Querying JSON, XML, and Temporal Data with T-SQL from Pluralsight

The most common scenario with SQL Server is querying structured data. But many do not know that it also allows storing and querying semi-structured data using XML and JSON; as well as obtaining values from any point in time with temporal tables.

Querying structured data is the most common scenario with SQL Server. However, there are cases where the schema is not known up front or more flexibility is needed. Additionally, sometimes it is required to know the value of a particular field at a specific point in time. In this course, Querying JSON, XML, and Temporal Data with T-SQL, you’ll gain the ability to use JSON and XML to store, modify, and query semi-structured data. First, you’ll learn how to work with JSON in SQL Server. Next, you’ll discover how to work with XML. Finally, you’ll explore how to retrieve values at any point in time with temporal tables. When you’re finished with this course, you’ll have the skills and knowledge of JSON, XML, and temporal tables needed to work with semi-structured data and historic data in SQL Server. Software required: Microsoft SQL Server.

What's inside

Syllabus

Course Overview

Querying JSON with T-SQL

Querying XML Data with T-SQL

Utilizing Temporal Tables

Final Takeaway

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Demonstrates how to use JSON and XML to store, modify, and retrieve semi-structured data, which is useful in many industries

Provides guidance on utilizing Temporal Tables to obtain historic data, enhancing understanding of data patterns and changes over time

Taught by experienced instructors, ensuring industry knowledge and up-to-date best practices

Requires foundational knowledge in SQL Server, which may not be suitable for complete beginners

Focuses on querying semi-structured data, which may not align with the needs of all learners seeking a comprehensive SQL Server course

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Querying JSON, XML, and Temporal Data with T-SQL with these activities:

Understand SQL and relational databases

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Refresh your understanding of SQL and relational databases before taking the course to ensure a solid foundation.

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Review SQL basics (data types, operators, queries)
Practice writing basic SQL queries

Review SQL Basics

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Ensure a strong foundation by refreshing your understanding of fundamental SQL concepts.

Browse courses on SQL

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Go through your notes or textbooks to cover essential SQL topics.
Complete a few practice problems to test your understanding.

Gather related research papers and articles

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Prepare for the course by collecting existing research works and articles relevant to the topics covered in the course.

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Search for research papers and articles using keywords related to the topic
Review the abstracts and introductions to identify relevant materials
Download and organize the selected materials

11 other activities

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Join a T-SQL Study Group

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Enhance your understanding through collaborative learning and peer support.

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Connect with your classmates or find a T-SQL study group online.
Schedule regular meetings to discuss course concepts and practice queries.
Share knowledge, ask questions, and provide feedback.
Work together on practice exercises or projects to reinforce your learning.

Follow T-SQL Basics Tutorial

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Reinforce the concepts of querying structured data with SQL Server by following an in-depth tutorial.

Browse courses on SQL Server

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Locate a comprehensive T-SQL basics tutorial online.
Set aside a dedicated time to work through the tutorial.
Follow the instructions and complete the exercises to practice querying.
Take notes or mark important concepts for future reference.

JSON Query Practice

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Reinforce your understanding of JSON querying by completing practice drills.

Browse courses on JSON

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Find specific values within JSON documents
Filter JSON documents based on criteria

Create custom SQL queries using JSON and XML

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Reinforce your understanding of the syntax and functionality of SQL queries by practicing writing your own queries.

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Choose a dataset containing JSON or XML data
Write SQL queries to extract and manipulate data from the chosen dataset
Test your queries and refine them as needed

JSON Querying Practice Problems

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Test your understanding of JSON querying by attempting practice problems.

Browse courses on JSON

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Find a set of JSON querying practice problems online or in a textbook.
Allocate specific time for solving these problems.
Attempt to solve the problems on your own.
Check your answers against provided solutions.
Review incorrect answers to identify areas for improvement.

Explain XML Data Retrieval

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Enhance your comprehension of XML data retrieval by creating a presentation or tutorial.

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Explain the structure and syntax of XML
Demonstrate how to retrieve data from XML using SQL

Build a T-SQL Coding Sandbox

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Solidify your understanding of T-SQL by creating a coding sandbox where you can experiment with queries.

