Summary  
This chapter covers recognizing, converting, and handling fundamental data types—such as strings, numbers, dates, booleans, arrays, objects, and binary—in JSON-based workflows to ensure values have the correct shape for downstream operations.  

General domain of usage  
Workflow automation

Data types define **what kind of value** a workflow handles like text, numbers, dates, booleans, lists, objects, or files. Knowing them ensures nodes **read, compare, and transform data correctly** instead of producing silent errors or misrouting logic.

Definition

n8n passes data between nodes as JSON in an **array-of-items** shape. If the type is wrong (string vs number, array vs object), nodes won't behave the way you expect.

When working with data in n8n, make sure each value is in the right shape before passing it downstream. Clean, normalized, and correctly typed data keeps workflows predictable and prevents silent failures.

- **Coerce data early:** convert strings to numbers before doing math;
- **Normalize text:** lowercase and trim before deduping or routing;
- **Dates:** generate with <code>{{$now}}</code>, compare in IF (Date & Time), reformat with Date & Time node;
- **Arrays:** use real arrays; Split Out to process items and Aggregate/Item Lists to recombine;
- **LLM outputs:** request strict JSON, then validate and normalize before merging.

With all of this, you should confidently recognize and convert data types, handle dates and arrays properly, manage binary files when needed, and quickly resolve type mismatches that disrupt workflow logic.

Which step helps prevent errors when performing math operations in n8n?

n8n is a flexible automation platform for connecting apps, transforming data, and building AI-powered workflows. You'll develop strong fundamentals through real, practical examples, covering triggers, JSON handling, data-flow theory, AI integration, webhooks, and complete automation builds. The focus is on understanding how information moves through a workflow and how to structure that information so nodes and APIs behave predictably. The result is the ability to design, debug, and ship reliable automations that work end to end.

A practical overview of n8n's environment, core tools, and the mindset needed to build automations. Concepts include using AI effectively, understanding how data flows through nodes, importing templates, and transforming raw inputs into structured output.

A focused exploration of the essential workflow components. Triggers, data manipulation nodes, HTTP requests, webhooks, and flow control logic. The material builds a clear mental model for how executions start, how data is shaped, and how routing decisions are made.

A deep dive into how n8n represents and processes data. Topics include JSON structure, reading full payloads, repairing malformed JSON, handling arrays and objects, and working with binary files. The goal is predictable, confident data handling across all workflows.

A step-by-step transformation of an ODT plan into a structured automation blueprint. The material covers reliable RSS feeds, preparing data for LLMs, generating tweets with Airtable loops, designing outcome-driven flows, and mapping the full workflow inside Miro.

A complete build from initial concept to final output. Topics include structuring the flow, normalizing API data, looping, error-proofing, and writing back to Airtable with polished automation that demonstrates end-to-end reliability and clarity.

Introduction to Data Types

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Introduction to Data Types