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Azure Synapse Analytics Training in Hyderabad

Synapse offers a single service for all tasks such as management, data processing, and serving. This is accomplished through the combination of Power BI and Azure Machine Learning. 

14 Modules

with Certifications


After Completion



Azure can allow you to manage query data on your own terms. When your users are online or not, you can choose between high supplied resources and low demand. Azure SQL Data Warehouse has been rebranded as Azure Synapse Analytics. Azure SQL Data Warehouse was an MPP (Massively parallel processing) solution meant to store massive amounts of data in Microsoft Azure Data Warehouse.
However, Microsoft has added several unique features that give them a competitive advantage over other participants in the market. Microsoft Azure is used as a data warehouse by nearly 80% of Fortune 500 companies. Microsoft has another significant advantage in that it is present everywhere. Users are aware of their interface and other apps, such as Microsoft Excel, Microsoft PowerPoint, Microsoft Access, and MSBI (Microsoft Business Intelligence), which are also utilized on an organizational level.

  • Extend insights into all of your data and machine learning modules of your websites and applications with powerful insights.
  • Instant clarity — With the most recent data available on Microsoft Azure Synapse Architecture, you can instantly clear all of your business-related doubts.
  • Unrivaled security—With row-level security and dynamic data masking, you can protect your data.
  • Unified Experience — End-to-end solutions minimize project development time.
  • Limitless Scale – Deliver your data to your upper staff as quickly as possible.
  • Cost-effective – the cloud’s most cost-effective and data management.

From Version IT’Azure Synapse Analytics in Hyderabad, you will learn how Azure Synapse Analytics, enables you to execute various types of analytics through its components, which can be utilized to develop modern data warehouses through advanced analytical solutions. You will learn how Azure Synapse Analytics addresses the issue of having a single service to meet the broad range of analytics requirements that organizations face today, as well as a tour of the core application used to communicate with the many Azure Synapse Analytics components. You will learn about the numerous Azure Synapse Analytics components that allow you to develop your analytical solutions all in one place.

Who can Enroll?

Version IT provides Azure Synapse Analytics training to aspirants of all ability levels. There is no specific background required.

Advantages of Azure Synapse Analytics Training

  • You can create, manage, and deploy an Azure Synapse Analytics Data Warehouse.
  • Using the Transact-SQL COPY statement, load data into Synapse SQL Pools.
  • In Synapse SQL Pools, you can run queries and analyze enormous volumes of data.
  • Install an instance of Azure Synapse Analytics Workspaces.
  • Use Azure Synapse Studio to load and analyse data.
  • Using Synapse Studio, visualise query results.
  • Manage and pause computing to improve performance while reducing cost.
Career Opportunities with Azure Synapse Analytics

Azure Synapse Analytics is a developing service that was introduced in previous years to improve SQL Data Warehousing. If your company requires Azure Synapse Analytics, you should choose Microsoft Azure over alternative services such as Amazon AWS and Google Cloud because it is used by all major companies. However, you must determine what is best for your company.
If you want to make it big in the data arena and flourish as a future leader, consider our Azure Synapse Analytics institutes in Hyderabad for Azure Synapse Analytics training.


Topics You will Learn

  • Technical requirements
    Interdiction of the components of the Azure Synapse Creating a Synapse Workspace
  • Understanding Azure Data Lake: Exploring Synapse Studio

Technical requirements: Introducing SQL Pool

  • Creating a SQL Pool
  • Synapse SQL Pool
    Architecture and components
  • Examining DWUs
  • Understanding distribution in Synapse SQL Pool
  • Understanding portions in Synapse
  • SQL Pool
    Using a temporary table in Synapse SQL Pool
  • Discovering the Benefits of Synapse SQL Pool

Understanding Synapse SQL on demand

  • SQL on-demand architecture and components
  • Learning about the benefits of Synapse SQL on-demand
  • Technical requirements
  • Using Synapse pipelines to import data
  • Bringing data to your Synapse SQL Pool using the Copy Data tool
  • Using Azure Data Factory to import data
  • Using SQL Server Integration Services to Import Data
  • Technical requirements
  • Introducing Synapse pipe lines
  • Integration runtime
  • Activities
  • Pipelines

Creating linked services
Defining source and target
Using various activities in synapse pipelines
Scheduling synapse pipelines
Creating pipelines using samples

  • Technical requirements
    Enabling the analytical store in Cosmos DB
    Data storage
  • Transactional store
  • Analytical store

