Pancake Power: How You Can Eat Any JSON Complexities on Snowflake for Breakfast?

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Pancake is a tool from Snowflake’s Native App Accelerator that helps users manage JSON data. Pancake makes complex JSON data pipelines easy to build and downstream processes impossible to break. This article will help you to streamline the complexity that you might have faced with JSON.

The JSON Dilemma: Pros and Cons

We all understand that JSON’s flexible schema is both a gift and a challenge. We love it’s human-readable format is highly useful. However, on the other hand it can create headaches for data engineers. It is because of the lack of inconsistency. Think about a single field like “weight” appearing as a string in one record, a number in another, or even as a null value. Manually cleaning and standardizing this data across various systems and APIs can take days before you even start meaningful analysis. This is where the power of Pancake comes into play.

Enter Pancake: Your JSON Lifesaver

Pancake is a native app built to help you simplify the entire process of JSON management. It automatically handles schema discovery and analysis, mapping your JSON data to the appropriate Snowflake data types. Furthermore, Pancake can even generate SQL code for dynamic tables. This drastically reducing manual intervention and allows you to focus on extracting insights rather than cleaning data. Whether you're dealing with complex nested arrays or fields with constantly changing data types, Pancake will help you make your life easy.

Real-Life Impact: Tackling Complex JSON Data

Let’s walk through a real-world scenario where Pancake shines: Imagine you’re a data engineer working with a massive JSON dataset from a life sciences company. Your task is to ingest and analyze this data within Snowflake, but there are several challenges:

• Multiple Nested Levels: The JSON schema has several nested structures.
• Dynamic Fields: Some fields constantly change their data types.
• Nested Arrays: You have multiple arrays that need to be split into separate, relational tables.

This sounds like a lot of mundane tasks. But it is typical of a day-to-day life of a data engineer. However, you don’t need to worry, as you have Pancake. In this scenario, Pancake quickly analyzes a JSON schema with 216 attributes, 18 nested arrays, and 51 different objects - all within seconds! It helps you by splitting the complex data into relational tables and generated the necessary SQL code for you, saving you days of manual work. Pancake also continuously monitors the data for schema changes and sends email alerts when updates are needed.

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5 Ways Pancake Simplifies JSON Processing

• Quick Setup: Start by adding your data source. Pancake performs a rapid scan to analyze the structure of your JSON data.
• Detailed Analysis: Pancake breaks down every aspect of your JSON, providing insights into every nested object, array, and field type.
• Automated Data Structuring: Easily split complex data into relational tables, select primary and foreign keys, and join them for seamless data integration.
• SQL Code Generation: Pancake automates the creation of SQL code for dynamic tables. Just copy and paste the code into Snowflake and you’re good to go! ???
• Real-Time Monitoring: Pancake continuously checks for schema changes and alerts you, ensuring your pipelines remain robust and accurate over time.

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Why Pancake is a Game-Changer

Pancake is revolutionizing how data engineers handle JSON processing by automating what used to be a manual, error-prone task. With Pancake, you can:

• Save Time: Reduce days of manual work to mere seconds.
• Minimize Errors: Automatically map JSON to the correct Snowflake data types, reducing human error.
• Stay Resilient: Pancake continuously adapts to changing schemas without breaking workflows, ensuring your data pipelines remain intact.
• Keep Your Data in Snowflake: All processing happens within Snowflake—no need to move data elsewhere, maintaining speed and security.

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Conclusion

Pancake is a game-changer for data engineers who regularly deal with the complexities of JSON. By automating the most tedious aspects of #JSON processing—schema discovery, data structuring, and #SQL code generation—Pancake saves valuable time and minimizes errors, allowing engineers to focus on deriving insights and driving innovation. Its ability to adapt to changing schemas and monitor pipelines in real-time ensures that your workflows stay resilient and reliable. With Pancake, handling complex JSON data is no longer a bottleneck, but a streamlined part of your data operations.

You can read the article by IntellaNOVA on medlum:

https://medium.com/@ibbyrahmani/pancake-power-how-snowflake-helps-you-can-eat-any-json-complexities-for-breakfast-9087da3a4f08

This article was by inspired by "Transform Your JSON Data With Pancake In Snowflake: Simplify, Streamline, Succeed!" By Cameron Wasilewsky , Senior SE, at Snowflake

#DataEngineering #JSONProcessing #Snowflake #Automation #Pancake #DataTransformation #Innovation #Efficiency Saqib M. Tarik Dwiek Sridhar Ramaswamy Christian Kleinerman