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Choose a preferred coding environment.
Set up a database and connect it to your coding environment.
Write T-SQL queries to perform various operations on the data.
Test your queries and troubleshoot any errors.
Repeat with different datasets to cover a range of scenarios.

Explore Temporal Tables

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Expand your knowledge of temporal tables by completing guided tutorials.

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Understand the concept of temporal tables
Practice creating and querying temporal tables

Explore advanced features of JSON and XML support in SQL Server

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Expand your knowledge by delving into advanced features and techniques for working with JSON and XML in SQL Server.

Browse courses on JSON

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Identify the specific advanced features you want to explore
Search for tutorials or documentation on those features
Follow the tutorials and practice using the features

Create a Semi-Structured Data Querying Guide

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Deepen your understanding by creating a comprehensive guide that consolidates your knowledge of querying semi-structured data.

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Organize your notes and research on JSON and XML querying.
Write a detailed guide that covers different techniques and use cases.
Include examples and code snippets for clarity.
Review and refine your guide to ensure accuracy and completeness.

Develop a Temporal Data Analysis Dashboard

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Gain hands-on experience with temporal tables by building a dashboard to analyze historical data.

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Gather a dataset with temporal data.
Design a conceptual model for your dashboard.
Create temporal tables and populate them with the data.
Develop queries to extract insights from the temporal data.
Build interactive visualizations to display the insights on a dashboard.

Career center

Learners who complete Querying JSON, XML, and Temporal Data with T-SQL will develop knowledge and skills that may be useful to these careers:

Project Manager

Project Managers plan, execute, and close projects for businesses. This course may be useful for Project Managers because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in project management.

See salaries and explore the career path for Project Manager

Data Scientist

Data Scientists use data to build predictive models and make recommendations to businesses. This course may be useful for Data Scientists because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in data science.

See salaries and explore the career path for Data Scientist

Business Analyst

Business Analysts analyze business processes and make recommendations to businesses on how to improve their operations. This course may be useful for Business Analysts because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in business analysis.

See salaries and explore the career path for Business Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. This course may be useful for Software Engineers because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in software development.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts collect, process, and analyze data to identify trends and patterns. They use their findings to make recommendations to businesses on how to improve their operations. This course may be useful for Data Analysts because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in data analysis.

See salaries and explore the career path for Data Analyst

Database Administrator

Database Administrators manage and maintain databases to ensure that they are available and performant. This course may be useful for Database Administrators because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often stored in databases.

See salaries and explore the career path for Database Administrator

Data Engineer

Data Engineers design, build, and maintain data pipelines to ensure that data is available to businesses in a timely and accurate manner. This course may be useful for Data Engineers because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in data engineering.

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Business Intelligence Analyst

Business Intelligence Analysts use data to identify trends and patterns and make recommendations to businesses on how to improve their operations. This course may be useful for Business Intelligence Analysts because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in business intelligence.

See salaries and explore the career path for Business Intelligence Analyst

Data Governance Specialist

Data Governance Specialists develop and implement data governance policies and procedures for businesses. This course may be useful for Data Governance Specialists because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often subject to data governance policies and procedures.

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Database Developer

Database Developers design and develop databases for businesses. This course may be useful for Database Developers because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often stored in databases.

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Information Architect

Information Architects design and implement information systems for businesses. This course may be useful for Information Architects because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in information architecture.

See salaries and explore the career path for Information Architect

Data Warehouse Architect

Data Warehouse Architects design and implement data warehouses for businesses. This course may be useful for Data Warehouse Architects because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often stored in data warehouses.

See salaries and explore the career path for Data Warehouse Architect

Data Integration Specialist

Data Integration Specialists design and implement data integration solutions for businesses. This course may be useful for Data Integration Specialists because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often involved in data integration.

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Data Modeler

Data Modelers design and implement data models for businesses. This course may be useful for Data Modelers because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in data modeling.

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Enterprise Data Architect

Enterprise Data Architects design and implement data architectures for businesses. This course may be useful for Enterprise Data Architects because it provides them with the skills and knowledge needed to work with semi-structured and historic data, which is often used in data architecture.

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