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Azure Data Engineer [DP-203] Course in Mumbai

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Edureka's Azure Data Engineer course in Mumbai helps you clear the official Microsoft Azure Data Engineering Exam: DP-203 and gain expertise in the field. In the training, you will learn to design and implement data storage, develop data processing pipelines, and implement data security with relevant industry use cases. Get certified in Azure Data Engineering and learn from experienced industry experts with hands-on real-time project experience.

Live Online Classes starting on 4th May 2024

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Why enroll for DP 203: Data Engineering on Microsoft Azure in Mumbai?

Microsoft is recognized as a leader in the Gartner Magic Quadrant for Data Analytics and Business Intelligence Platforms for 12 consecutive years

According to Linkedin, Data Engineering is one of the fast growing jobs in technology with a growth rate of 40% year on year

Average salary for a Data Engineer is INR 10.5 Lakhs per year in India and in the United States, it is $114,835 per year in the United States - Indeed.com

Azure Data Engineer Training Benefits in Mumbai

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 Mumbai

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 Mumbai

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 in Mumbai

Azure Data Engineering Certification Course Curriculum in Mumbai

Curriculum Designed by Experts

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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 Engineer Course Description in Mumbai

What are the prerequisites for this Azure Data Engineering Course?

To enroll in the Mumbai course, you must have a basic understanding of Azure. You will also receive free self-paced videos on Azure Fundamentals.

What skills does an Azure Data Engineer in Mumbai need?

Azure Data Engineer Training in Mumbai 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 enroll in this Azure Data Engineering Training in Mumbai?

Those who are passionate about learning and aspire to become a Data Engineer or Data Architect in Mumbai can join this training.

Azure Data Engineer Projects in Mumbai

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....

View Project Details

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....

View Project Details

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....

View Project Details

Azure Data Engineering Certification - DP 203 EXAM in Mumbai

It's a Microsoft certification exam validating skills in building data solutions on Azure, costing USD 165.

The online exam costs USD 165, with pricing based on the country or region.

The DP-203 exam lasts for 2 hours (120 mins).

A passing score is 700 or greater on a scale of 1 to 1,000.

The exam is available in English, Chinese, Japanese, Korean, German, French, Spanish, Portuguese, Arabic, Russian, Chinese (Traditional), Italian, and Indonesian.

Designed and implemented data storage (15–20%), Developed data processing (40–45%), Secured, monitored, and optimized data storage and processing (30–35%).

You can retake the exam after 24 hours, with a 14-day wait between attempts (up to 5) and at most five attempts in 12 months.

Results are available within minutes for most exams, with a report on your score and feedback. Labs take about 30 minutes to score.

Renew for free by passing the online assessment before it expires, extending it for one year from the expiration date.

Microsoft issues the certificate upon passing the DP-203 exam.

Full participation, quiz, and project completion in the course are required.

Yes, with a projected 11% growth in data engineering jobs, it offers excellent career prospects and earning potential.

Beginners can easily learn DP-203 certification course through user-friendly cloud-based platforms like Azure, with structured training paths.

It's a valuable career investment, validating skills, enhancing prospects, and opening doors to new job opportunities.

Roles include Azure Data Engineer, Azure Architect, Azure Cloud Engineer, Data Architect, and Data Analyst.

Refund policies vary, and learners can request a refund within a specified period if dissatisfied with the course content.

Yes, visit the page for top Azure Data Engineering Interview Questions and Answers.

Duration varies, with weekend classes lasting around 6.5 weeks and weekday classes lasting 18 to 20 days from Monday to Friday.

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Data Engineer Course in Mumbai

What companies in Mumbai are hiring Data Engineers?

IBM

Microsoft

Facebook

Oracle

Amazon

What career options can I look forward to with Data Engineering skills in Mumbai?

Data engineering skills can lead to various roles such as data engineer, data warehouse manager, database administrator, business intelligence analyst, and data architect in Mumbai.

What is the minimum education requirement for Azure Data Engineer Training?

No degree is required—a bachelor's or master's in relevant fields is common. The Mumbai Data Engineering course can kickstart your career without formal education.

How much is the average Azure Data Engineer Certification Cost in Mumbai?

Azure Data Engineer Training in Mumbai 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's Data Engineer course, there is no reason to believe that you won't make more money.

Which is the best language to use for Azure Data Engineering?

Java, Python, R, SQL, and Scala are widely used languages in Mumbai for Data Engineering.

What are the criteria for admission to the Azure Data Engineer course?

Anyone can join to learn Data Engineering using Azure in Mumbai. A basic understanding of data structures, algorithms, SQL, Python, Java, Cloud platforms, distributed systems, and Data pipelines is helpful

What are the most important skills for a Data Engineer in Mumbai?

Proficiency in Java, Python, or C++, relational databases, SQL, data warehousing, Apache Spark, data mining, and data modeling are crucial skills for a Data Engineer in Mumbai.

After completing the Data Engineer course, are there job opportunities in Mumbai for fresh graduates?

Yes, enroll in this course in Mumbai and understand Algorithms, data structure, SQL, Programming (Python and Java), Cloud platforms, distributed systems, and data pipelines for better job prospects.

How long will it take to become a Data Engineer in Mumbai?

The duration of Edureka's Data Engineer Course in Mumbai varies from 3 to 12 months, depending on the curriculum and desired certification.

Why should I take the Microsoft Azure Data Engineer Course in Mumbai?

The course certifies you as a data science expert, enhancing job opportunities, pay, and long-term career prospects in Mumbai.

What is the Data Engineer Certification DP 203?

This exam evaluates technical skills in Azure data storage, processing, security, monitoring, and optimization.

What is the average salary for Microsoft Data Engineer Certification in Mumbai and globally?

Data engineers in Mumbai earn over 830k INR annually, with global salaries ranging from £43,401 (U.K.) to $94,358 (U.S.). The Azure Data Engineer Course in Mumbai is worth it, as it certifies expertise and improves job opportunities, pay, and career prospects.

Which certificate is best for the Azure Data Engineering Course in Mumbai?

Certificates like Microsoft Certified: Azure Data Engineering, Google Professional Data Engineer, and Cloudera Certified Professional Data Engineer are suitable for Data Engineers.

Is Azure Data Engineering Training a good career in Mumbai?

Yes, as long as there's data, Data Engineers will be in demand, contributing to an organization's success in Mumbai.

What is the future of Azure Data Engineering Training in Mumbai?

Data engineers in Mumbai will prioritize performance-focused elements and specialized functions with the shift to cloud solutions.

Which is better, a Data Engineer or Data Scientist?

Simply said, a data scientist can interpret data only after having received the data in the correct format. The role of the Data Engineer is to deliver the data to the hands of an expert in data science. Today, a Data Engineer is more popular than a Data Scientist because tools cannot perform the Data Engineer's duties. However, a Data Engineer can earn as much as $90,8390 per year, whereas an individual who is a data scientist earns $91,470 per year. If you compare these numbers of the Data Engineer and the Data Scientist, you may not notice a significant distinction initially. If you look more deeply into numbers, the data scientist can earn between 20 and 30% more than the average Data Engineer.

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