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Instructor-led Azure Data Engineering Course by PwC live online Training Schedule
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Why enroll for Applied Data Engineering on Azure Cloud Course?
Applied Data Engineering on Azure Cloud Training Benefits
The global big data and data engineering services market size is anticipated to be worth USD 169.9 billion by 2029 from USD 75.55 billion in 2024, growing at a CAGR of 17.6% from 2024 to 2029. Almost 56 percent of organizations worldwide use Microsoft Azure for their cloud services. This growth underscores the increasing demand for data engineering expertise and the strategic importance of data-driven decision-making in businesses globally.
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Why Applied Data Engineering on Azure Cloud Course 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 Applied Data Engineering on Azure Cloud Course
Applied Data Engineering on Azure Cloud Skills Covered
Applied Data Engineering on Azure Cloud Tools Covered
Applied Data Engineering on Azure Cloud Course Curriculum
Curriculum Designed by Experts
Migrating SSIS to Azure Data Factory: Pipeline Design and Execution
8 Topics
Topics:
- ETL Process
- Azure data factory
- Integration Runtime
- SSIS (SQL Server Integration Service)
- Azure SQL DB
- Create a pipeline in ADF and data flow.
- Various Dataflow activities available in ADF
- Scheduling and monitoring a package in ADF
![skill]( "Hands On Experience")
- Create an SSIS package and deploy it in Azure SSISDB.
- Create an ADF pipeline 'Execute SSIS Package'.
- Create SSIS IR and map existing SSISDB
- Scheduling an SSIS package through a trigger
![skill]( "skill you will learn")
- Data Integration
- Manage Databases
- Monitor Data Pipelines
Use Case: Integrate Employee learning records for HR Datawarehouse Part - I
5 Topics
Topics:
- Extracting learning records from SFTP location to ADLS
- Pandas in Python
- Azure Databricks
- Create a notebook activity in ADF to process raw csv files into dataframes and once done write modified dataframe into output csv files.
- Process output csv files and load into target staging tables of SQL DB
![skill]( "Hands On Experience")
- Explore Azure Databricks
- Run an Azure Databricks Notebook with Azure Data Factory
- Use a SQL Warehouse in Azure Databricks
- Use pandas to process csv files in ADB
![skill]( "skill you will learn")
- Data Manipulation tasks
- Database Querying
- Big Data Processing
Use Case: Integrate Employee learning records for HR Datawarehouse Part - II
5 Topics
Topics:
- Data Processing with Azure
- Apache Spark in Azure Databricks
- Execute stored proc to process staging table data into main tables of DW and truncate staging table for next day's load.
- Load process will be based on incremental or Upsert logic.
- Maintain a history table where everyday's data feed will be kept aside for future audit purposes or RCA analysis.
![skill]( "Hands On Experience")
- Use Spark in Azure Databricks
- Use Azure monitor to observe daily data flow and errors occur.
![skill]( "skill you will learn")
- Data Processing
- Manage Azure Resources
Reporting and Data Analysis with Microsoft Fabric
7 Topics
Topics:
- Azure OneLake
- Microsoft Fabric overview and features
- Fabric data factory
- Fabric synapse analytic
- Spark notebook in Fabric Synapse analytic
- Data storage in Lake database of Fabric One lake
- Data visualization and reporting using Power BI
![skill]( "Hands On Experience")
- Explore Microsoft Fabric data tool.
- Extraction data from API using Data factory data flow.
- Store raw JSON data in One lake.
- Transform raw data into clean tabular format and store in Lake database of one lake.
- Use this table data referring Power BI dashboard and report.
![skill]( "skill you will learn")
- Data Visualization and Reporting
- Data transformation
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Applied Data Engineering on Azure Cloud Course Details
About PwC Academy
PwC Academy is a learning and education service offering of PwC India. It provides diverse training courses based on the best practices of PwC’s global network of firms and brings real-life business experiences into the classroom. Moreover, subject matter experts help to make learning more effective and practical.
PwC Academy focuses on improving the knowledge, skills, competence, and expertise of professionals and students by offering diverse learning programs in areas such as financial accounting and reporting, risk, governance, and digital.
About this Applied Data Engineering on Azure Cloud Course
This course covers multiple industry-specific use cases, giving learners practical understanding and hands-on experience with Azure data engineering. Starting with migrating SSIS packages to Azure Data Factory (ADF) and creating pipelines, learners will delve into ETL processes, Azure SQL Database integration, and scheduling within ADF.
