Working with Semi-structured Data with Snowflake from Pluralsight

Snowflake offers full support for semi-structured data. This course will teach you how to apply schema on read, loading, and writing to semi-structured file formats, working with the variant data type to interpret semi-structured fields and more.

The Snowflake Cloud Data Platform has full support for semi-structured data stored in formats such as JSON, XML, parquet, and more. In this course, Working with Semi-structured Data with Snowflake, you’ll learn to load, write, and query these data formats that are very common in data engineering projects.

First, you’ll explore Snowflake’s supported semi-structured file formats and the powerful and flexible variant data type. Next, you’ll discover how to load and write in popular formats such as JSON, parquet, and more. Finally, you’ll learn how to use Snowflake’s SQL implementation and built-in functions for querying semi-structured data.

When you’re finished with this course, you’ll have the skills and knowledge of working with semi-structured data to apply on your next data engineering project.

What's inside

Syllabus

Course Overview

Reading and Writing Semi-structured Data

Querying Semi-structured Files

Working with Semi-structured Fields

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Delves into working with semi-structured data that is common in data engineering projects

Students will better understand how to load, write, and query these data formats

Focuses on semi-structured data formats like JSON, XML, parquet, etc

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 Working with Semi-structured Data with Snowflake with these activities:

Review Concepts of Semi-structured Data

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Prepare for the course by refreshing your knowledge of semi-structured data and related concepts.

Browse courses on Semi-Structured Data

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Revisit textbooks or online resources to review the definitions and characteristics of semi-structured data.
Explore examples of semi-structured data in different formats, such as JSON, XML, and CSV.

Review Examples of SQL Queries on Semi-structured Data

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Enhance your SQL skills by analyzing real-world examples of queries on semi-structured data.

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Find resources that provide examples of SQL queries for semi-structured data.
Review the examples and identify common patterns and techniques.
Practice writing your own SQL queries based on these examples.

Follow Tutorials on Parquet File Handling

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Enhance your skills in loading and writing semi-structured data in Parquet format by following guided tutorials.

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Find tutorials on working with Parquet files in Snowflake.
Follow the tutorials to create a Parquet file and load it into Snowflake.
Query the Parquet table to extract and analyze the data.

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Practice Working with JSON and XML Files

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Reinforce your understanding of loading, writing, and querying semi-structured data in JSON and XML file formats.

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Create a sample JSON file with nested objects and arrays.
Use Snowflake to load the JSON file into a table.
Query the table to retrieve specific data from the JSON objects.
Repeat steps 1-3 for an XML file.

Explore Advanced Features of Snowflake for Semi-structured Data

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Expand your knowledge of Snowflake's capabilities for handling semi-structured data by following guided tutorials.

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Identify advanced features of Snowflake related to semi-structured data, such as user-defined functions (UDFs) and table functions.
Follow tutorials to implement these features in your Snowflake environment.

Host a Study Session on Variant Data Type

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Deepen your understanding of the variant data type by leading a discussion with peers.

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Prepare a presentation on the variant data type and its applications.
Host a virtual or in-person study session.
Facilitate a discussion on the topic and answer questions.

Develop a Data Visualization for Semi-structured Data

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Solidify your understanding of querying semi-structured data by creating an interactive data visualization.

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Choose a semi-structured dataset and identify key insights you want to visualize.
Use Snowflake to query the data and prepare it for visualization.
Select an appropriate visualization tool and create an interactive visualization.

Build a Sample Data Pipeline for Semi-structured Data

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Apply your learning by creating a fully functional data pipeline that processes and analyzes semi-structured data.

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Design the data pipeline, including data sources, transformations, and destination.
Implement the pipeline using Snowflake and other tools as needed.
Test the pipeline and analyze the results to ensure accuracy and efficiency.

Career center

Learners who complete Working with Semi-structured Data with Snowflake will develop knowledge and skills that may be useful to these careers:

Data Engineering Manager

Data Engineering Managers are responsible for leading and managing teams of Data Engineers. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for Data Engineering Managers to understand how to work with semi-structured data.

See salaries and explore the career path for Data Engineering Manager

Data Quality Analyst

Data Quality Analysts are responsible for ensuring the quality of data in an organization. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for Data Quality Analysts to understand how to work with semi-structured data.

See salaries and explore the career path for Data Quality Analyst

ETL Developer

ETL Developers are responsible for building and maintaining data pipelines. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for ETL Developers to understand how to work with semi-structured data. This course can help you to build a foundation in understanding how to work with these data formats in your day to day work.

See salaries and explore the career path for ETL Developer

Data Governance Analyst

Data Governance Analysts are responsible for developing and implementing data governance policies and procedures. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for Data Governance Analysts to understand how to work with semi-structured data.

See salaries and explore the career path for Data Governance Analyst

Data Scientist Manager

Data Scientist Managers are responsible for leading and managing teams of data scientists. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for Data Scientist Managers to understand how to work with semi-structured data.

See salaries and explore the career path for Data Scientist Manager

Data Integration Specialist

Data Integration Specialists are responsible for integrating data from multiple sources into a single data warehouse or data lake. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for Data Integration Specialists to understand how to work with semi-structured data.

See salaries and explore the career path for Data Integration Specialist

Data Analytics Manager

Data Analytics Managers are responsible for leading and managing teams of Data Analysts. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for Data Analytics Managers to understand how to work with semi-structured data.

See salaries and explore the career path for Data Analytics Manager

Data Architect

Data Architects design and build data architectures for organizations. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for Data Architects to understand how to work with semi-structured data. This course can help you to build a foundation in understanding how to work with these data formats in your day to day work.

See salaries and explore the career path for Data Architect

Data Warehouse Engineer

Data Warehouse Engineers are responsible for designing and building data warehouses. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for Data Warehouse Engineers to understand how to work with semi-structured data. This course can help you to build a foundation in understanding how to work with these data formats in your day to day work.

See salaries and explore the career path for Data Warehouse Engineer

Database Administrator

Database Administrators are responsible for the day to day operations of database systems. As more organizations adopt cloud-based data platforms like Snowflake, it is becoming increasingly important for DBAs to understand how to work with semi-structured data. This course can help you to build a foundation in understanding how to work with these data formats in your day to day work.

See salaries and explore the career path for Database Administrator

Business Analyst

Business Analysts often work with semi-structured data in formats such as JSON or XML when performing analysis and reporting. This course can help you to build a foundation in understanding how to work with these data formats and may be helpful in your career as a Business Analyst.

See salaries and explore the career path for Business Analyst

Data Scientist

Data Scientists often work with semi-structured data in formats such as JSON or XML. This course can help you to build a foundation in understanding how to work with these data formats and may be helpful in your career as a data scientist.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers often work with semi-structured data in formats such as JSON or XML when building applications. This course can help you to build a foundation in understanding how to work with these data formats and may be helpful in your career as a software engineer.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts often work with semi-structured data in formats such as JSON to perform analysis and reporting. This course can help you to build a foundation in understanding how to work with these data formats in your day to day work.

See salaries and explore the career path for Data Analyst

Data Engineer

As a Data Engineer, you will design and build data pipelines for your organization. With the rise in popularity of semi-structured data and the need for data engineers to understand how to work with these data formats, this course may be a helpful resource in your career.

See salaries and explore the career path for Data Engineer