Querying the Cosmos DB analytical store

  • Querying with Azure Synapse Spark
  • Querying with Azure Synapse SQL Serverless
  • Technical requirements
  • Supporting T-SQL language elements in a Synapse SQL pool
  • CTEs
  • SELECT-OVER clause
  • Using dynamic SQL in Synapse SQL
    Learning group by options in Synapse SQL
  • Using T-SQL loops in Synapse SQL

Stored procedures

  • Views

Optimising transactions in Synapse SQL
Supporting system views in a Synapse SQL Pool
Using T-SQL queries on semi-structured and unstructured data

  • Reading parquet files
  • Reading JSON documents
  • External tables
  • Technical requirements
  • Implementing best practices for a Synapse-dedicated SQL pool
  • Maintaining statics
  • Using the correct distribution for your tables
  • Using partitioning
  • Using an adequate column size
  • Advantages of using a minimum transaction size
  • Using PolyBase to load data
  • Reorganisation and rebuilding indexes
  • Materialisation views
  • Using an appropriate resource class
  • Implementing best practices for a Synapse serverless SQL pool
  • Selecting the region to create a serverless SQL pool
  • File for querying
  • Using CETAS to enhance query performance
  • Implementing best practices for a Synapse Spark pool
  • Configuring the auto-pause setting
  • Enhance Apache Spark performance
  • Implementing network security
  • Managed workspace virtual network
  • Private endpoint for SQL on-demand
  • IP firewall rules
  • SQL authorization
  • Azure Active Directory authorization
  • Implementing RBAC in a Synapse SQL Pool
  • Enabling threat protection
  • Azure SQL auditing
  • Azure Defender for SQL
  • Understanding information protection
  • Technical requirements
  • Using Azure Open Datasets
  • Using Sample Scripts
  • Pyspark (Python)
  • Spark (Scala)
  • Technical requirements
    Connecting to a
  • Power BI Workspace
    Creating your own dashboard on Azure Synapse
  • Creating new Power BI datasets
    Creating Power BI reports

Connecting Azure Synapse Data to Power BI Desktop
Connecting to a Synapse-dedicated SQL Pool
Connecting to a Synapse Serverless SQL Pool

  • Technical requirements
  • Understanding various architectures and components
  • Bringing data to Azure Synapse
  • Using Azure stream analytics
  • Using Azure Databricks

Implementation of real-time analytics on streaming data
Ingest data into Cosmos DB
Accessing data from the Azure Cosmos DB analytics store in Azure Synapse
Loading data to a Spark Data Frame
Creating Visualisations

  • Technical requirements
  • Preparing the environment
  • Creating a text analytics resource in the Azure portal
  • Creating an Anomaly Detector resource in the Azure portal
  • Creating an Azure key vault
  • Creating an Azure ML-linked service in Azure Synapse
  • Machine learning capabilities in Azure Synapse
  • Data ingestion and orchestration
  • Data preparation and exploration
  • Training machine learning models
  • Use cases with cognitive services
  • Sentiment analytics
  • Anomaly detection
  • Technical requirements
  • Creating restore points
  • Automatic restoration points
  • User-defined restore points
  • Geo-backup and disaster recovery
  • Geo-redundant restore through the Azure portal
  • Geo-redundant restoration through PowerShell
  • Cross-subscription restore 
  • Technical requirements
  • Managing Synapse resources
  • Analytical Pools
  • External Connections
  • Integration
  • Security
  • Source control
  • Monitoring Synapse workloads
  • Integration
  • Activities
  • Analytics Pools
  • Managing maintenance schedules
  • Creating alerts for Azure Synapse Analytics

Let Your Certificates Speak


All You Need to Start this Course


Still Having Doubts?

Azure Synapse Analytics is a Microsoft Azure cloud-based integrated analytics service. It allows users to examine massive amounts of data while utilizing both on-demand and supplied resources.

Synapse Analytics is an upgrade of Azure SQL Data Warehouse that combines big data and data warehousing into a single platform. It supports data integration, data warehousing, and big data analytics.

On-demand analytics, data integration, and transformation, security and compliance features, serverless SQL pools, and both provisioned and serverless resources are among the key features.
A data warehouse is a centralized storage and analysis facility for massive amounts of data. Azure Synapse Analytics processes and analyzes data across several nodes using a distributed architecture, which provides scalability and performance.

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