics Engineer (Azure)
What is the average pay scale of an Azure Data Engineer professional in Australia?
The average annual salary ranges from AUD 90,000 to AUD 150,000 for Azure Data Engineers in Australia.
How long does it take to become a Data Engineer in Australia?
The Data Engineer Course in Australia takes 3-12 months and helps individuals become data engineers with varying certifications
Can fresh graduates find job opportunities after completing the Data Engineer course in Australia?
Yes, enrollment in the Azure Data Engineer Certification Training in Australia is open to anyone interested in starting a career in Data Engineering, provided they understand fundamental concepts.
Why should I take Microsoft Azure Data Engineer Course in Australia?
The Data Engineering Course is the one to take if you want to work with businesses because it certifies you as an expert in data science. After finishing our comprehensive program, you'll have the skills you need to succeed as a data engineer and a job-ready portfolio to show off during the interview process.
What is the Average Payscale of a Azure Data Engineer professionals in Australia?
The average annual salary of an Azure Data Engineer professional in Australia ranges from AUD 90,000 to AUD 150,000. However, the actual salary can vary based on factors such as experience, skills, qualifications, and the employing organization.
Why should I take the Microsoft Azure Data Engineer Course in Australia?
This exam evaluates your capability to perform technical functions. Design and implement storage for data; design and create data processing; develop and establish data security and monitoring and optimize data storage and processing storage.
What is the market trend for Azure Data Engineer in Australia?
Demand for Azure Data Engineers in Australia is rising due to the increased adoption of Microsoft Azure for cloud data solutions, leading to more job opportunities.
How do I become an Azure data engineer in Australia?
To become a certified Azure Data Engineer in Australia, proficiency in data computation languages such as SQL, Python, or Scala and knowledge of data architecture concepts is necessary.
Which certificate is best for the Azure Data Engineering Course in Australia?
Suitable certifications for data engineers in Australia include Microsoft Certified: Azure Data Engineering, Google Professional Data Engineer, and Cloudera Certified Professional (CCP) Data Engineer.
Is Azure Data Engineering Training a good career in Australia?
Yes, as long as there's data to process, Data Engineers will be sought-after in Australia, contributing to organizational success with programming and problem-solving skills.
What is the future of Azure Data Engineering Training in Australia?
The trend in Australia involves increased demand for Azure Data Engineers, especially with expertise in cloud-based solutions, big data and analytics, data integration, and AI/machine learning.
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