Learners will be equipped with practicals to integrate HR learning records using Azure Databricks, focusing on data extraction, transformation with notebooks, and loading into SQL Data Warehouse. The course concludes with data analysis using Microsoft Fabric, including Spark analytics, Python scripting, and Power BI visualization, providing comprehensive skills in ADF, Databricks, SQL Data Warehouse, and data visualization tools.
What are the prerequisites for this Applied Data Engineering on Azure Cloud course?
There are no prerequisites for this course. However, it would be beneficial to have basic knowledge of SQL and an understanding of Azure Data Factory (ADF).
What will you learn from this Applied Data Engineering on Azure Cloud course?
By the end of the course, you will be able to:
- Create Simple SSIS package i.e. ETL flow
- Develop Pipeline and Dataflow in ADF
- Schedule a pipeline in ADF
- Pull out Employee's Learning records
- Create a notebook to process the raw csv files as per business requirements
- Load data into Azure SQL database staging table
- Transfer data from Stage to Main table using Upsert logic
- Extract data from API using Fabric data factory
- Transform data using spark in Microsoft fabric
- Visualize data using Fabric Power BI
Who should go for this Applied Data Engineering on Azure Cloud Training?
This Azure training course is specifically designed for:
- Individuals looking to establish their credibility and value in the market as experienced
- Data Engineers
- Data Architects
- Data Analysts
- Database Administrators
- Developers
- IT Professionals
- Freshers
What are the roles and responsibilities of an Azure Data Engineer professional?
Azure Data Engineers are specialists who combine expertise in data management and Azure services. They play a crucial role in designing, implementing, and managing data solutions on the Azure platform. The following are some key responsibilities of an Azure Data Engineer:
- Designing Data Storage Solutions
- Building and Maintaining Data Pipelines
- Data Modeling and Optimization
- Implementing Data Security and Compliance
- Monitoring and Troubleshooting
These professionals play a crucial role in managing data throughout its lifecycle within Azure, ensuring it is secure, accessible, and optimized for various analytical and operational needs.
What is the scope of Azure Data Engineering?
The field of Azure Data Engineering holds immense promise for the future, with numerous organizations gearing up to leverage its capabilities. Azure Data Engineering is continuously evolving with the introduction of new tools and technologies aimed at optimizing organizational processes through automation. Reports indicate a robust growth trajectory, forecasting substantial market expansion from its current size. Many enterprises are adopting Azure Data Engineering to automate data workflows and enhance operational efficiency.
What are the system requirements for this Applied Data Engineering on Azure Cloud course?
The following specifications are the recommended system requirements for this Azure Data Engineering course:
- Operating System: Any modern operating system that supports the required tools and services (e.g., Windows, macOS, Linux).
- Processor: A 64-bit processor with a minimum speed of 2GHz or higher is recommended for optimal performance, especially when running Azure-related tools and services.
- Memory (RAM): At least 8 GB of RAM is advisable to meet the requirements of running Azure services, development environments, and data processing tasks simultaneously.
- Storage: Sufficient free storage space for installing various Azure tools, SDKs, and other required software components. At least 20 GB of free space is advisable.
- Browser: Compatibility with modern web browsers for accessing Azure Portal, online resources, documentation, and web-based tools used in the course.
How will I execute the practical during this Applied Data Engineering on Azure Cloud course?
Detailed step-by-step installation guides are available on the LMS. In case you come across any doubt, the 24*7 support team will promptly assist you.
Applied Data Engineering on Azure Cloud Certification
To unlock the course completion certificate from PwC Academy and Edureka, you must ensure the following:
- Completely participate in this Applied Data Engineering on Azure Cloud Certification course.
- You must complete all modules along with the graded assessments.
Yes, Azure Data Engineering is a highly promising career choice in 2024 and is anticipated to maintain its significance in the foreseeable future. Here are several reasons why:
- High Demand: There is a strong need for Azure Data Engineering professionals in the IT sector. Companies are increasingly adopting cloud-based data solutions to handle big data, analytics, and business intelligence. This demand leads to a strong job market with plenty of opportunities.
- Lucrative Salaries: Azure Data Engineers usually earn competitive salaries, frequently higher than the average IT professional. Salaries vary based on experience, skills, and location, but the potential for high earnings is strong.
- Career Progression: Azure Data Engineering provides a defined career trajectory with chances for growth. You have the opportunity to begin as a Data Engineer and advance to roles like Senior Data Engineer, Data Architect, or specialize in areas such as Data Science or Machine Learning Engineering.
