Sql Server Training

SQL SERVER TRAINING: V CUBE SOFTWARE SOLUTIONS provides SQL Server Training in Hyderabad. We offer Real-time Database Design in hands-on experience in live Case Studies.

Sql server Training in Kukatpally Duration:25 days

SQL Server key highlights

 Sql Server Training in kukatpally 100+ hours of learning

Sql Server Training in kukatpally  Real-time industry professionals curate the course.

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Sql Server Training in Kukatpally 28+ Skills That Are Useful in the Workplace

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Description of the SQL Server Course

Why SQL Server is so popular:

SQL Server is a Microsoft product. It used to manage and store information. SQL Server is a “relational database management system”. Apart, this term means two things. First, that data stored inside SQL Server in a “relational database”. second, that SQL Server is an entire “management system”, not a database. SQL itself stands for Structured Query Language. The language used to manage and administer the database server.  

 A Power BI dataset from a relational database that exists on premises in your local network. Specifically, this tutorial uses a sample SQL Server database, which Power BI must access through an on-premises data gateway.

1. Create and publish a Power BI Desktop (.pbix) file that imports data from a SQL Server database on-premises.

2. Configure Power BI’s data source and dataset settings for SQL Server connectivity via a data gateway.

3. Set up a refresh schedule to ensure that your Power BI dataset is always up to date.

4. Perform an on-demand dataset refresh.

5. Examine the refresh history to see how previous refresh cycles fared.

6. Delete the artefacts created in this tutorial to free up resources.


Curriculum for the MSBI

What is Database?

What is Data Warehouse?

Difference between Database & Data Warehouse

Database Creation using GUI 

Database Creation using T-SQL Scripts

DB Design using Files • File locations and Size Parameters

DB Log Files, Growth and Placement 

DB Structure Modifications & Ownership

Table creation using T-SQL Scripts


Single Row and Multi-Row Insert Statements 

Table Aliases, Column Aliases & Usage

Table creation with Schemas

DELETE versus TRUNCATE Statements

 SELECT Queries and Sub Queries

 Schemas and Nested Queries with Aliases

Data Integrity and Normal Forms

 Tables with Keys & Constraints

NULL and IDENTITY Properties – Usage

 UNIQUE KEY Constraint and NOT NULL

 PRIMARY KEY Constraint & Importance


CHECK and DEFAULT Constraints, Usage



Sub Queries, Nested Queries and EXISTS 



Inner Joins – Purpose and Performance

 Outer Joins – Types, Advantages and Usage

Cross Joins – Advantages and Limitations 

Self Joins and Sub Queries

Benefits of Views – End User Access 

Defining Views on Tables and Views 

SCHEMABINDING and Encryption Options

ALTER TABLE Issues and Solutions with Views

System Views & Management Views: Audits 

Joins and Nested Sub Queries in Views

Functions – Syntax, Usage, and Importance

 Scalar-Valued Functions and Examples 

Table Valued Functions and Examples 

System Functions and Joins – CROSS APPLY

 Date, Time and Conversion Functions 

String Functions and Meta-data Functions


Joining Functions and Tables / Views

Need for Indexes, Index Types & Usage 

Indexing Table & View Columns


PRIMARY KEYS and Non-Clustered Indexes

Need for Stored Procedures & Syntax

 Use of Variables and Query Parameters 

Stored Procedures with Loops &IF… ELSE



System Stored Procedures and Nesting 

Dynamic SQL Queries and Parameters 

Stored Procedures, Data Validation Options

OUTPUT Parameters and Result set Options

Triggers – Architecture, Types & Usage 

DML Triggers and Performance Impact

INSERTED and DELETED Memory Tables 

Triggers for Audit Operations (Memory)

