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📅 Course Duration
2 1/2 Months
💰 Course Price
₹ 25000
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📄 Course Content
Azure Data Engineering Course in Noida
Interested in pursuing a career in cloud data engineering, taking Azure data engineer training in Noida will open up the opportunities in the technological field. Version IT provides industry-oriented training and integrates both the theoretical concepts and practical implementation.
Understanding the Azure Data Engineering Course in Noida
The Azure data engineering course in Noida gives an in-depth overview of the data ecosystem of Azure and its use in the contemporary enterprise setting. The training is aimed at educating the learners to develop and operate credible information pipelines that facilitate business intelligence and sophisticated analytics.
Throughout the course, students are taught the skills of consuming data of various sources, processing large amounts of data quickly, and storing it safely in the Azure infrastructure. The course is practical in nature, allowing the students to acquire the technical skills required to tackle the data problems in the real world.
The curriculum contains practical work with significant Azure services utilized in data engineering processes. These services facilitate the management of data within organizations and allow teams to make useful conclusions with the help of complex sets of data.
The participants receive experience in dealing with cloud storage solutions, ETL pipelines, data transformation processes, and performance optimization methods. This sequential learning model will make sure that the students will enhance their conceptual as well as practical problem solving abilities.
Why Choose Version IT for Azure Data Engineering Training in Noida
The correct training program is a key opportunity in the development of an effective career in cloud data engineering. The Version IT Azure data engineering training in Noida is unique in that it incorporates the industry relevant curriculum in association with the practical mode of training.
Curriculum that is Industry-driven.
The Version IT provides a properly organized curriculum to match the demands of the industry. The training presents fundamental principles of Azure data services and current data engineering practice as well as practical implementation strategies. This will make sure that the students acquire viable knowledge that is in line with what the companies require of level-sensible Azure Data Engineers.
Practical Training in Live Projects.
At Version IT, learners have the task of working on real time projects and case studies which provide them with hands-on experience. This practical methodology assists the students to appreciate how the Azure data pipelines, data warehouses and cloud storage systems work in actual business settings which makes them workforce-ready at the close of the training.
Skilled Industry Trainers.
The training program will be conducted by the experts, who already have a great amount of experience in the working with Azure cloud technologies. Their experience in the industry can assist students to acquire practical problem solving methods, best practices and advanced concepts applied in the current data engineering projects.
Flexible Learning Options
Version IT offers learners the opportunity to have different training schedules. Students will have options of classroom training, weekend training and online training programmes. This is flexible so that not only fresh graduates but also those who are in employment can study the Azure data engineering without interfering with their current engagements.
Career Guidance and Placement Support.
Version IT offers career guidance and job preparation support to the learners even after the training. Resume construction, interview training, and certification are provided to students, and it makes them more likely to get jobs following the completion of the training of Azure Data Engineering.
Microsoft Azure Data Engineering Training in Noida: What You Will Learn
The Microsoft azure data training in Noida is a very extensive training program in terms of the concepts needed to construct a modern cloud-based data architecture. The course is meant to make the learners acquire the technical knowledge required to administer data systems within the enterprise settings.
The students would start with the basics of the Azure and cloud computing and advance to more specific data engineering tools. The training is aimed at acquiring the skills that can assist the professionals to create the efficient data pipeline design and introduce the scalable data processing structures.
During the program, participants learn in such aspects as:
- Developing data ingestion pipeline.
- Controlling organized and unstructured data.
- Design of cloud-based data warehouses.
- The application of data transformation operations.
- Observation and optimization of Azure data processes.
The training also brings out the best practices in ensuring data security, compliance and performance in the Azure environments. These competencies are necessary in organizations whose operations are critical to relying on the cloud-based data infrastructure.
Through the course, the learners should be able to know how to design and execute modern data solutions in the power of data service provided by Azure.
Flexible Azure Data Engineering Online Training in Noida
To most professionals, it is difficult to strike a balance between work and developing their skills. To cope with this requirement, Version IT has provided Azure data engineering online training in Noida, which enables a learner to acquire skills that can be valuable in the course without interfering with their career obligation.
The online training program offers the same extensive training program as the classroom training but it is more flexible. Students will have the opportunity to participate in instructor-based classes remotely, get learning material online, and submit practical work anywhere.
This is an ideal model of flexible learning especially to working professionals who would wish to update their competencies as they remain in the same line of duty. Interactive discussions, real time demonstrations and collaborative learning are also facilitated by the program.
The students attending the online training will be provided with access to the recordings of the training sessions, exercises on the subject, and projects to complete, which will help them to improve their knowledge of the Azure data engineering principles.
Online training, which is structured, enables the learner to acquire the required in-demand skills in cloud data, without the need to interrupt the convenient and flexible learning schedule.
Career Opportunities After Azure Data Engineering Training
The training of Azure data engineer in Noida is capable of providing a vast career in the thriving cloud technology industry. The demand of professionals to manage and optimize their data infrastructure has only been on the rise as companies move their data infrastructure to the cloud.
Azure Data Engineers will be significant in creating data pipelines, as well as integration of data sources and have data to use in analytics and decision-making processes.
Upon training, the learners will get a chance to pursue such roles as:
- Azure Data Engineer
- Cloud Data Engineer
- Big Data Engineer
- Data Platform Engineer
- ETL Developer
- Data Solutions Engineer
These functions include the designing of data processes, taking care of data storage systems, and assisting business intelligence projects in organizations.
As cloud data professionals are in high demand, the trainees who complete Azure data engineering course in Noida have opportunities to work in a successful career at both domestic and global market.
Azure Data Engineering Certification
The Azure Data Engineering course in Noida at Version IT assists students to prepare to take the widely recognized Microsoft Azure Data engineer associate certification. This certification confirms that you are competent to design, construct and administer data solutions utilizing Azure solutions. The training will incorporate exam oriented instructions, hands-on laboratories and simulated real world situations to consolidate your knowledge on Azure data tools and technologies.
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
