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👨🏫 10+ Years Experience
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📅 Course Duration
2 1/2 Months
💰 Course Price
₹ 25000
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📄 Course Content
Azure Data Engineer in Hyderabad
Graduate to compete successfully in the competitive world through our advanced and integrated curriculum. Version IT is the best institute for Azure Data Engineer Training in Hyderabad that includes essential solution skills in Infrastructure as a Service (IaaS), Platform as a Service (PaaS) as well as Software as a Service (SaaS), namely, virtual computing, storage, networking and data analysis.
Overview
Moreover, the training will increase your expertise in the most popular public clouds in the world. The Google Cloud Platform (GCP) is also integrated in our Azure Data Engineer Course in Hyderabad, which aligns with the industry requirements, so you will not only obtain theoretical knowledge but also practical skills to succeed.
Overview on How to Master in Azure Cloud Data Engineer in 2025
Version IT is offering the Azure Data Engineer Training in India from anyplace online that will equip you to analyze the flexible cloud system of Azure. In addition, our course material entails all the processes and procedures that are necessary to emerge successful in the stiff cutthroat competition in the profession.
- Complete Azure fundamentals: Learn the fundamentals and basics of becoming a professional data engineer.
- Real-World Project Experience: Excel using real-world projects, since in practice is the most important way to fast track knowledge.
- Collaborative Learning Environment: Version IT promotes a team based learning environment to sharpen your communication, problem solving and teamwork skills.
- Industry-Relevant Case Studies: Use the working cases that are relevant to the field to learn more about the challenges that Azure Data Engineers can encounter.
Azure Cloud Data Engineer Course: Key Features
The quality of our curriculum created by our experts is good to both novices and seasoned workers.
- The course incorporates both theoretical and practical education as per the existing requirements in the software industry.
- The students get special staff help in resume writing, interviewing skills, and placement services to enable them realize their career objectives.
- It includes hiring assistance which we offer the students once the training has completed so as to kick start their career.
- There are special laboratory centers that people can attend to sharpen the acquired practical skills in the course.
- Other courses that are provided online and have flexible schedules are also offered by us.
Skills Covered in our Azure Data Engineer Coaching
- Create, operate, and automatic data pipelines with SQL and Azure Data Factory.
- Exquisite, useful knowledge of Databricks and PySpark to process and analyse large volumes of data.
- Know the rules of storing and management of data in Data Lake and Delta Lake architectures.
Azure Cloud Data Engineer Course Prerequisites & Eligibility
They need to know the basics of SQL and Python, but not mandatory. Every applicant is welcomed to work with our team of cloud data engineers.
Eligibility to Apply Azure Cloud Data Engineer Course:
- The candidate should have a Bachelor’s degree.
- IT and non-IT candidates are acceptable
- Programmers of all levels are invited as the program will be created to develop the basic programming knowledge to those who have no programming experience previously.
- Employment gaps of no more than three years are also acceptable to the applicant.
Detailed Azure Data Engineer Classes Curriculum
Module 01: Introduction to Big Data
Module 02: Data transformation for Business Intelligence.
Module 03: Social Networking with Hadoop.
Module 04: ADF & Databricks Integration
Why Version IT is the best Azure data engineer training institute in Hyderabad?
- Full Placement Dedication: We specially assist loyal candidates to get good jobs.
- Flexible Learning Methods: One can choose to learn either classroom or Azure Data Engineer Online Training In Hyderabad
- What our alumni have achieved: Over 100,000 successful alumni have reached their dreams through us. It is the start of your success history.
- Updated Curriculum: We constantly update our curriculum to be up to date with the latest and most popular in-demand skills, to ensure that you stay at the top of the game.
- Professional Instructors: Study under industry experts who have had years of practical experience, as well as, innovative teaching techniques that assure a profound level of knowledge.
- End to End Career Support: We teach more than teach. We also equip you to be in the job market through resume development, interview training and job placement.
- Established Student Satisfaction: Our history of changing careers is supported by favorable feedback of our students.
Version IT by the Numbers
- 50,000+ Students Trained
- 15,000+ Professionals Placed
- 250+ Corporate Hiring Partners
- 10+ Years Experience in the Industry per Trainer.
- Job-Oriented Intensive Programs (JOIP)
Best Azure Data Engineer training in Hyderabad Certification
On successful completion of the training Azure Cloud Data Engineer, you will be provided with a professional certification by Version IT.
Certification Process:
- The entire training program.
- Complete all projects and assignments punctually.
- Get your formal certificate one week after the course is over.
