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Azure Data Engineer Training in UK
Learn Microsoft Azure data engineering training in UK at Version IT & understand how organizations design and manage modern cloud-based data systems.
Overview of Azure Data Engineer Training in UK
The emerging technologies of cloud computing and big data have led to tremendous consumption of data professionals in the United Kingdom. Cloud-based solutions have become very important in storing, processing, and analyzing data in large quantities in organizations today. One of the most popular cloud ecosystems that are used in contemporary data engineering solutions has been implemented in Microsoft Azure.
Due to this change, firms are currently seeking those professionals with good skills in Azure data engineering who will be able to structure and administer scalable data solutions. Another futile is taking an Azure data engineer course in UK as a means of developing the skill set to compete in an expanding industry.
The Version IT Azure data engineering training in UK is aimed at enabling students to gain technical skills and hands-on applications that enable them to work with the contemporary Azure data engines. This training is a good starting point to a successful career in cloud data engineering whether the individual is a beginner that needs to venture into the cloud domain or an IT professional that needs to upgrade his or her skills.
Growing Demand for Azure Data Engineers in the UK
The UK technology industry is growing at a very high rate, and corporations are allocating a lot of money to cloud-based data storage. Banks and health institutions as well as retail and technology companies have to use Azure data engineering solutions to process and analyze large amounts of data effectively.
This increased need has presented immense employment opportunities to individuals who have the skills in the field of Azure data engineering. Attending in Azure data engineering training in UK allows the learners to acquire the knowledge needed to create scalable data pipelines, combine various data sources, and serve advanced analytics systems.
Azure Data Engineers are important in assisting organizations in turning raw data into valuable insights. They build robust data systems, streamline cloud-based data systems, and have data made available as business intelligence and reporting data.
By compeleting Azure data engineering course in UK, will help one acquire these essential skills and emerge as an effective resource in the contemporary data-driven company.
Why Choose Version IT for Azure Data Engineer Training in UK
Version IT is also known to provide quality technical training programs based on real practical learning and career preparation. Our training of an Azure data engineer in UK will enable the learners to acquire real-life competencies as well as practical application of modern Azure data engineering technologies.
Industry-Experienced Trainers
We offer training that is facilitated by seasoned professionals trained in cloud technologies (Azure) and solutions based on data engineering at enterprise levels.
Practical Hands-On Learning
The training is more practical-based and in which learners are provided with real-life experience in dealing with the Azure cloud environments and real world data engineering applications.
Job-Oriented Training Approach.
Our data engineering training in the UK is developed with a high emphasis on industry and real job skills.
Real-Time Project Exposure
Learners are also exposed to real-life practices by giving them practical examples and hands-on activities that guide the students in learning how the Azure data solutions are applied in organizations.
Professional Learning Environment.
We are an organized learning platform, which offers mentorship, technical assistance, and direction to the students to establish successful careers in Azure data engineering.
Flexible Azure Engineering Online Training in UK
The flexibility is often necessary in the process of learning new technical skills, particularly among the working professionals and students who have other obligations, which must be weighed against education. Version IT provides online training in Azure Engineering Online Training in UK and it is easy to acquire the skills of cloud data engineering at any place.
The online trainings will aim at creating an interactive and engaging learning experience as the classroom-based trainings. Learners are able to attend real time instructor led sessions, ask questions, and interact with other students whilst studying in the comfort of their homes.
Our Azure Engineering Online Training in UK is specifically useful to those professionals who would wish to keep up to date with their job routines without disturbing them. Through organised training and the provision of available learning materials, students will be able to master their knowledge in Azure data engineering.
Career Opportunities After Azure Data Engineering Training
The employment opportunities in the field of cloud computing and data engineering are vast after completing the training of Azure data engineering in the UK.
The companies in the UK are continuously seeking specialists capable of operating cloud data environments of substantial scale and constructing effective data pipelines. Azure Data Engineers are also associated with facilitating business to derive insights of their data and help in making strategic decisions.
Upon successfully completing Microsoft Azure data engineering course in UK, students have the capability to secure jobs as Azure Data Engineer, Cloud Data Engineer, Data Platform Engineer and Azure Solutions Specialist.
As cloud technologies are being adopted more and more, these roles will continue to be sought after in the years to come.
Taking an Azure engineering course in the UK, the professionals can acquire knowledge and technical skills to compete within the rapidly expanding job market of cloud technology.
Career Support and Guidance from Version IT
Version IT is also keen on helping the learners in building successful careers in cloud technologies as well as technical training.
The training in UK program of the Azure data engineer is accompanied with mentorship of the students, who will be informed about the expectations of the industry and employment prospects of the program in terms of the UK.
Students are provided with the visualization of the practical usage of cloud technologies in real companies and the role of Azure data engineers in the contemporary data-oriented business settings.
We provides knowledgeable mentorship and learning focused on the industry and therefore enables the learners to enter the cloud data engineering profession 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
Students are taught about the Azure computing platforms, cloud information architecture, data integration, and scalable data processing methods in contemporary firms.
