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Azure Data Engineering Training in Delhi
Register for Azure Data Engineering Training in Delhi with Version IT and master Azure Data Engineering. You will acquire the skills required in the industry such as the data warehousing, big data analytics, and pipeline management.
Azure Data Engineering Course Overview
Azure Data engineering course in Delhi is designed in a way to impart a comprehensive understanding of the data ecosystem of Microsoft Azure. It includes the necessary knowledge to design data pipelines, work with huge quantities of data, and apply data integration solutions with Azure tools.
In the Microsoft Azure data engineer training in Delhi, the students are going to receive information on how to create scalable data architectures, which can be used to support analytics, reporting, and machine learning applications. The course starts with the basics of cloud computing and progressively advances to more advanced methods of Azure data engineering.
The major issues that were addressed in the training are:
- Background of cloud computing and Microsoft Azure platform.
- Knowledge Azure data storage solutions.
- Laboring with Azure Data Lake Storage.
- Azure Data Factory data integration.
- Azure synapse analytics in the form of data warehousing.
- Methods of processing and transformation of data.
- Adopting data protection and management.
- Real-time information processing and monitoring.
The training will be very practical in nature whereby students will be working on live situations and projects which are supposed to emulate real world business problems. By undertaking practical activities, students acquire the capabilities of developing a trustworthy and scalable data solutions in the cloud.
At the conclusion of the Microsoft Azure data engineer course in Delhi, the participants would know how to handle end-to-end data processes, including data ingestion, transformation, and visualization.
Key Features of Azure Data Engineering Training in Delhi at Version IT
Learning Azure engineering course in Delhi online at Version offers:
Flexible Classes
The platform, when combined with the Ease of Learning, provides the contemporary students with the opportunity to refine and personalize their education in the most painless way possible.
Learn from Expert Trainers
Gain experience through culture-changing trainers who also bring a variety of workplace experience. Get experience skills and strategies that will guarantee success in your profession.
Infinite Practical Training
Train without restriction under the guidance of above mentioned culture changing trainers by improving on your skills through the practical approach in a continuous fashion.
Internship Opportunity
Enter into your career with a relevant industry experience via our internship program. One will have projects to work on and one will be mentored individually to meet different challenges.
Interview & Career Guidance
You can reach great heights in life and your career with his interview tips and proper training with established career goals and that too under his personal guidance.
Unlimited Employment Opportunities
Launch your career with a plethora of employment opportunities where an individual can get myriads of employment and create a successful career indefinitely.
Who Should Take Azure Data Engineering Course?
The Azure Engineering course in Delhi is the best course to be taken by a person who desires to develop or develop their careers in data engineering and cloud data management.
This course is suitable for:
- IT Professionals: This training can be extremely useful to software engineers, system administrators and database developers who are planning to shift to positions in cloud-based data engineering.
- Data Analysts and Data Scientists: This course will be of great interest to professionals that are already handling data but are interested in improving their abilities by studying scalable cloud-based solutions to process data.
- Database Administrators: DBAs who intend to migrate and administer enterprise data solutions on cloud providers such as Azure will be able to acquire relevant experience via this program.
- Fresh Graduates and Career Switcher: Those who desire to join the fast-progressing data engineering field can begin its career with Azure data engineering competencies.
- Cloud Professionals: The current practitioners in the field of cloud platform usage who wish to also become experts in the area of Azure data solutions will be able to advance their knowledge with the help of this training.
As businesses embrace data-driven approaches, Azure Data Engineers have become important in the management of enterprise data systems. This course equips the learners with these demanding positions through practical skills that are job ready.
Certification Path for Azure Data Engineering in Delhi
The professional certification is also significant in certifying your skills in cloud data engineering. Azure Engineering online course in Delhi makes students ready about the world renowned Microsoft certifications.
The most favored certification route is the Microsoft Azure Data engineer associate certification that establishes your skills of designing and deploying data solutions based on azure services.
The certification training is oriented to such basic competencies as:
- Procuring and developing data storage solutions.
- Creation of data processing solutions.
- Adopting data security and compliance.
- Data Systems monitoring and optimization.
The trainers take the students through the structure of the certification exam, key concepts and practice questions during the course. This will provide the learners with the practical knowledge and exam preparation.
An Azure Data engineering certification can assist professionals in:
- Authenticate their technical knowledge.
- Enhance employment in cloud data positions.
- Increase earning potential
- Attain international visibility in the IT market.
As the adoption of Azure by enterprises grows at a rapid pace, there is increased demand of certified Azure Data Engineers by organizations worldwide.
Azure Data Engineering Training with Job Support Program
The job support program availed to learners is among the greatest benefits of attending Azure Data Engineering Training in Delhi at Version IT. The training is not just about offering technical knowledge but also to ensure that the students are able to launch or advance their careers successfully.
The job support program will entail:
Hands-on Project Training:
Students complete real-time projects in the industry that emulates enterprise-level data engineering.
Interview Preparation:
The program will also entail the mock interviews, resume construction support, and tips on responding to technical interview queries pertaining to Azure data engineering.
Practical Use Cases:
Students get exposed to a practical environment like pipeline construction of ETL, data lake management, and data optimization.
Expert Mentorship:
The course offers mentorship by the industry professionals to enable the learners to learn complex concepts and the best practices in the industry.
Career Guidance:
Participants are counselled to make the optimal career path selection in the Azure data engineering ecosystem such as Data Engineer, Cloud Data Engineer and Data Platform Engineer.
This program provides a practical training that is complemented with career assistance to help the learners be well equipped to face the competitive job market with confidence.
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
The skills that you will acquire include data pipeline design and management, ETL processes, Azure Data Factory, data lake management, data transformation, and scalable data construction on the Azure cloud platform.
The average duration of most of the Azure Data Engineering training programs range between 6 and 10 weeks, depending on the type and programme of training.
Azure Data Engineering is unique in the sense that it is compatible with the Microsoft ecosystem and has strong capabilities including Azure Data Factory, Azure Synapse analytics, and Azure Data Lake storage.
The fees of the training on Azure Data Engineering may differ based on the institute, the course timeframe, and the type of training.
Upon successful completion of the training of Azure Data Engineering, one can take up a number of positions including but not limited to:
- Azure Data Engineer
- Cloud Data Engineer
- Data Platform Engineer
- Big Data Engineer
- ETL Developer
- Data Solutions Architect
