Apply Advanced SQL Server Analytics and Programming
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Apply Advanced SQL Server Analytics and Programming
This course is part of Apply SQL Server Database Management & Analytics Specialization
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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
February 2026
15 assignments
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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.
What's included
6 videos3 assignments
6 videos•Total 63 minutes
- Executing Python Commands•10 minutes
- Python Comparison Operators•13 minutes
- If and Else Statements in Python•9 minutes
- Arithmetic Operators in Python•10 minutes
- Various Comparison and Logical Operators•13 minutes
- Tuples in Python•8 minutes
3 assignments•Total 50 minutes
- Python Programming Concepts for SQL Server•30 minutes
- Executing Python and Control Flow•10 minutes
- Python Operators and Data Structures•10 minutes
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