Topics You will Learn
● Understanding different Cloud Models
● Advantages of Cloud Computing
● Different Cloud Services
● Different Cloud vendors in the market
● Introduction to Azure
● Azure cloud computing features
● Azure Services for Data Engineering
● Introduction of Azure Resources/Services with examples
● Azure management portal
● Advantage of Azure Cloud Computing
● Managing Azure resources with the Azure portal
● Overview of Azure Resource Manager
● Azure management services
● What is Azure Resource Groups
● Configuration and management of Azure Resource groups for hosting Azure
services
● Completed walkthrough of the Azure Portal with all the features
● What is Resource Groups and why do we need RG’s in Azure cloud computing
platform to host resources?
● Different types of Storage Accounts provisioning in Cloud computing with
different storage services
● Details explanation & understanding of different Blob/container storage
services
● Creating and managing the data in container storage services with Public and
Private accesses as per the need of a project
● Implementation of Snapshots for Blob storage services and File share storage
service
● Generating SAS for different storage services to make the storage content
browseable across all the globe or Publicly
● What is Standard Storage Account and Premium Storage account and which to
use accordingly as per the real time scenarios
● Detail explanation and implementation of Data Lake storage Gen2 Storage
Account to store the unstructured data in cloud storage services
● All the features/properties(Overview, activity log, Tags, Access control(IAM),
Storage browser…etc) of Azure Storage Accounts
● Maintenance and management of Storage keys and connection string for Azure
Storage services
● Implementing different levels of access(Reader, contributor, owners…etc) to the
Azure Storage accounts
● Moving the storage account with storage content across different Resources
Groups based on real time scenarios
● Migrating the data from On-prem(Private cloud) to Azure Storage account
(Public cloud) using Az copy(forward migration)
● Migrating the data from public cloud to Private cloud(reverse migration)
● Implementing the Az copy commands to migrate the data
● Moving the SA & its content from one Resource Group to another
● Azure Storage explorer for creating, managing, and maintaining the Azure
storage services data
● Installation of Azure Storage Explorer and what is the purpose of this tool for
Azure Storage accounts(its Purpose & benefits with real time scenarios)
● Generate Shared Access Signature(SAS) in Azure Storage Explorer(ASE) for
security implementation of Storage account content
● Managing of Access keys & connection strings of SA with Azure Storage
Explorer
● Configuration of Authentication and Authorization for Storage Account via
Azure Active Directory
● Hosting File share Storage services to On prem servers or Cloud Servers as
shared drive for File share servers
● Introduction to SQL DB’s
● Creation of new SQL DB’s & Sample SQL DB’s both in On-prem and Cloud
computing
● Planning and deploying Azure SQL Database
● Implementing and managing Azure SQL Database
● Managing Azure SQL Database security
● Planning and deployment of SQL DB’s in Azure cloud computing with real time
scenarios
● Different DB’s Deployment options
● Databases purchasing models.(VCore & DTU’s)
● Visualization of cloud DB server, Database, and validation of data from
on-prem(private cloud)
● Implementation of Firewall security rules on Azure DB servers to access and
connect from on-prem SSMS
● Creation of Database in on-premises and synch with azure cloud
● Migrating SQL DB’s from On-premises to Azure cloud computing using
Microsoft Data migration assistant
● Restoring SQL DB’s from On-prem to cloud computing
● Migration of Specific DB objects from on-prem to cloud based upon base upon
project requirements
● Implementation of RSV and scheduling the backups of SQL DB’s and Azure
Storage Account file share services on schedule, on demand based upon real
time scenarios
● Introduction to SQL DB Queries
● SQL queries detail explanations, syntax & execution based upon real time
scenarios
● Deep understanding and implementation of concepts/Components of ADF
● Building blocks of Azure Data Factory
● Complete features and walk through of Azure Data factory studio
● Different triggers and their implementation in ADF
● What is integration run time and different types of integration run time in ADF
● When to use ADF
● Why to use ADF
● Different types of ADF pipelines
● Pipelines in ADF
● Different types of Activities in ADF
● Datasets in Azure Data factory
● Linked services in ADF
● Copying the data from Blb Storage account to ADL’s Gen2 Storage account
● Copying of zip files(.csv) from Blob SA to ADL’s Gen2 SA using ADF
● Implementation and explanation of Metadata control in ADF to find the structure
before copying the data
● Implementation and explanation of Validation and If Condition
● Implementation of Get Metadata control, filter control & For Each Control or
activities in ADF
● Implementation & execution to copy the data from GitHub platform to Azure
Storage services with variables and parameters
● Implementation of Foreach control, copy data control and Set variable to
dynamically load the data from source to target using ADF
● Creating Dynamic pipelines with lookup activity to copy multiple .csv files data
picking form Json format data in Azure Storage services
● Copying the files from GitHub Dynamically with the use of Dynamic parameters
allocation-AUTOMATION PROCESS
● Copying the data from different files formats(.csv, .xlsx, .txt, .Parquet, .Json,
.SQL…etc) using suitable ADF controls/activities
● Implementation and execution of Loading the data from Blb SA to SQL DB single
table & multiple tables using copy data activity, ForEach activity
● Executing multiple pipelines in parallel with Execute pipeline activity
● Implementation of Schedule based triggers for different ADF pipelines
containing different activities.