- Future-Ready Skills: Azure Data Engineering skills are essential for modern data management and analytics. As businesses increasingly focus on data-driven decision-making, the need for Azure Data Engineering skills is expected to remain high.
Azure Data Engineering presents an enriching career opportunity for those who are enthusiastic about advancing organizational achievements by leveraging Microsoft's cloud-based data solutions.
Applied Data Engineering on Azure Cloud certification confirms an individual's proficiency in designing and implementing data solutions using Microsoft Azure services. These certifications cover a broad range of topics, including data storage, data processing, data security, and data integration. Specific areas of focus include Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure SQL Database.
Azure Data Engineering is a field with significant growth potential. As a data engineer, it is crucial to have a thorough understanding of ETL processes, data pipelines, and data management. Azure Data Engineering certifications equip professionals with the skills needed to handle complex data workflows, optimize data storage, and ensure data security, making them valuable assets in the data-driven landscape of modern enterprises.
This course covers advanced Azure Data Engineering topics, and freshers with a fundamental understanding of Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure SQL Database will find it very helpful.
The value of obtaining an Applied Data Engineering on Azure Cloud Certification is multi-faceted:
- Enhanced Career Opportunities: Co-branded certification from PwC and Edureka demonstrates your expertise in Azure data engineering, making you a more desirable candidate for job opportunities. It can lead to higher earning potential in various industries and roles, including data engineer, data analyst, and data architect.
- Skill Validation: It validates your skills and knowledge in areas such as data integration, data transformation, data storage, and data security on the Azure platform. This gives you confidence in your abilities to effectively implement data engineering solutions within organizations.
- Industry Recognition: Employers often seek candidates with recognized certifications. An Azure Data Engineering certification demonstrates your commitment to staying up-to-date in the field and your proficiency in using Azure tools and technologies.
- Personal Growth: Certification reflects a commitment to continuous learning and professional growth, helping you stay relevant in a rapidly evolving field. It ensures you are knowledgeable about the latest advancements and best practices in data engineering.
- Employer Benefits: Employers benefit from having certified Azure data engineers on their teams who can leverage Azure services to build, manage, and optimize data solutions. Certified professionals can help improve data-driven decision-making, enhance data security, and streamline data processes.
After completing an Applied Data Engineering on Azure Cloud, you will be eligible for job roles such as:
- Azure Data Engineer
- Data Architect
- Data Analyst
- Database Administrator
- Data Scientist
- Data Engineer
- ETL Developer
- Lead Data Engineer
- Principal Data Engineer
Top Companies such as Microsoft, Deloitte, Adobe, Infosys, Mercedes Benz, IBM, Wells Fargo, Wipro, TCS, Capgemini, L&T Technologies, Mitsubishi, Honeywell, Nike, Visa, and many more are frequently hiring for the role of Azure Data Engineers.
Please visit the page that will guide you through the top Azure Data Engineer Interview Questions.
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Applied Data Engineering on Azure Cloud Course FAQs
What if I miss the Applied Data Engineering on Azure Cloud Course classes?
You will never miss a lecture at Edureka! as you can always view the recorded session of the class available in your LMS.
So, what are you waiting for then, let’s enroll with Edureka and learn the best Azure Data Engineering course online with India's top instructors.
Can I change the batch after enrolling in this Applied Data Engineering on Azure Cloud Course?
No, we don't allow batch changes as it impacts your learning and career goals.
What is the role of the PwC Academy in this Applied Data Engineering on Azure Cloud course?
This Applied Data Engineering on Azure Cloud course has been designed and developed by PwC Academy, and SMEs from PwC Academy will conduct the master class.
What is the refund policy for the Applied Data Engineering on Azure Cloud course?
This Applied Data Engineering on Azure Cloud course, offered jointly by PwC and Edureka, is Non-Refundable.
What if I have queries after I complete this Applied Data Engineering on Azure Cloud course online?
Your access to the Support Team is for a lifetime and will be available 24/7. The team will help you resolve queries during and after the completion of this certification course.
How soon after signing up would I get access to the Learning Content?
Yes, once you enroll in the Applied Data Engineering on Azure Cloud course, you will have lifetime access to the course material.
Who are the instructors for this Applied Data Engineering on Azure Cloud course?
All the instructors at Edureka are industry practitioners with a minimum of 10-12 years of relevant IT experience. They are subject matter experts trained by Edureka to provide an excellent learning experience to the learners.
Is this course 100% online? Do I need to attend any physical classes?
This course is 100% online, and there will be no physical classes. This course can be accessed through the web on any device.
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