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.
Apply Advanced SQL Server Analytics and Programming
Apply Advanced SQL Server Analytics and Programming
This course is part of Apply SQL Server Database Management & Analytics Specialization
Instructor: EDUCBA
Included with
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.
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
February 2026
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.
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There are 4 modules in this course
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
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
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
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.
What's included
6 videos3 assignments
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