Apply Advanced SQL Server Analytics and Programming

This course is part of Apply SQL Server Database Management & Analytics Specialization

Instructor: EDUCBA

Access provided by Jawaharlal Nehru University

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Store, query, and modify JSON and semi-structured data within SQL Server.
Design and query graph databases to model and analyze complex relationships.
Integrate R and Python in SQL Server for advanced analytics and data processing.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

15 assignments

Taught in English

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This course is part of the Apply SQL Server Database Management & Analytics Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

By the end of this course, learners will be able to manage semi-structured data using JSON, model complex relationships with graph databases, and apply advanced analytics by integrating R and Python within SQL Server. Learners will gain the ability to query, modify, and analyze diverse data formats directly inside the database environment.

This course is designed for database professionals and data practitioners who want to move beyond traditional relational querying and leverage advanced SQL Server capabilities. Through hands-on concepts, learners will understand how to store and manipulate JSON data, build and query graph databases for relationship-driven use cases, and execute R and Python scripts for analytics, data ingestion, and transformation. The course emphasizes practical application, enabling learners to process structured and unstructured data efficiently without moving data outside SQL Server. What makes this course unique is its unified approach to modern data handling within SQL Server—combining JSON, graph databases, R, and Python in a single advanced curriculum. By completing this course, learners will enhance their analytical skill set, improve data-driven decision-making, and be better prepared to handle real-world enterprise data challenges using SQL Server’s advanced features.

This module focuses on managing and querying JSON data within SQL Server. Learners explore how JSON supports semi-structured data storage, how to insert and query JSON using built-in SQL Server functions, and how to modify JSON content efficiently. The module emphasizes practical techniques for working with hierarchical data while maintaining data integrity and flexibility in enterprise database environments.

What's included

8 videos4 assignments

8 videos Total 83 minutes

Introduction to JSON 12 minutes
Inserting Data in JSON table 11 minutes
JSON Using Variables 6 minutes
Select Queries in JSON 11 minutes
Working on JSON Type 10 minutes
Inserting Data of Type JSON 13 minutes
More on Select Queries on JSON 10 minutes
Altering JSON Data 10 minutes

4 assignments Total 60 minutes

JSON Data Management in SQL Server 30 minutes
JSON Data Management in SQL Server 10 minutes
Querying JSON Data 10 minutes
Advanced JSON Queries and Updates 10 minutes

This module introduces graph database concepts and their implementation in SQL Server. Learners examine how nodes and edges represent entities and relationships, how graph tables are created and modified, and how real-world relationship models are implemented using SQL Server graph features. The module highlights relationship-centric querying for complex data scenarios.

What's included

8 videos4 assignments

8 videos Total 80 minutes

Introduction to Graph Databases 10 minutes
Creating Node Table 11 minutes
Creating Edge Table 10 minutes
Altering Edge Table 10 minutes
Example on Creating Graph Database Part 1 12 minutes
Example on Creating Graph Database Part 2 13 minutes
Example on Creating Graph Database Part 3 8 minutes
Example on Creating Graph Database Part 4 8 minutes

4 assignments Total 60 minutes

Graph Databases with SQL Server 30 minutes
Graph Database Basics 10 minutes
Modifying Graph Structures 10 minutes
Graph Database End-to-End Examples 10 minutes

This module covers the integration of R with SQL Server to enable advanced analytics directly within the database environment. Learners explore executing R scripts, importing external data sources, processing non-tabular data, and performing analytical joins. The module emphasizes data preprocessing, analysis, and result integration using R.

What's included

8 videos4 assignments

8 videos Total 73 minutes

Introduction to R Using SQL 8 minutes
Executing R Scripts in SQL Server 10 minutes
Executing R scripts for Importing CSV File 9 minutes
Working on R Command 10 minutes
Reading PDF File 10 minutes
Displaying Data in SQL Query 8 minutes
Writing Commands on R Command Prompt 9 minutes
Working on Joins using R Script 9 minutes

4 assignments Total 60 minutes

R Integration and Advanced Analytics in SQL Server 30 minutes
Introduction to R with SQL Server 10 minutes
Working with R Commands and Data Sources 10 minutes
Advanced Data Processing Using R Scripts 10 minutes

This module introduces Python programming concepts as applied within SQL Server. Learners examine how Python scripts are executed, how control flow and operators function, and how core data structures support analytical scripting. The module focuses on foundational Python skills that enhance SQL Server-based analytics.