● Implementation of Event based triggers for different ADF pipelines containing
different activities.
● Implementation of Thumbling window-based triggers for different ADF pipelines
containing different activities.
● Implementation and execution of storage and Event based triggers.
● Detail explanation & implementation of Azure Keyvaults
● Making the SQL DB connection string to store in Keyvault to enhance the
security for SA content and SQL DB
● Generating the secrets inside the Azure keyvault and granting access by
implementing the access policies for different users
● Detail walk through of GitHub portal
● Creating an account, repo’s, in GitHub portal
● Integrating Azure Data Factory with GitHub Portal as per project requirements.
● Placing, maintaining and executing the source code via GitHub portal for Azure
Data Factory.
● Creating master branch, practice branches in GitHub portal to merge the newly
created code via Pull Requests.
● Setting up the Repo for ADF pipelines and converting to live mode from GitHub
portal covering with real time scenarios.
● Designing new Data flows
● Designing and implementing transformations
● Inline Datasets in data flow source control
● Designing and implementing of Data flow with Source transformations, Filter
transformations & Sink transformations in ADF with inline Datasets
● Implementation of Select transformations with Data flows for various source
controls
● Implementation of Dataflows using Aggregate & Sink transformation
● Implementation of Dataflow with conditional split & Sink transformation with
copy data activity
● Implementation of Dataflow with Exists & Sink transformation
● Implementation of Azure Dataflows for Derived column transformation with
Source & Sink transformation
● Implementation of Azure Dataflows to connect to SQL DB with Source & Sink
transformation
● Union & Union flow transformation implementation with ADF Data flows
● Implementation of Azure Dataflows to connect to SQL DB with Source & Sink
transformation
● Implementation of windows functions…like Rank() function, Dense_Rank()
function, Row_Number() function…etc.
● What is Apache Spark, details explanation and implementation of Apache Spark
● Illustration and Elaboration of Apache Spark Architecture
● Explanation of RDD & DAG
● Understanding of different Apache Spark components
● What are worker nodes and slaves nodes in Azure Data Bricks clusters
● Implementation of Azure Databricks cluster by considering different worker
nodes and slave nodes
● Different features and properties of Azure Data Bricks clusters
● Creating single node and multi nodes clusters
● Creation of Pyspark notebooks in Databricks cluster to fulfil different business
requirements
● What is Azure Synapse Analytics
● Implementation of Linked Services/Datasets in Synapse Analytics
● Implementation of dedicated SQL Pool inside Synapse Analytics
● Implementation of serverless SQL Pool inside Synapse Analytics
● Creation of Apache spark pool in Azure Synapse Analytics
● Writing SQL Script in Azure Synapse analytics to get the result set in tabular and
chart formats
● Visualizing the data in Synapse analytics in variety of different charts (like pie
charts, line charts, bar charts…. etc)
● Designing of Synapse Analytics pipelines by considering various activities as
per the business requirements
● Creation of Datasets, Linked services for Synapse Analytics pipelines
● Data analysis with serverless spark pools in Azure Synapse Analytics
● What is Apache spark in azure synapse analytics
● Designing and development of Apache spark pool in Azure synapse
● Creating Spark Databases and tables to load the data from source system and
analysing the data in Synapse analytics
● What is Azure Stream Analytics
● Purposes and usage of Stream Analytics in Azure cloud computing
● Benefits and advantages of stream analytics
● Architecture diagram of data flow in Azure stream analytics with other cloud
services
● Understanding & usage of browser-based Raspberry Pi simulator
● Deployment of IoT Hub services as an input for Stream analytics jobs
● Implementation & execution of stream analytics jobs and designing inputs and
outputs for IoT Hub and Datalake Gen2
● Writing SQL scripts to generate live streaming data and loading it in destination
Let Your Certificates Speak
- Comprehensive training in Azure Data.
- Certificates are globally recognized & they upgrade your programming profile.
- Certificates are generated after the completion of course.
All You Need to Start this Course
- Engaging and interactive course content.
- Expert-led instruction for a deeper understanding.
FAQ's
Our training centers are all day on the working days and the training centers have our state-of-the-art lab infrastructure which you can use anywhere you want. In the case of online students, our servers and the lab facilities are available around the clock via the internet.
In the case of the classroom, you are allowed to attend the same session with another batch. In the case of Azure Data Engineer Online Training, each session is taped and you can watch at your own convenience and you may get to watch what was not covered.
Our trainers are all real time industry experts and with minimum experience of 10+ years. You can meet our instructors and check their profile before you enroll.
Our three flexible options are instructor-based classroom training, live instructor-based online training and self-paced video training.
Yes, we give group enrollment discounts and will organize tailor-made corporate training to your group. You can know more by contacting us.
