Azure Data engineer with DevOps

Azure Data Engineer

Azure Data Engineer Training In Hyderabad-Become career ready experts in azure data engineer training online hyderabad domain with the aid of V Cube Software Solutions, Azure Data Engineer Training in Kukatpally In Hyderabad by experts

Duration: 45days


 100+ hours of learning

 Real-time industry professionals curate the course.

Internships and live projects

Dedicated staff of placement experts

Placement is guaranteed 100 percent Assistance

28+ Skills That Are Useful in the Workplace

Trainers with a minimum of 12 years of experience

Videos and back-up classes

Subject Matter Experts Deliver Guest Lectures

contact us


Why Azure Data engineer is so popular?

Azure data engineers are in charge of data-related implementation tasks such as providing data storage services, ingesting streaming and batch data, transforming data, implementing security requirements, implementing data retention policies, identifying performance bottlenecks, and gaining access to external data.” Sky blue information engineers investigate and research explicit information questions presented by partners, and they construct and keep up with secure and agreeable handling pipelines by utilizing various devices and strategies. These experts utilize different Azure information administrations and dialects to store and create purged and improved datasets for examination.

Curriculum for the Azure Data Engineer

Microsoft Azure is a hardware and software-as-a-service cloud computing platform. The service provider creates a managed service here to give users on-demand access to these services.

Azure SQL Database, Azure SQL Managed Instance, and Azure Synapse Analytics are all supported.
It can be applied to all SQL Databases under an Azure subscription as a security policy.
Users can adjust the level of masking to suit their needs.
Only the query results for certain column values on which data masking has been performed are masked. It has no effect on the database’s real stored data.

From Azure SQL Database or Azure Synapse Analytics, query data stored in Hadoop, Azure Blob Storage, or Azure Data Lake Store. It eliminates the need for data to be imported from a third-party source.
Use a few easy T-SQL queries to import data from Hadoop, Azure Blob Storage, or Azure Data Lake Store without having to install a third-party ETL tool.
Export data to Hadoop, Azure Blob Storage, or Azure Data Lake Store with Azure Data Lake Store. It allows data to be exported and archived to external data repositories.

Microsoft offers the option of reserving storage capacity on Azure to reduce Azure Storage charges. The reserved storage on Azure cloud provides users with a fixed amount of capacity for the reservation time. It may be used to store Gen 2 data in a normal storage account for Block Blobs and Azure Data Lake.

It’s built to handle tables with hundreds of millions of rows of data. Because Synapse SQL runs on a Massively Parallel Processing (MPP) architecture that distributes data processing across numerous nodes, Azure Synapse Analytics performs complicated queries and returns query results in seconds, even with large data.
The Synapse Analytics MPP engine is accessed through a control node, which acts as a point of entry for applications. The control node cuts down the Synapse SQL query into MPP optimised format when it receives it. Individual operations are also routed to compute nodes that can complete the processes in parallel, resulting in significantly improved query performance.

Dedicated SQL Pool is a set of tools that allows you to use Azure Synapse Analytics to construct a more typical Enterprise Data Warehousing platform. Data Warehousing Units (DWU) are used to measure the resources, which are provisioned using Synapse SQL. A dedicated SQL pool stores data using columnar storage and relational tables, which improves query performance and reduces storage requirements.

Azure has a dedicated analytics service called Azure Stream Analytics, which includes the Stream Analytics Query Language, a basic SQL-based language. It enables developers to extend the query language’s capabilities by introducing new ML (Machine Learning) functions. Azure Stream Analytics can process a massive quantity of data at over a million events per second and provide the results with extremely low latency.

It’s a versatile standalone tool that lets you manage Azure Storage from any platform, and it’s available for Windows, Mac OS, and Linux. Microsoft Azure Storage is available for download.
It gives easy access to many Azure data stores, including ADLS Gen2, Cosmos DB, Blobs, Queues, Tables, and more.
One of the most important aspects of Azure Storage Explorer is that it allows users to operate even if they are not connected to the Azure cloud service by using local emulators.

Join with us to start your career

Open chat
Need Help?
Can we Help you?