Cursor Declaration and Fetch Options

 STATIC and DYNAMIC Cursor Types 


LOCAL and GLOBAL Cursors – Scope

KEYSET Cursors and Temp Objects

Embedding Cursors in SPs and Functions 

Temp Tables and Procedures with Cursors

Common Table Expressions (CTE) and Queries 

Stored Procedures with CTE: Tuning Options

Transaction Options and Stored Procedures

 ACID Properties in T-SQL and Scope 

EXPLICIT Transaction Types and Issues 

IMPLICIT Transactions Types and Issues 

AUTOCOMMIT Transaction and Advantages 

Nested Points and Save Points usage 

Query Blocking Issues and Query Hints

SPs with Transactions & Temp Objects



 1).Database Developer: Database developers ensure that DBMS’s are capable of handling massive amounts of data. Most database developers work with software development teams. This career requires extensive knowledge of SQL. Three distinct areas are common to the job of database developer:

  • Modifying and editing databases
  • New databases design and development
  • Investigating database issues

The average salary for a Database Developer is $98,415 annually. Become Database Developer with Sql Server Training in KPHB

2)Software Developer :A software designer is responsible for both the design and development phases in software creation. He will plan out all the necessary parts of the automated tasks. To help illustrate the process, he plans documentation and flowcharts.


The average annual salary for a Software Developer is $102,528.

3)Software Consultant: Below are some of the Database solutions that Software Consultants can create:

Database Development Services

Database Administration and Maintenance Services

Troubleshooting MS SQL Database

Database-optimization and performance scalability

Database design using Data modeling tool like xCase

MS SQL Report Services – Custom Reports

SSIS SQL Server Integration Services

The annual average salary for a Software Consultant is $118,000.


Data is rapidly becoming one of the most important parts of technological advancement..NET is no exception. .NET developers should be familiar with Microsoft’s own SQL databases and rising innovation, such as NoSQL.


The average annual salary for a .Net developer is $107 250


What is the Future of SQL SERVER

SQL will be around until the end of time. Relational databases systems are still important, even with Big Data Systems’ rise. RDBMS companies are also introducing Big Data-flavored features such as scaling, distributed processing, and data warehousing in order to manage large amounts of structured data using the existing implementations. SQL is a good place to begin and has great potential. However, you should improve your skills and expand your scope to meet different needs. These are some things you need to keep in mind.

  1. Start with a platform. SQL is an ANSI-standard database scripting language. However, it has been modified by large technology companies like Microsoft, Oracle and IBM. Learn SQL on a platform you have purchased. If it’s Microsoft, install SQL Server to explore T-SQL. While general statements are universal across all platforms, you will find that there are changes in query, datatypes and execution levels as you dig deeper.
  2. Explore the database engine to learn more about this product. You will be able to write better queries if you know how the queries are evaluated within the server.
  3. Learn how to manage databases.
  4. Knowledge of data integration and reporting would be an advantage. If it’s SQL Server, then you can try SSIS (SQL Server Integration Services), and SSRS(SQL Server Reporting Services).
  5. HIVE is a last resort if you want to dive into Big Data. It’s similar to SQL

SQL is appearing in more and more places. The SQLite data is integrated into many modern web browsers like Google Chrome, Opera and Safari. It also integrates into many mobile operating systems, including Blackberry OS and Google Android.

On the other hand, the rapid growth in data and metadata means that optimization of Big Data SQL, such as SQL for Hadoop and cloud computing is not keeping up with it. The rapid intake of data and the demand for real time analysis a competitive advantage.

Even NoSQL databases (competitors to SQL) started to support SQL. Google taught its Spanner2.0 global-scale database SQL instead of a NoSQL implementation from Version 1.0. They see that SQL is so common that they don’t need to reinvent the wheel when they create their own query language. Google created “Standard SQL to be used across many Google apps like BigQuery, Adwords and so forth.

Data is being moved to the cloud more frequently, so it is possible to replicate it for fault tolerance and make it easier to query it. Apache Cassandra standards and freely-available tools such as Apache Hive mean that everyone can afford cloud-based data.

On the other hand, you can find SQL databases everywhere you look in web browsers or on mobile phones. You can also download the My SQL , Work Bench, My SQL community edition, and SQLite free of charge to create your apps and then deploy them to Heroku.

SQL is the “glue” that binds all data and tools together. It will continue to do so for many years.Now is the Best Time to Get SQL Server training in kukatpally and Upgrade your skills 

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