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Azure Data Engineer Training in Pune
Do you want to change your career and be a hot employee in the cloud market? In the era of big data organisations are turning to the cloud at a very rapid rate and Microsoft Azure is leading the pack. The need and demand of professionals with architectural, building, and management skills in regard to data solutions onAzure are immense.
Why a Career as an Azure Data Engineer?
Welcome to Version IT, the leader in Azure Data Engineer Online Training in Pune. Just graduated and want to enter the world of IT, or are you an expert whose skills have become outdated and need to be developed to match the industry? Our industry-optimized course will make you an Azure Data Engineer ready to work.
Why a Career as an Azure Data Engineer?
Data is the new oil, nevertheless, raw data is unproductive until it is refined with the proper engineering. The role of an Azure Data Engineer is to integrate, transform and consolidate the data of different structured and unstructured systems into formats that are compatible in the development of analytics solutions.
As Big Data continues to grow exponentially, firms in Pune and other parts of the world are in a frenzy to find specialists capable of managing the “Data Engineering on Microsoft Azure” (DP-203) stack. Once you have mastered such tools as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure Data Lake, you are ready to obtain highly paid positions in the leading MNCs.
We do not teach but we mentor at Version IT. As one of the top companies in the provision of Training in Azure Data Engineer, we fill in the gap between the theoretical and the practical. Our training philosophy is different as we are practical, based on scenarios, and preparing interviews.
By opting to pursue our Azure Data Engineer Course in Pune, you are opting to pursue a course that is designed by industry veterans possessing more than 10+ years of experience. Not only do we guarantee you that you pass the certification exam but also the confidence to handle difficult data engineering processes in a production environment.
Reasons Why Version It Is The Ideal Organization To Take Azure Data Engineer Course In Pune
There are many institutes that provide training, why do we?
- Modernized Material: The cloud evolves at a rapid pace. Our Online course on Azure Data Engineer is updated on a regular basis approximately after every few months with new features of the new azure.
- Interactive Learning: We are of the opinion that there should be two way communication. We have interactive and conversation oriented sessions.
- Backup Classes: Missed a Class? Access was obtained by capturing videos of each session via our LMS.
- Low Costs: Quality education should not be about cracking the wallet. We provide competitive prices that come in installments.
- Community Support: Become part of our group of alumni Data Engineers in leading companies.
Azure Data Engineer Course Highlights
- 100% Hands-On Training: Practice on real-life scenarios and applications.
- Professional Instructors: Train with professional and expert subjects.
- Certification Aligned DP-203: The course syllabus encompasses all areas of knowledge that are needed to complete the official Microsoft certification.
- Real-time Projects: Capstone projects which simulate real industry problems.
- Placement Assistance: Special help to assist you to get your dream job.
- Flexible Learning: Selecting between Training Azure Data Engineer online or in-person.
Version IT’s Azure Data Engineer Course Flexible Training Modes
We know that our students are unique and they have different needs. Version IT is flexible around your schedule whether you are an employee or a student.
- Online Training
Cannot travel to a center? No problem. Our online training, which is the Azure Data Engineer, is ranked as among the best in the industry. It is not a recording; it is an interaction, live instruction session during which you may pose questions to the instructor instantly. We implement high-end teamwork technologies to make the web-based classroom as authentic as a real classroom.
- Classroom Training
In case of physical contact, our Azure Data Engineer Training in Pune (classroom mode at Ameerpet) is provided with a specific learning environment and lab facilities with direct access of the mentor.
Azure Data Engineer Practical Projects
You cannot become an engineer by theory. Our course of data engineering online in Pune is based on Learning by Doing. The course projects will include three main projects:
- Retail Analytics Pipeline: Along high-levels, create an end-to-end pipeline to process the daily sales information of various retail stores, transform it with the Databricks, and load it into Synapse to report.
- Healthcare Data Migration: A safe migration project of patient-sensitive information, which can use stringent security measures and mask data during migration to the cloud.
- Real-Time Traffic Analysis: Consuming traffic sensor data through Event Hubs in real-time and processing them with Stream Analytics to determine traffic congestion trends.
These are meant to be included in your resume to provide you with some talking points to your technical interviews.
Who must take this Azure Data Engineer course?
The course of the Azure Data Engineer is provided to:
- ETL Developers: Who are professionals of tools such as Informatica, Talend, or SSIS, and are interested in migrating to the cloud.
- Big Data Professionals: Hadoop/Spark developers who want to learn the Azure ecosystem.
- SQL Developers: DBAs or developers interested in developing into Data Engineering.
- New Graduates: IT lovers who seek a career opportunity with high growth.
Azure Data Engineer Career Placement and Support
The completion of the Azure Data Engineer Training course in Pune will only be the start. Version IT believes in your career success. Our special placement office is relentlessly working to hook you with the best companies in terms of hiring.
- Resume Building: We assist you in developing a professional resume that puts into focus your new skills in the Azure and project experience.
- Mock Interviews: Take part in tough technical mock interviews so as to test your preparedness.
- Job Alerts: Receive a priority of watching jobs in Pune and in all of India.
- Soft Skills Training: Save your communication and presentation skills to break HR rounds.
Job Roles You Can Target:
- Azure Data Engineer
- Big Data Engineer
- Cloud Data Architect
- ETL Developer (Cloud)
- Data Warehouse Engineer
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
FAQ's
To make the best of this training, you need to have a general idea of SQL and basic background information about databases. Python is an added advantage and we teach the fundamental coding requirements in the sessions.
Live sessions are recorded and uploaded in our Learning Management system (LMS) within 24 hours. These recordings are available at your own convenience so that you can listen to those topics that you have missed or revised.
The training is 100 per cent practical, and you will be directly working on the edge of the Azure portal. Our three real-time industry projects that include Azure Data Factory, Databricks, and Synapse Analytics are to verify job preparation.
Yes, we provide special placement services, such as resume development, mock interviews, and job notifications. Our certified students are actively linked to the leading MNCs and startups in Pune seeking Azure professionals.
